In vivo white matter microstructure in adolescents with early-onset psychosis: a multi-site mega-analysis

Emerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset <18 years). However, as neuroimaging methods vary and sample sizes are modest, results remain inconclusive. Using harmonized data processing protocols and a mega-analytic approach, we compared white matter microstructure in EOP and healthy controls using diffusion tensor imaging (DTI). Our sample included 321 adolescents with EOP (median age = 16.6 years, interquartile range (IQR) = 2.14, 46.4% females) and 265 adolescent healthy controls (median age = 16.2 years, IQR = 2.43, 57.7% females) pooled from nine sites. All sites extracted mean fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) for 25 white matter regions of interest per participant. ComBat harmonization was performed for all DTI measures to adjust for scanner differences. Multiple linear regression models were fitted to investigate case-control differences and associations with clinical variables in regional DTI measures. We found widespread lower FA in EOP compared to healthy controls, with the largest effect sizes in the superior longitudinal fasciculus (Cohen’s d = 0.37), posterior corona radiata (d = 0.32), and superior fronto‐ occipital fasciculus (d = 0.31). We also found widespread higher RD and more localized higher MD and AD. We detected significant effects of diagnostic subgroup, sex, and duration of illness, but not medication status. Using the largest EOP DTI sample to date, our findings suggest a profile of widespread white matter microstructure alterations in adolescents with EOP, most prominently in male individuals with early-onset schizophrenia and individuals with a shorter duration of illness

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18–72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18–73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen’s d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions

White matter connectivity, cognition, symptoms and genetic risk factors in Schizophrenia

Schizophrenia is a highly heritable complex neuropsychiatric disorder with a lifetime prevalence of around 1%. It is often characterised by impaired white matter structural dysconnectivity. In vivo and post-mortem alterations in white matter microstructure have been reported, along with differences in the topology of the structural connectome; overall these suggest a reduced communication between distal brain regions. Schizophrenia is characterised by persistent cognitive impairments that predate the occurrence of symptoms and have been shown to have a neural foundation reflecting aberrant brain connectivity. So far, 179 independent genome-wide significant single nucleotide polymorphisms (SNPs) have been associated with a diagnosis of schizophrenia. The high heritability and polygenicity of schizophrenia, white matter parameters and cognitive functions provides a great opportunity to investigate the potential relationships between them due to the genetic overlap shared among these factors. This work investigates the psychopathology of schizophrenia from a neurobiological, psychological and genetic perspective. The datasets used here include data from the Scottish Family Mental Health (SFMH) study, the Lothian Birth Cohort 1936 (LBC1936) and UK Biobank. The main goal of this thesis was to study white matter microstructure in schizophrenia using diffusion MRI (dMRI) data. Our first aim was to examine whether processing speed mediated the association between white matter structure and general intelligence in patients diagnosed with schizophrenia in the SFMH study. Secondly, we investigated specific networks from the structural connectome and their topological properties in both healthy controls and patients diagnosed with schizophrenia in the SFMH study. These networks were studied alongside cognition, clinical symptoms and polygenic risk factor for schizophrenia (szPGRS). The third aim of this thesis was to study the effects of szPGRS on the longitudinal trajectories of white matter connectivity (measured using tractography and graph theory metrics) in the LBC1936 over a period of three-years. Finally, we derived the salience network which has been previously associated with schizophrenia and examined the effect of szPGRS on the grey matter nodes associated with this network and their connecting white matter tracts in UK Biobank. With regards to the first aim, we found that processing speed significantly mediates the association between a general factor of white matter structure and general intelligence in schizophrenia. These results suggest that, as in healthy controls, processing speed acts as a key cognitive resource facilitating higher order cognition by allowing multiple cognitive processes to be simultaneously available. Secondly, we found that several graph theory metrics were significantly impaired in patients diagnosed with schizophrenia compared with healthy controls. Moreover, these metrics were significantly associated with intelligence. There was a strong tendency towards significance for a correlation between intelligence and szPGRS that was significantly mediated by graph theory metrics in both healthy controls and schizophrenia patients of the SFMH study. These results are consistent with the hypothesis that intelligence deficits are associated with a genetic risk for schizophrenia, which is mediated via the disruption of distributed brain networks. In the LBC1936 we found that higher szPGRS showed significant associations with longitudinal increases in MD in several white matter tracts. Significant declines over time were observed in graph theory metrics. Overall these findings suggest that szPGRS confer risk for ageing-related degradation of some aspects of structural connectivity. Moreover, we found significant associations between higher szPGRS and decreases in cortical thickness, in particular, in a latent factor for cortical thickness of the salience network. Taken together, our findings suggest that white matter connectivity plays a significant role in the disorder and its psychopathology. The computation of the structural connectome has improved our understanding of the topological characteristics of the brain’s networks in schizophrenia and how it relates to the microstructural level. In particular, the data suggests that white matter structure provides a neuroanatomical substrate for cognition and that structural connectivity mediates the relationship between szPGRS and intelligence. Additionally, these results suggest that szPGRS may have a role in age-related changes in brain structural connectivity, even among individuals who are not diagnosed with schizophrenia. Further work will be required to validate these results and will hopefully examine additional risk factors and biomarkers, with the ultimate aims of improving scientific knowledge about schizophrenia and conceivably of improving clinical practice

Polygenic contribution to the relationship of loneliness and social isolation with schizophrenia

Previous research suggests an association of loneliness and social isolation (LNL-ISO) with schizophrenia. Here, we demonstrate a LNL-ISO polygenic score contribution to schizophrenia risk in an independent case-control sample (N = 3,488). We then subset schizophrenia predisposing variation based on its effect on LNL-ISO. We find that genetic variation with concordant effects in both phenotypes shows significant SNP-based heritability enrichment, higher polygenic contribution in females, and positive covariance with mental disorders such as depression, anxiety, attention-deficit hyperactivity disorder, alcohol dependence, and autism. Conversely, genetic variation with discordant effects only contributes to schizophrenia risk in males and is negatively correlated with those disorders. Mendelian randomization analyses demonstrate a plausible bi-directional causal relationship between LNL-ISO and schizophrenia, with a greater effect of LNL-ISO liability on schizophrenia than vice versa. These results illustrate the genetic footprint of LNL-ISO on schizophrenia

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I$^{2}$ = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions

The relationship between white matter microstructure and general cognitive ability in patients with schizophrenia and healthy participants in the ENIGMA Consortium

Objective: Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants. Methods: The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition. Results: Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges’ g]=0.27, CI=0.17–0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05–0.35) and healthy participant groups (effect size=0.32, CI=0.18–0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18–0.37), the patient group (effect size=0.23, CI=0.09–0.38), and the healthy participant group (effect size=0.31, CI=0.18–0.44). Conclusions: This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association

10Kin1day: a bottom-up neuroimaging initiative

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain

Addendum:Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways

No abstract available

Sex differences in the adult human brain:Evidence from 5216 UK Biobank participants

Sex differences in the human brain are of interest for many reasons: for example, there are sex differences in the observed prevalence of psychiatric disorders and in some psychological traits that brain differences might help to explain. We report the largest single-sample study of structural and functional sex differences in the human brain (2750 female, 2466 male participants; mean age 61.7 years, range 44–77 years). Males had higher raw volumes, raw surface areas, and white matter fractional anisotropy; females had higher raw cortical thickness and higher white matter tract complexity. There was considerable distributional overlap between the sexes. Subregional differences were not fully attributable to differences in total volume, total surface area, mean cortical thickness, or height. There was generally greater male variance across the raw structural measures. Functional connectome organization showed stronger connectivity for males in unimodal sensorimotor cortices, and stronger connectivity for females in the default mode network. This large-scale study provides a foundation for attempts to understand the causes and consequences of sex differences in adult brain structure and function