Genomic loci influence patterns of structural covariance in the human brain.

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Prevalence of Neuroradiological Abnormalities in First-Episode Psychosis: A Systematic Review and Meta-analysis.

Importance: Individuals presenting with first-episode psychosis (FEP) may have a secondary ("organic") etiology to their symptoms that can be identified using neuroimaging. Because failure to detect such cases at an early stage can have serious clinical consequences, it has been suggested that brain magnetic resonance imaging (MRI) should be mandatory for all patients presenting with FEP. However, this remains a controversial issue, partly because the prevalence of clinically relevant MRI abnormalities in this group is unclear. Objective: To derive a meta-analytic estimate of the prevalence of clinically relevant neuroradiological abnormalities in FEP. Data Sources: Electronic databases Ovid, MEDLINE, PubMed, Embase, PsychINFO, and Global Health were searched up to July 2021. References and citations of included articles and review articles were also searched. Study Selection: Magnetic resonance imaging studies of patients with FEP were included if they reported the frequency of intracranial radiological abnormalities. Data Extraction and Synthesis: Independent extraction was undertaken by 3 researchers and a random-effects meta-analysis of pooled proportions was calculated. Moderators were tested using subgroup and meta-regression analyses. Heterogeneity was evaluated using the I2 index. The robustness of results was evaluated using sensitivity analyses. Publication bias was assessed using funnel plots and Egger tests. Main Outcomes and Measures: Proportion of patients with a clinically relevant radiological abnormality (defined as a change in clinical management or diagnosis); number of patients needed to scan to detect 1 such abnormality (number needed to assess [NNA]). Results: Twelve independent studies (13 samples) comprising 1613 patients with FEP were included. Of these patients, 26.4% (95% CI, 16.3%-37.9%; NNA of 4) had an intracranial radiological abnormality, and 5.9% (95% CI, 3.2%-9.0%) had a clinically relevant abnormality, yielding an NNA of 18. There were high degrees of heterogeneity among the studies for these outcomes, 95% to 73%, respectively. The most common type of clinically relevant finding was white matter abnormalities, with a prevalence of 0.9% (95% CI, 0%-2.8%), followed by cysts, with a prevalence of 0.5% (95% CI, 0%-1.4%). Conclusions and Relevance: This systematic review and meta-analysis found that 5.9% of patients presenting with a first episode of psychosis had a clinically relevant finding on MRI. Because the consequences of not detecting these abnormalities can be serious, these findings support the use of MRI as part of the initial clinical assessment of all patients with FEP.

Serum immune markers and transition to psychosis in individuals at clinical high risk.

Individuals at clinical high risk (CHR) for psychosis have been found to have altered cytokine levels, but whether these changes are related to clinical outcomes remains unclear. We addressed this issue by measuring serum levels of 20 immune markers in 325 participants (n = 269 CHR, n = 56 healthy controls) using multiplex immunoassays, and then followed up the CHR sample to determine their clinical outcomes. Among 269 CHR individuals, 50 (18.6 %) developed psychosis by two years. Univariate and machine learning techniques were used to compare levels of inflammatory markers in CHR subjects and healthy controls, and in CHR subjects who had (CHR-t), or had not (CHR-nt) transitioned to psychosis. An ANCOVA identified significant group differences (CHR-t, CHR-nt and controls) and post-hoc tests indicated that VEGF levels and the IL-10/IL-6 ratio were significantly higher in CHR-t than CHR-nt, after adjusting for multiple comparisons. Using a penalised logistic regression classifier, CHR participants were distinguished from controls with an area-under the curve (AUC) of 0.82, with IL-6 and IL-4 levels the most important discriminating features. Transition to psychosis was predicted with an AUC of 0.57, with higher VEGF level and IL-10/IL-6 ratio the most important discriminating features. These data suggest that alterations in the levels of peripheral immune markers are associated with the subsequent onset of psychosis. The association with increased VEGF levels could reflect altered blood-brain-barrier (BBB) permeability, while the link with an elevated IL-10/IL-6 ratio points to an imbalance between anti- and pro-inflammatory cytokines.

Brief Report: Specificity of Interpersonal Synchrony Deficits to Autism Spectrum Disorder and Its Potential for Digitally Assisted Diagnostics.

Reliably diagnosing autism spectrum disorders (ASD) in adulthood poses a challenge to clinicians due to the absence of specific diagnostic markers. This study investigated the potential of interpersonal synchrony (IPS), which has been found to be reduced in ASD, to augment the diagnostic process. IPS was objectively assessed in videos of diagnostic interviews in a representative referral population from two specialized autism outpatient clinics. In contrast to the current screening tools that could not reliably differentiate, we found a significant reduction of IPS in interactions with individuals later diagnosed with ASD (n = 16) as opposed to those not receiving a diagnosis (n = 23). While these findings need to be validated in larger samples, they nevertheless underline the potential of digitally-enhanced diagnostic processes for ASD.

A multivariate neuromonitoring approach to neuroplasticity-based computerized cognitive training in recent onset psychosis.

Two decades of studies suggest that computerized cognitive training (CCT) has an effect on cognitive improvement and the restoration of brain activity. Nevertheless, individual response to CCT remains heterogenous, and the predictive potential of neuroimaging in gauging response to CCT remains unknown. We employed multivariate pattern analysis (MVPA) on whole-brain resting-state functional connectivity (rsFC) to (neuro)monitor clinical outcome defined as psychosis-likeness change after 10-hours of CCT in recent onset psychosis (ROP) patients. Additionally, we investigated if sensory processing (SP) change during CCT is associated with individual psychosis-likeness change and cognitive gains after CCT. 26 ROP patients were divided into maintainers and improvers based on their SP change during CCT. A support vector machine (SVM) classifier separating 56 healthy controls (HC) from 35 ROP patients using rsFC (balanced accuracy of 65.5%, P < 0.01) was built in an independent sample to create a naturalistic model representing the HC-ROP hyperplane. This model was out-of-sample cross-validated in the ROP patients from the CCT trial to assess associations between rsFC pattern change, cognitive gains and SP during CCT. Patients with intact SP threshold at baseline showed improved attention despite psychosis status on the SVM hyperplane at follow-up (p < 0.05). Contrarily, the attentional gains occurred in the ROP patients who showed impaired SP at baseline only if rsfMRI diagnosis status shifted to the healthy-like side of the SVM continuum. Our results reveal the utility of MVPA for elucidating treatment response neuromarkers based on rsFC-SP change and pave the road to more personalized interventions.

Prevention of Psychosis: Advances in Detection, Prognosis, and Intervention.

Importance: Detection, prognosis, and indicated interventions in individuals at clinical high risk for psychosis (CHR-P) are key components of preventive psychiatry. Objective: To provide a comprehensive, evidence-based systematic appraisal of the advancements and limitations of detection, prognosis, and interventions for CHR-P individuals and to formulate updated recommendations. Evidence Review: Web of Science, Cochrane Central Register of Reviews, and Ovid/PsychINFO were searched for articles published from January 1, 2013, to June 30, 2019, to identify meta-analyses conducted in CHR-P individuals. MEDLINE was used to search the reference lists of retrieved articles. Data obtained from each article included first author, year of publication, topic investigated, type of publication, study design and number, sample size of CHR-P population and comparison group, type of comparison group, age and sex of CHR-P individuals, type of prognostic assessment, interventions, quality assessment (using AMSTAR [Assessing the Methodological Quality of Systematic Reviews]), and key findings with their effect sizes. Findings: In total, 42 meta-analyses published in the past 6 years and encompassing 81 outcomes were included. For the detection component, CHR-P individuals were young (mean [SD] age, 20.6 [3.2] years), were more frequently male (58%), and predominantly presented with attenuated psychotic symptoms lasting for more than 1 year before their presentation at specialized services. CHR-P individuals accumulated several sociodemographic risk factors compared with control participants. Substance use (33% tobacco use and 27% cannabis use), comorbid mental disorders (41% with depressive disorders and 15% with anxiety disorders), suicidal ideation (66%), and self-harm (49%) were also frequently seen in CHR-P individuals. CHR-P individuals showed impairments in work (Cohen d = 0.57) or educational functioning (Cohen d = 0.21), social functioning (Cohen d = 1.25), and quality of life (Cohen d = 1.75). Several neurobiological and neurocognitive alterations were confirmed in this study. For the prognosis component, the prognostic accuracy of CHR-P instruments was good, provided they were used in clinical samples. Overall, risk of psychosis was 22% at 3 years, and the risk was the highest in the brief and limited intermittent psychotic symptoms subgroup (38%). Baseline severity of attenuated psychotic (Cohen d = 0.35) and negative symptoms (Cohen d = 0.39) as well as low functioning (Cohen d = 0.29) were associated with an increased risk of psychosis. Controlling risk enrichment and implementing sequential risk assessments can optimize prognostic accuracy. For the intervention component, no robust evidence yet exists to favor any indicated intervention over another (including needs-based interventions and control conditions) for preventing psychosis or ameliorating any other outcome in CHR-P individuals. However, because the uncertainty of this evidence is high, needs-based and psychological interventions should still be offered. Conclusions and Relevance: This review confirmed recent substantial advancements in the detection and prognosis of CHR-P individuals while suggesting that effective indicated interventions need to be identified. This evidence suggests a need for specialized services to detect CHR-P individuals in primary and secondary care settings, to formulate a prognosis with validated psychometric instruments, and to offer needs-based and psychological interventions.

Predicting Response to Repetitive Transcranial Magnetic Stimulation in Patients With Schizophrenia Using Structural Magnetic Resonance Imaging: A Multisite Machine Learning Analysis.

Background: The variability of responses to plasticity-inducing repetitive transcranial magnetic stimulation (rTMS) challenges its successful application in psychiatric care. No objective means currently exists to individually predict the patients' response to rTMS. Methods: We used machine learning to develop and validate such tools using the pre-treatment structural Magnetic Resonance Images (sMRI) of 92 patients with schizophrenia enrolled in the multisite RESIS trial (http://clinicaltrials.gov, NCT00783120): patients were randomized to either active (N = 45) or sham (N = 47) 10-Hz rTMS applied to the left dorsolateral prefrontal cortex 5 days per week for 21 days. The prediction target was nonresponse vs response defined by a ≥20% pre-post Positive and Negative Syndrome Scale (PANSS) negative score reduction. Results: Our models predicted this endpoint with a cross-validated balanced accuracy (BAC) of 85% (nonresponse/response: 79%/90%) in patients receiving active rTMS, but only with 51% (48%/55%) in the sham-treated sample. Leave-site-out cross-validation demonstrated cross-site generalizability of the active rTMS predictor despite smaller training samples (BAC: 71%). The predictive pre-treatment pattern involved gray matter density reductions in prefrontal, insular, medio-temporal, and cerebellar cortices, and increments in parietal and thalamic structures. The low BAC of 58% produced by the active rTMS predictor in sham-treated patients, as well as its poor performance in predicting positive symptom courses supported the therapeutic specificity of this brain pattern. Conclusions: Individual responses to active rTMS in patients with predominant negative schizophrenia may be accurately predicted using structural neuromarkers. Further multisite studies are needed to externally validate the proposed treatment stratifier and develop more personalized and biologically informed rTMS interventions.