Genetic Associations Among Inflammation, White Matter Architecture, and Extracellular Free Water.

Phenotypic and genetic relationships between white matter microstructure (i.e., fractional anisotropy [FA]) and peripheral inflammatory responses (i.

Effects of gene dosage on cognitive ability: A function-based association study across brain and non-brain processes.

Copy-number variants (CNVs) that increase the risk for neurodevelopmental disorders also affect cognitive ability. However, such CNVs remain challenging to study due to their scarcity, limiting our understanding of gene-dosage-sensitive biological processes linked to cognitive ability. We performed a genome-wide association study (GWAS) in 258,292 individuals, which identified-for the first time-a duplication at 2q12.

Virtual stressors with real impact: what virtual reality-based biobehavioral research can teach us about typical and atypical stress responsivity.

Stress contributes to transdiagnostic morbidity and mortality across a wide range of physical and mental health problems. VR tasks have been validated as stressors with robust effect sizes for VR-based stressors to evoke stress across the most common autonomic and adrenocortical stress biomarkers. However, meta-analytic validation of VR stressors have resulted in inconsistent logic: why should something that isn't real evoke a very real suite of stress responses? This review posits that conceptually addressing this question requires differentiating a cause, "stressor", from effects, "stress".

Characterization of pain and somatization and its relationship with psychopathology in early onset psychosis.

Background: Early onset psychosis (EOP) frequently presents with a severe clinical phenotype and poor long-term prognosis. Clinical experience suggests that individuals with EOP have abnormal pain and somatosensory processing, yet relative to adult-onset psychosis, pain and somatic sensory processing in EOP have rarely been studied.

Methods: The history of two characteristic patients is described to illustrate clinical presentations of pain in EOP patients.

Copy-number variants differ in frequency across genetic ancestry groups.

Copy-number variants (CNVs) have been implicated in a variety of neuropsychiatric and cognitive phenotypes. We found that deleterious CNVs are less prevalent in non-European ancestry groups than they are in European ancestry groups of both the UK Biobank (UKBB) and a US replication cohort (SPARK). We also identified specific recurrent CNVs that consistently differ in frequency across ancestry groups in both the UKBB and SPARK.

Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model.

When virtual reality becomes psychoneuroendocrine reality: A stress(or) review.

This review article was awarded the Dirk Hellhammer award from ISPNE in 2023. It explores the dynamic relationship between stressors and stress from a historical view as well as a vision towards the future of stress research via virtual reality (VR). We introduce the concept of a "syncytium," a permeable boundary that blurs the distinction between stress and stressor, in order to understand why the field of stress biology continues to inadequately measure stress alone as a proxy for the force of external stressors.

Bridging the gap: improving correspondence between low-field and high-field magnetic resonance images in young people.

Background: Portable low-field-strength magnetic resonance imaging (MRI) systems represent a promising alternative to traditional high-field-strength systems with the potential to make MR technology available at scale in low-resource settings. However, lower image quality and resolution may limit the research and clinical potential of these devices. We tested two super-resolution methods to enhance image quality in a low-field MR system and compared their correspondence with images acquired from a high-field system in a sample of young people.

Using rare genetic mutations to revisit structural brain asymmetry.

Asymmetry between the left and right hemisphere is a key feature of brain organization. Hemispheric functional specialization underlies some of the most advanced human-defining cognitive operations, such as articulated language, perspective taking, or rapid detection of facial cues. Yet, genetic investigations into brain asymmetry have mostly relied on common variants, which typically exert small effects on brain-related phenotypes.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates.

Riemannian frameworks for the harmonization of resting-state functional MRI scans.

Magnetic Resonance Imaging provides unprecedented images of the brain. Unfortunately, scanners and acquisition protocols can significantly impact MRI scans. The development of statistical methods able to reduce this variability without altering the relevant information in the scans, often coined harmonization methods, has been the topic of an increasing research effort supported by the recent growth of publicly available neuroimaging data sets and new possibilities for combining them to achieve greater statistical power.

Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia.

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.

Multimodal Neuroimaging Summary Scores as Neurobiological Markers of Psychosis.

Background And Hypothesis: Structural brain alterations are well-established features of schizophrenia but they do not effectively predict disease/disease risk. Similar to polygenic risk scores in genetics, we integrated multifactorial aspects of brain structure into a summary "Neuroscore" and examined its potential as a marker of disease.

Study Design: We extracted measures from T1-weighted scans and diffusion tensor imaging (DTI) models from three studies with schizophrenia and healthy individuals.