Deviations from normative brain white and gray matter structure are associated with psychopathology in youth

Contains fulltext : 285929.pdf (Publisher’s version ) (Open Access

Delineating disorder-general and disorder-specific dimensions of psychopathology from functional brain networks in a developmental clinical sample

The interplay between functional brain network maturation and psychopathology during development remains elusive. To establish the structure of psychopathology and its neurobiological mechanisms, mapping of both shared and unique functional connectivity patterns across developmental clinical populations is needed. We investigated shared associations between resting-state functional connectivity and psychopathology in children and adolescents aged 5–21 (n =1689). Specifically, we used partial least squares (PLS) to identify latent variables (LV) between connectivity and both symptom scores and diagnostic information. We also investigated associations between connectivity and each diagnosis specifically, controlling for other diagnosis categories. PLS identified five significant LVs between connectivity and symptoms, mapping onto the psychopathology hierarchy. The first LV resembled a general psychopathology factor, followed by dimensions of internalising- externalising, neurodevelopment, somatic complaints, and thought problems. Another PLS with diagnostic data revealed one significant LV, resembling a cross-diagnostic case-control pattern. The diagnosis-specific PLS identified a unique connectivity pattern for autism spectrum disorder (ASD). All LVs were associated with distinct patterns of functional connectivity. These dimensions largely replicated in an independent sample (n = 420) from the same dataset, as well as to an independent cohort (n =3504). This suggests that covariance in developmental functional brain networks supports transdiagnostic dimensions of psychopathology.publishedVersio

Shared pattern of impaired social communication and cognitive ability in the youth brain across diagnostic boundaries

Background Abnormalities in brain structure are shared across diagnostic categories. Given the high rate of comorbidity, the interplay of relevant behavioural factors may also cross these classic boundaries. Methods We aimed to detect brain-based dimensions of behavioural factors using canonical correlation and independent component analysis in a clinical youth sample (n = 1732, 64 % male, age: 5–21 years). Results We identified two correlated patterns of brain structure and behavioural factors. The first mode reflected physical and cognitive maturation (r = 0.92, p = .005). The second mode reflected lower cognitive ability, poorer social skills, and psychological difficulties (r = 0.92, p = .006). Elevated scores on the second mode were a common feature across all diagnostic boundaries and linked to the number of comorbid diagnoses independently of age. Critically, this brain pattern predicted normative cognitive deviations in an independent population-based sample (n = 1253, 54 % female, age: 8–21 years), supporting the generalisability and external validity of the reported brain-behaviour relationships. Conclusions These results reveal dimensions of brain-behaviour associations across diagnostic boundaries, highlighting potent disorder-general patterns as the most prominent. In addition to providing biologically informed patterns of relevant behavioural factors for mental illness, this contributes to a growing body of evidence in favour of transdiagnostic approaches to prevention and intervention.publishedVersio

Differences in diurnal saliva cortisol variation between patients with Chronic Fatigue Syndrome and patients with Fibromyalgia, and the role of Insomnia Severity as a predictor.

Objective: Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (CFS/ME) is a severe chronic disease, that severely impacts the quality of life. The underlying pathophysiology of CFS/ME is still unknown, but a substantial body of research has focused on the potential role of the hypothalamic-pituitary-adrenal (HPA) axis. The overarching aim of this study was to further examine the differences in HPA axis functioning in CFS/ME and Fibromyalgia patient groups. This was done by examining diurnal cortisol variance, and evening cortisol levels using saliva samples. Method: Female patients with CFS/ME (n = 18) and Fibromyalgia (n = 15) were recruited from a 10-week specialized multidisciplinary rehabilitation program in Trondheim, Norway. Six saliva cortisol samples were collected from each participant at fixed time points throughout the day. Participants also completed self-report questionnaires assessing their level of insomnia severity, fatigue, anxiety, depression, and pain intensity. Results: CFS/ME patients exhibited significantly less cortisol variation within a day, compared to fibromyalgia patients. Insomnia severity was not a significant predictor of cortisol variation within a day. However, higher levels of insomnia were significantly associated with higher levels of cortisol in the evening irrespectively of primary diagnosis. Conclusion: CFS/ME patients had significantly less cortisol variance than fibromyalgia patients, still they do not significantly differ in levels of symptoms such as fatigue, pain intensity, insomnia severity, anxiety, and depression. This may indicate that significantly lower cortisol variance is maintained by other mechanisms in CFS/ME patients compared to Fibromyalgia patients, further suggesting different pathophysiology between the two disorders

Linking sarcopenia, brain structure and cognitive performance: a large-scale UK Biobank study

La sarcopenia se refiere a la pérdida de masa y función muscular relacionada con la edad y está relacionada con el deterioro de la salud somática y cerebral, incluido el deterioro cognitivo y la enfermedad de Alzheimer. Sin embargo, las relaciones entre sarcopenia, estructura cerebral y cognición no se conocen bien. Aquí, investigamos las asociaciones entre los rasgos sarcopénicos, la estructura cerebral y el rendimiento cognitivo. Se incluyeron 33.709 participantes del Biobanco del Reino Unido (54,2% mujeres; rango de edad de 44 a 82 años) con imágenes de resonancia magnética estructural y de difusión, infiltración de grasa del músculo del muslo (n = 30.561) a partir de imágenes de resonancia magnética de cuerpo entero (indicador de calidad muscular) y rendimiento cognitivo general según lo indicado por el primer componente principal de un análisis de componentes principales en múltiples pruebas cognitivas (n = 22 530). De estos, 1.703 participantes calificaron para probable sarcopenia debido a su baja fuerza de prensión manual, y asignamos a los 32.006 participantes restantes al grupo sin sarcopenia. Utilizamos regresión lineal múltiple para probar cómo los rasgos sarcopénicos (sarcopenia probable versus no sarcopenia y porcentaje de infiltración de grasa del músculo del muslo) se relacionan con el rendimiento cognitivo y la estructura cerebral (espesor y área cortical, anisotropía fraccional de la sustancia blanca y volúmenes cerebrales profundos e inferiores). A continuación, utilizamos modelos de ecuaciones estructurales para probar si la estructura cerebral mediaba la asociación entre los rasgos sarcopénicos y cognitivos. Ajustamos todos los análisis estadísticos para detectar factores de confusión. Mostramos que los rasgos sarcopénicos (probable sarcopenia versus no sarcopenia e infiltración de grasa muscular) se asocian significativamente con un menor rendimiento cognitivo y diversas medidas de imágenes de resonancia magnética cerebral. En la probable sarcopenia, para las regiones cerebrales incluidas, observamos una anisotropía fraccional de sustancia blanca significativamente más baja y generalizada (77,1% de los tractos), volúmenes cerebrales regionales predominantemente más bajos (61,3% de los volúmenes) y un espesor cortical más delgado (37,9% de las parcelaciones), con | r| tamaños del efecto en (0.02, 0.06) y valores de P en (0.0002, 4.2e-29). Por el contrario, observamos asociaciones significativas entre una mayor infiltración de grasa muscular y un espesor cortical más delgado y generalizado (76,5% de las parcelaciones), una menor anisotropía fraccional de la sustancia blanca (62,5% de los tractos) y volúmenes cerebrales predominantemente más bajos (35,5% de los volúmenes), con |r | tamaños del efecto en (0.02, 0.07) y valores de P en (0.0002, 1.9e-31). Las regiones que mostraron los tamaños de efecto más significativos en la corteza, la materia blanca y los volúmenes fueron las del sistema sensoriomotor. El análisis de modelos de ecuaciones estructurales reveló que las regiones sensoriomotoras del cerebro median el vínculo entre los rasgos sarcopénicos y cognitivos [sarcopenia probable: valores de P en (0,0001, 1,0e-11); infiltración de grasa muscular: valores de P en (7.7e-05, 1.7e-12)]. Nuestros hallazgos muestran asociaciones significativas entre los rasgos sarcopénicos, la estructura cerebral y el rendimiento cognitivo en una población de adultos de mediana edad y mayores. Los análisis de mediación sugieren que la estructura cerebral regional media la asociación entre los rasgos sarcopénicos y cognitivos, con posibles implicaciones para el desarrollo y la prevención de la demencia.Sarcopenia refers to age-related loss of muscle mass and function and is related to impaired somatic and brain health, including cognitive decline and Alzheimer’s disease. However, the relationships between sarcopenia, brain structure and cognition are poorly understood. Here, we investigate the associations between sarcopenic traits, brain structure and cognitive performance. We included 33 709 UK Biobank participants (54.2% female; age range 44–82 years) with structural and diffusion magnetic resonance imaging, thigh muscle fat infiltration (n = 30 561) from whole-body magnetic resonance imaging (muscle quality indicator) and general cognitive performance as indicated by the first principal component of a principal component analysis across multiple cognitive tests (n = 22 530). Of these, 1703 participants qualified for probable sarcopenia based on low handgrip strength, and we assigned the remaining 32 006 participants to the non-sarcopenia group. We used multiple linear regression to test how sarcopenic traits (probable sarcopenia versus non-sarcopenia and percentage of thigh muscle fat infiltration) relate to cognitive performance and brain structure (cortical thickness and area, white matter fractional anisotropy and deep and lower brain volumes). Next, we used structural equation modelling to test whether brain structure mediated the association between sarcopenic and cognitive traits. We adjusted all statistical analyses for confounders. We show that sarcopenic traits (probable sarcopenia versus non-sarcopenia and muscle fat infiltration) are significantly associated with lower cognitive performance and various brain magnetic resonance imaging measures. In probable sarcopenia, for the included brain regions, we observed widespread significant lower white matter fractional anisotropy (77.1% of tracts), predominantly lower regional brain volumes (61.3% of volumes) and thinner cortical thickness (37.9% of parcellations), with |r| effect sizes in (0.02, 0.06) and P-values in (0.0002, 4.2e−29). In contrast, we observed significant associations between higher muscle fat infiltration and widespread thinner cortical thickness (76.5% of parcellations), lower white matter fractional anisotropy (62.5% of tracts) and predominantly lower brain volumes (35.5% of volumes), with |r| effect sizes in (0.02, 0.07) and P-values in (0.0002, 1.9e−31). The regions showing the most significant effect sizes across the cortex, white matter and volumes were of the sensorimotor system. Structural equation modelling analysis revealed that sensorimotor brain regions mediate the link between sarcopenic and cognitive traits [probable sarcopenia: P-values in (0.0001, 1.0e−11); muscle fat infiltration: P-values in (7.7e−05, 1.7e−12)]. Our findings show significant associations between sarcopenic traits, brain structure and cognitive performance in a middle-aged and older adult population. Mediation analyses suggest that regional brain structure mediates the association between sarcopenic and cognitive traits, with potential implications for dementia development and prevention.https://orcid.org/0000-0001-5832-0603https://scholar.google.com/citations?user=MrICwaMAAAAJ&hl=enhttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0001429659Revista Internacional - IndexadaS

Deviations from normative brain white and gray matter structure are associated with psychopathology in youth

Combining imaging modalities and metrics that are sensitive to various aspects of brain structure and maturation may help identify individuals that show deviations in relation to same-aged peers, and thus benefit early-risk-assessment for mental disorders. We used one timepoint multimodal brain imaging, cognitive, and questionnaire data from 1280 8-21-year-olds from the Philadelphia Neurodevelopmental Cohort. We estimated age-related gray and white matter properties and estimated individual deviation scores using normative modeling. Next, we looked for associations between the estimated deviation scores, and with psychopathology domain scores and cognition. More negative deviations in DTI-based fractional anisotropy (FA) and the first principal eigenvalue of the diffusion tensor (L1) were associated with higher scores on psychosis positive and prodromal symptoms and a general psychopathology factor. A more negative deviation in cortical thickness (CT) was associated with a higher general psychopathology score. Negative deviations in global FA, surface area, L1 and CT were also associated with poorer cognitive performance. No robust associations were found between the deviation scores based on CT and DTI. The low correlations between the different multimodal MRI based deviation scores support that brain maturation is highly heterogenous and suggest that psychopathological burden in adolescence may map onto partly distinct neurobiological features

Traces of impaired social communication and cognitive ability in the youth brain are shared across diagnostic boundaries

Background: Despite longstanding effort, psychopathology etiology remains elusive. Identification of shared and distinct traits across clinical groups may illuminate the structure of psychopathology. A multitude of factors is likely involved; however, most studies have investigated one or a few factors at a time. Methods: In a clinical youth sample (n=1732, 64% male, age range: 5-21 years), we used canonical correlation and independent component analysis to estimate modes of covariation between structural neuroimaging measures with clinical, cognitive, and psychosocial variables. Out-of-sample validations of brain patterns were conducted in an independent population-based sample (n=1253, 54% female, age range: 8-21 years). Brain patterns in the independent sample were then correlated with clinical, and cognitive variables to test their predictive ability. Results: We identified two significant modes of brain-behavior covariation: the first linked age, physical and cognitive maturation to lower cortical thickness and gyrification (r=.92, p=.005). The second mode linked lower academic performance, trouble with social communication and psychological difficulties, with lower white matter surface area and gyrification (r=.92, p=.006). Diagnosed youth showed elevated mode 2 scores compared to undiagnosed peers. Out-of-sample validation replicated the covariation pattern across brain features. Mode 1 correlated highly with age (r [95% CI]; .7 [.68-.71]) and age-related cognitive maturation (.36 [.33-.38]), while mode 2 correlated with deviations from normative cognitive development (-.24 [-.27--.21]). Conclusion: Our results link maturation and socio-cognitive difficulties to brain structure across diagnostic boundaries, suggesting disorder-general effects as the most prominent. This emphasises transdiagnostic approaches in the identification of traits relevant for psychopathology

Computational modeling of the N-Back task in the ABCD study: associations of drift diffusion model parameters to polygenic scores of mental disorders and cardiometabolic diseases

Background. Cognitive dysfunction is common in mental disorders and represents a potential risk factor in childhood. The nature and extent of associations between childhood cognitive function and polygenic risk for mental disorders is unclear. We applied computational modeling to gain insight into mechanistic processes underlying decision making and working memory in childhood and their associations with PRS for mental disorders and comorbid cardiometabolic diseases. Methods. We used the drift diffusion model to infer latent computational processes underlying decision-making and working memory during the N-back task in 3707 children aged 9-10 from the ABCD Study. SNP-based heritability was estimated for cognitive phenotypes, including computational parameters, aggregated N-back task performance and neurocognitive assessments. PRS was calculated for Alzheimer’s disease (AD), bipolar disorder, coronary artery disease (CAD), major depressive disorder, obsessive-compulsive disorder, schizophrenia and type 2 diabetes. Results. Heritability estimates of cognitive phenotypes ranged from 12 to 39%. Bayesian mixed models revealed that slower accumulation of evidence was associated with higher PRS for CAD and schizophrenia. Longer non-decision time was associated with higher PRS for AD and lower PRS for CAD. Narrower decision threshold was associated with higher PRS for CAD. Load-dependent effects on non-decision time and decision threshold were associated with PRS for AD and CAD, respectively. Aggregated neurocognitive test scores were not associated with PRS for any of the mental or cardiometabolic phenotypes. Conclusions. We identified distinct associations between computational cognitive processes to genetic risk for mental illness and cardiometabolic disease, which could represent childhood cognitive risk factors

Linking Sarcopenia, Brain Structure, and Cognitive Performance

Here we share the R-scrips for a project investigating the links between sarcopenia, brain structure, and cognitive performance. If you choose to use these scrips, please cite the corresponding manuscript, available in Brain Communications, at https://doi.org/10.1093/braincomms/fcae083