Biology subjects

Madole, J. W.

Publications and source records attributed to Madole, J. W..

7 recordsLinked to original sources

bioRxiv2021

General dimensions of human brain morphometry inferred from genome-wide association data

BackgroundUnderstanding the neurodegenerative mechanisms underlying cognitive declines in the general population may facilitate early detection of adverse health outcomes in late life. This study investigates biological pathways shared between brain morphometry, ageing, and cognitive ability. MethodsWe develop Genomic Principal Components Analysis (genomic PCA) to model general dimensions of variance in brain morphometry within brain networks at the level of their underlying genetic architecture. With genomic PCA we extract genetic principal components (PCs) that index global dimensions of genetic variance across phenotypes (unlike ancestral PCs that index genetic similarity between participants). Genomic PCA is applied to genome-wide association data for 83 brain regions which we calculated in 36,778 participants of the UK Biobank cohort. Using linkage disequilibrium score regression, we estimate genetic overlap between brain networks and indices of cognitive ability and brain ageing. ResultsA genomic principal component (PC) representing brain-wide dimensions of shared genetic architecture accounted for 40% of the genetic variance across 83 individual brain regions. Genomic PCs corresponding to canonical brain networks accounted for 47-65% of the genetic variance in the corresponding brain regions. These genomic PCs were negatively associated with brain age (rg = -0.34). Loadings of individual brain regions on the whole-brain genomic PC corresponded to sensitivity of a corresponding region to age (r = - 0.27). We identified positive genetic associations between genomic PCs of brain morphometry and general cognitive ability (rg= 0.17-0.21). ConclusionThese results demonstrate substantial shared genetic etiology between connectome-wide dimensions of brain morphometry, ageing, and cognitive ability, which will help guide investigations into risk factors and potential interventions of ageing-related cognitive decline.

genetics↗

bioRxiv2020

Multivariate genomic analysis of 1.5 million people identifies genes related to addiction, antisocial behavior, and health

Behaviors and disorders related to self-regulation, such as substance use, antisocial conduct, and ADHD, are collectively referred to as externalizing and have a shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The identified loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results captures variation in a broad range of behavioral and medical outcomes that were not part of our genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions, and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental condition.

genetics↗

bioRxiv2020

Three major dimensions of human brain cortical ageing in relation to cognitive decline across the 8th decade of life.

Different brain regions can be grouped together, based on cross-sectional correlations among their cortical characteristics; this patterning has been used to make inferences about ageing processes. However, cross-sectional brain data conflates information on ageing with patterns that are present throughout life. We characterised brain cortical ageing across the 8th decade of life in a longitudinal ageing cohort, at ages ~73, ~76, and ~79 years, with a total of 1,376 MRI scans. Volumetric changes among cortical regions of interest (ROIs) were more strongly correlated (average r = 0.805, SD = 0.252) than were cross-sectional volumes of the same ROIs (average r = 0.350, SD = 0.178). We identified a broad, cortex-wide, dimension of atrophy that explained 66% of the variance in longitudinal changes across the cortex. Our modelling also discovered more specific fronto-temporal and occipito-parietal dimensions, that were orthogonal to the general factor and together explained an additional 20% of the variance. The general factor was associated with declines in general cognitive ability (r = 0.431, p < 0.001) and in the domains of visuospatial ability (r = 0.415, p = 0.002), processing speed (r = 0.383, p < 0.001) and memory (r = 0.372, p < 0.001). Individual differences in brain cortical atrophy with ageing are manifest across three broad dimensions of the cerebral cortex, the most general of which is linked with cognitive declines across domains. Longitudinal approaches are invaluable for distinguishing lifelong patterns of brain-behaviour associations from patterns that are specific to aging.

neuroscience↗

bioRxiv2019

Enhanced prediction of cognitive function using aging-sensitive networks within the human structural connectome

Using raw structural and diffusion brain MRI data from the UK Biobank (UKB; N = 3,155, ages 45-75 years) and the Lothian Birth Cohort 1936 (LBC1936; N = 534, all age 73 years), we examine aging of regional grey matter volumes (nodes) and white matter structural connectivity (edges) within networks-of-interest in the human brain connectome. In UKB, the magnitude of age-differences in individual node volumes and edge weights corresponds closely with their loadings on their respective principal components of connectome-wide integrity (|rnodes| = 0.459; |redges| = 0.595). In LBC1936, connectome-wide and subnetwork-specific composite indices of node integrity were predictive of processing speed, visuospatial ability, and memory, whereas composite indices of edge integrity were associated specifically with processing speed. Childhood IQ was associated with greater node integrity at age 73. However, node and edge integrity remained associated with age 73 cognitive function after controlling for childhood IQ. Adult connectome integrity is therefore both a marker of early-life cognitive function and a substrate of late-life cognitive aging.

neuroscience↗

bioRxiv2019

Changing environments reveal innovative genetic variation in children's cortisol responses

Genetic associations with biopsychosocial phenotypes are often interpreted as evidence that the genome codes for fixed end-states. Instead, a given genotype might regulate a dynamic range of phenotypes in response to environmental change. We collected hair cortisol (n = 1,104), salivary cortisol in reaction to an in-laboratory stressor (n = 537), and diurnal salivary cortisol (n = 488) from twins aged 8-15 years in the Texas Twin Project. Baseline genetic variation in both salivary and hair cortisol was not simply magnified after stressor exposure or after waking. Rather, novel genetic influences on cortisol arose over time. Thus, environmental change can reveal genetic variation that would not otherwise be observed in static cortisol levels. These findings are in line with the notion that the genome regulates individuals reactions to the environment that differ across environments.

genetics↗

bioRxiv2019

Psychotic-like experiences, polygenic risk scores for schizophrenia and structural properties of the salience, default mode and central-executive networks in healthy participants from UK Biobank

Schizophrenia is a highly heritable disorder with considerable phenotypic heterogeneity. Hallmark psychotic symptoms can be considered as existing on a continuum from non-clinical to clinical populations. Assessing genetic risk and psychotic-like experiences (PLEs) in non-clinical populations and their associated neurobiological underpinnings can offer valuable insights into symptom-associated brain mechanisms without the potential confounds of the effects of schizophrenia and its treatment. We leveraged a large population-based cohort (UKBiobank) including information on PLEs, polygenic risk scores for schizophrenia (PRSSZ) and multi-modal brain imaging in combination with network neuroscience. Morphometric (cortical thickness, volume) and water diffusion (fractional anisotropy) properties of the regions and pathways belonging to the salience, default-mode and central-executive networks were computed. We hypothesized that these anatomical concomitants of functional dysconnectivity would be negatively associated with PRSSZ and PLEs. PRSSZ was significantly associated with a latent measure of cortical thickness across the salience network (r = -0.069, p = 0.010) and PLEs showed a number of significant associations with properties of the salience and default mode networks (involving the insular cortex, supramarginal gyrus and pars orbitalis, pFDR < 0.050); with the cortical thickness of the insula largely mediating the relationship between PRSSZ and auditory hallucinations. These results are consistent with the hypothesis that higher genetic liability for schizophrenia is related to subtle disruptions in brain structure and predisposes to PLEs even among healthy participants. In addition, our study suggests that networks engaged during auditory hallucinations show structural associations with PLEs in the general population.

neuroscience↗

bioRxiv2019

Weak and uneven associations of home, neighborhood and school environments with stress hormone output across multiple time scales.

The progression of lifelong trajectories of socioeconomic inequalities in health and mortality begins in childhood. Dysregulation in cortisol, a stress hormone that is the primary output of the hypothalamus-pituitary-adrenal (HPA) axis, has been hypothesized to be a mechanism for how early environmental adversity compromises health. However, despite the popularity of cortisol as a biomarker for stress and adversity, little is known about whether cortisol output differs in children being raised in socioeconomically disadvantaged environments. Here, we show that there are few differences between advantaged and disadvantaged children in their cortisol output. In 8- to 14-year-old children from the population-based Texas Twin Project, we measured cortisol output at three different time-scales: (1) diurnal fluctuation in salivary cortisol (n = 400), (2) salivary cortisol reactivity and recovery after exposure to the Trier Social Stress Test (n = 444), and (3) and cortisol concentration in hair (n = 1,210). These measures converged on two moderately correlated, yet distinguishable, dimensions of HPA function. We then tested differences in cortisol output across nine aspects of social disadvantage at the home (e.g., family socioeconomic status), school (e.g., average levels of academic achievement), and neighborhood (e.g., concentrated poverty). Children living in neighborhoods with higher concentrated poverty had higher diurnal cortisol output, as measured in saliva; otherwise, child cortisol output was unrelated to any other aspect of social disadvantage. Overall, we find limited support for alteration in HPA axis functioning as a general mechanism for the health consequences of socioeconomic inequality in childhood.

physiology↗