Biology subjects

Loughnan, R.

Publications and source records attributed to Loughnan, R..

4 recordsLinked to original sources

bioRxiv2026

Nonlinear associations between body mass index and brain microstructure across adolescence in the ABCD Study

Importance: Adolescent body mass index (BMI) is linked to brain microstructural alterations, but it is not known if this association is uniform across the BMI range. Objective: To characterize the shape of the association between adolescent BMI and brain microstructure across the BMI range. Design: Baseline, and 2-, 4-, and 6-year follow-up brain imaging and BMI from the Adolescent Brain Cognitive DevelopmentSM Study, analyzed between June 2025 and June 2026. Setting: Multicenter, population-based study including 21 sites distributed across the US. Participants: 10,479 adolescents (5,078 [48.5%] female; aged 9-18 years) from this population-based cohort study were included after quality control of complete data. Exposures: Centers for Disease Control BMI extended percentiles and percent from median BMI. Main Outcome and Measure: The primary outcome was the restricted normalized isotropic (RNI) signal fraction derived from diffusion imaging which indexes water confined within spherical cellular structures and is sensitive to microstructural properties including cellularity. Results: A total of 10,479 participants (5,078 [48.5%] female; aged 9-18 years) contributed 22,049 imaging observations across four timepoints. Higher BMI percentile was associated with greater RNI in bilateral reward- and appetite-related subcortical gray matter and white matter tracts, with effects varying spatially within structures, and with generally greater magnitude in males. Across these structures, the association increased steeply above the 80th percentile. This acceleration reflected compression of the percentile scale at high BMI; when BMI was reparameterized as percent from median, the association with RNI was approximately linear. Conclusions and Relevance: Our results suggest that BMI is associated with brain microstructure in a graded manner within white matter tracts and subcortical gray matter related to reward, executive function, and appetitive control. This indicates that the effect of BMI on microstructure is not confined to weight extremes and should be accounted for when modeling brain-body-behavior relationships during adolescence.

neuroscience↗

bioRxiv2022

The Impact of Population Stratification on the Analysis of Multimodal Neuroimaging Derived Measures

Magnetic resonance imaging (MRI) studies of the human brain are now attaining larger sample sizes with more diverse samples. However, population stratification, a key factor driving heterogeneity and confounding of associations, is seldom accounted for in neuroimaging analyses. To investigate this issue, we assessed the impact of population stratification on multimodal imaging measures using baseline data from the Adolescent Brain Cognitive Development (ABCD) StudySM (n = 10,748). Given this sociodemographically diverse sample, which broadly reflects the population composition of the United States, we performed a thorough evaluation of the impact of population stratification on derived neuroimaging metrics across five different imaging modalities: task functional MRI (task fMRI), resting state functional MRI (rsMRI), diffusion tensor images (DTI), restricted spectrum images (RSI), and structural T1 MRI (sMRI). We used parental income level as an example to highlight the impact of population stratification in confounding brain-wide associations. We show that derived metrics from structural images have up to three times more signal related to population stratification than do functional images. Controlling for population stratification in statistical models leads to a substantial reduction in the association strength between variables of interests and imaging measures, indicating the scale of potential bias. Moreover, because of unequal access to resources (such as income) across ancestral groups in United States, population stratification effects on imaging features may bias associations between parental income levels and imaging features, as we demonstrate. Our results provide a guide for researchers to critically examine the impact of population stratification and to assist in avoiding spurious brain-behavior associations. HighlightsO_LIHere, we conduct a comprehensive survey of the confounding impact of population stratification in large-scale imaging studies. C_LIO_LIMorphological features from structural imaging appear to be more susceptible to the confounding effects of population stratification than do functional imaging features. C_LIO_LIThe population stratification tends to inflates the association strengths between the variable of interest and imaging features. C_LIO_LIWhen the variable of interest is highly colinear with the population stratification, such as income levels, brain associations cannot be differentiated and may be misattributed as mediating effects. C_LIO_LIIt is critical to account for population stratification in imaging analyses. C_LI

neuroscience↗

bioRxiv2021

Multivariate genome-wide association studies on the tissue compartments of human brain identify novel loci underpinning brain development and neuropsychiatric outcomes.

The molecular determinants of tissue composition of the human brain remain largely unknown. Recent genome-wide association studies (GWAS) on this topic have had limited success due to methodological constraints. Here, we apply advanced whole-brain analyses on multi-shell diffusion imaging data and multivariate GWAS to two large scale imaging genetic datasets (UK Biobank and the Adolescent Brain Cognitive Development study) to identify and validate genetic association signals. We discovered 503 unique genetic loci that have impact on multiple regions of human brain. Among them, more than 79% were validated in either of two large-scale independent imaging datasets. Key molecular pathways involved in axonal growth, astrocyte-mediated neuroinflammation, and synaptogenesis during development were found to significantly impact the measured variations in tissue-specific imaging features. Our results shed new light on the biological determinants of brain tissue composition and their potential overlap with the genetic basis of neuropsychiatric disorders.

genetics↗

bioRxiv2019

Polygenic Score of Intelligence is More Predictive of Crystallized than Fluid Performance Among Children

BackgroundFindings in adults have shown more culturally sensitive crystallized measures of intelligence have greater heritability, these results were not able to be shown in children. MethodsWith data from 8,518 participants, aged 9 to 11, from the Adolescent Brain Cognitive Development (ABCD) Study(R), we used polygenic predictors of intelligence test performance (based on genome-wide association meta-analyses of data from 269,867 individuals) and of educational attainment (based on data from 1.1 million individuals), associating these predictors with neurocognitive performance. We then assessed the extent of mediation of these associations by a measure of recreational reading. Resultsmore culturally sensitive crystallized measures were more strongly associated with the polygenic predictors than were less culturally sensitive fluid measures. This mirrored heritability differences reported previously in adults and suggests similar associations in children. Recreational reading more strongly statistically mediated the genetic associations with crystallized than those with fluid measures of cognition. ConclusionThis is consistent with a prominent role of gene-environment correlation in cognitive development measured by "crystallized" intelligence tests. Such experiential mediators may represent malleable targets for improving cognitive outcomes.

neuroscience↗