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- Kanai, M, et al.
(author)
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- 2023
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swepub:Mat__t
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- Ge, R, et al.
(author)
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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization
- 2023
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In: bioRxiv : the preprint server for biology. - : Cold Spring Harbor Laboratory.
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Journal article (other academic/artistic)abstract
- Background: Normative modeling is a statistical approach to quantify the degree to which a particular individual-level measure deviates from the pattern observed in a normative reference population. When applied to human brain morphometric measures it has the potential to inform about the significance of normative deviations for health and disease. Normative models can be implemented using a variety of algorithms that have not been systematically appraised. Methods: To address this gap, eight algorithms were compared in terms of performance and computational efficiency using brain regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) collated from 87 international MRI datasets. Performance was assessed with the mean absolute error (MAE) and computational efficiency was inferred from central processing unit (CPU) time. The algorithms evaluated were Ordinary Least Squares Regression (OLSR), Bayesian Linear Regression (BLR), Generalized Additive Models for Location, Scale, and Shape (GAMLSS), Parametric Lambda, Mu, Sigma (LMS), Gaussian Process Regression (GPR), Warped Bayesian Linear Regression (WBLG), Hierarchical Bayesian Regression (HBR), and Multivariable Fractional Polynomial Regression (MFPR). Model optimization involved testing nine covariate combinations pertaining to acquisition features, parcellation software versions, and global neuroimaging measures (i.e., total intracranial volume, mean cortical thickness, and mean cortical surface area). Findings: Statistical comparisons across models at PFDR<0.05 indicated that the MFPR-derived sex- and region-specific models with nonlinear polynomials for age and linear effects of global measures had superior predictive accuracy; the range of the MAE of the models of regional subcortical volumes was 70-520 mm3 and the corresponding ranges for regional cortical thickness and regional cortical surface area were 0.09-0.26 mm and 24-560 mm2, respectively. The MFPR-derived models were also computationally more efficient with a CPU time below one second compared to a range of 2 seconds to 60 minutes for the other algorithms. The performance of all sex- and region-specific MFPR models plateaued at sample sizes exceeding 3,000 and showed comparable MAEs across distinct 10-year age-bins covering the human lifespan. Interpretation: These results provide an empirically benchmarked framework for normative modeling of brain morphometry that is useful for interpreting prior literature and supporting future study designs. The model and tools described here are freely available through CentileBrain (https://centilebrain.org/), a user-friendly web platform.
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- Morison, LD, et al.
(author)
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In-depth characterisation of a cohort of individuals with missense and loss-of-function variants disrupting FOXP2
- 2023
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In: Journal of medical genetics. - : BMJ. - 1468-6244 .- 0022-2593. ; 60:6, s. 597-607
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Journal article (peer-reviewed)abstract
- Heterozygous disruptions ofFOXP2were the first identified molecular cause for severe speech disorder: childhood apraxia of speech (CAS), and yet few cases have been reported, limiting knowledge of the condition.MethodsHere we phenotyped 28 individuals from 17 families with pathogenicFOXP2-only variants (12 loss-of-function, five missense variants; 14 males; aged 2 to 62 years). Health and development (cognitive, motor, social domains) were examined, including speech and language outcomes with the first cross-linguistic analysis of English and German.ResultsSpeech disorders were prevalent (23/25, 92%) and CAS was most common (22/25, 88%), with similar speech presentations across English and German. Speech was still impaired in adulthood, and some speech sounds (eg, ‘th’, ‘r’, ‘ch’, ‘j’) were never acquired. Language impairments (21/25, 84%) ranged from mild to severe. Comorbidities included feeding difficulties in infancy (10/26, 38%), fine (13/26, 50%) and gross (13/26, 50%) motor impairment, anxiety (5/27, 19%), depression (6/27, 22%) and sleep disturbance (10/24, 42%). Physical features were common (22/27, 81%) but with no consistent pattern. Cognition ranged from average to mildly impaired and was incongruent with language ability; for example, seven participants with severe language disorder had average non-verbal cognition.ConclusionsAlthough we identify an increased prevalence of conditions like anxiety, depression and sleep disturbance, we confirm that the consequences ofFOXP2dysfunction remain relatively specific to speech disorder, as compared with other recently identified monogenic conditions associated with CAS. Thus, our findings reinforce thatFOXP2provides a valuable entry point for examining the neurobiological bases of speech disorder.
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