Biology subjects

Dale, A. M.

Publications and source records attributed to Dale, A. M..

At least 37 records · Page 2Linked to original sources

bioRxiv2020

Associations between Early Midlife Lifestyle Behaviors, Young Adult Cognitive Reserve and Advanced Predicted Brain Age in Late Midlife

ImportanceBoth cognitive reserve and modifiable lifestyle behaviors are associated with dementia risk. The effect of early lifestyle behaviors and cognitive reserve on late midlife brain aging could inform early identification and risk reduction of future dementia. ObjectiveDetermine associations of young adult cognitive reserve, early midlife lifestyle behaviors, and the reserve-by-lifestyle interaction on late midlife brain age. Examine the relationship between mild cognitive impairment (MCI) and brain age. DesignParticipants were from the nationally representative Vietnam Era Twin Study of Aging (VETSA). Cognitive reserve was assessed at median age 20 years (IQR=1.38) with the Armed Forces Qualification Test (AFQT). Lifestyle behaviors (smoking, alcohol consumption, and social engagement) were assessed at median age 41 (IQR=5.00). Structural brain imaging conducted at median age 69 (IQR=4.74) was used to construct predicted brain age difference scores (PBAD=chronological age minus predicted brain age) and MCI was ascertained. SettingIn-person cognitive testing (ages 20 and 69); mailed survey (age 41); structural MRI, MCI diagnosis at University of California, San Diego (age 69). Participants431 community-dwelling men. ExposuresAFQT; self-reported health and lifestyle behaviors. Main outcomes and measuresPBAD scores; MCI. ResultsIn fully adjusted mixed linear models, age 20 cognitive reserve and the age 41 lifestyle composite were associated with age 69 PBAD [t (104)=2.62, p=0.01, 95%CI 0.874, 6.285; t (104)=3.37, p=0.001, 95%CI 0.583, 2.249 respectively] as was the reserve-by-lifestyle interaction [t (104) = -2.29, p=0.02, 95%CI -2.330, -0.167]. Unfavorable lifestyle predicted more advanced brain age, but only for those with lower young adult cognitive reserve. The MCI group had more advanced brain age (F (2,130) = 3.13; p=0.05). Conclusions and relevanceFavorable lifestyle behaviors promoted resistance to accelerated brain aging 3 decades later for those with lower young adult cognitive reserve. High reserve appeared to be protective regardless of lifestyle. The association with MCI suggests that advanced PBAD scores reflect poorer brain integrity, although it is unclear if PBAD is related to Alzheimers dementia specifically. Lower cognitive reserve increases risk for dementia, but early lifestyle modification may promote healthier brain aging and dementia risk reduction, particularly in those with lower reserve. Study TypeCohort Study Key PointsO_ST_ABSQuestionC_ST_ABSDo modifiable lifestyle behaviors in early midlife predict later accelerated brain aging and is that association moderated by cognitive reserve? FindingsA lifestyle composite of smoking, alcohol consumption and social engagement at age 41 was associated with estimated brain age in late midlife. There was a significant moderation effect whereby more unfavorable lifestyle behaviors predicted more advanced brain aging, but only in those with low-to-moderate cognitive reserve. MeaningFavorable lifestyle behaviors appear to be protective for brain integrity especially among those with lower cognitive reserve. Early midlife efforts at prevention could be prioritized among those with lower cognitive reserve.

neuroscience↗

bioRxiv2020

Multivariate genome-wide association study identifies 1735 unique genetic loci associated with cortical morphology.

Brain morphology has been shown to be highly heritable, yet only a small portion of the heritability is explained by the genetic variants discovered so far. Here we exploit the distributed nature of genetic effects across the brain and apply the Multivariate Omnibus Statistical Test (MOSTest) to genome-wide association studies (GWAS) of vertex-wise structural magnetic resonance imaging (MRI) cortical measures from N=35,657 participants in the UK Biobank. We identified 695 loci for cortical surface area and 539 for cortical thickness, in total 780 unique genetic loci associated with cortical morphology. This reflects an approximate 10-fold increase compared to the commonly applied univariate GWAS methods. Power analysis indicates that applying MOSTest to vertex-wise structural MRI data triples the effective sample size compared to conventional univariate GWAS approaches. Functional follow up including gene-based analyses implicate 10% of all protein-coding genes and point towards pathways involved in neurogenesis and cell differentiation.

genetics↗

bioRxiv2020

Atypical genomic patterning of the cerebral cortex in autism with poor early language outcome

Cortical regional identities develop through anterior-posterior (A-P) and dorsal-ventral (D-V) prenatal genomic patterning gradients. Here we find that A-P and D-V genomic patterning of cortical surface area (SA) and thickness (CT) is intact in typically developing and autistic toddlers with good language outcome, but is absent in autistic toddlers with poor early language outcome. Genes driving this effect are prominent in midgestational A-P and D-V gene expression gradients and prenatal cell types driving SA and CT variation (e.g., progenitor cells versus excitatory neurons). These genes are also important for vocal learning, human-specific evolution, and prenatal co-expression networks enriched for high-penetrance autism risk genes. Autism with poor early language outcome may be linked to atypical genomic cortical patterning starting in prenatal periods and which impacts later development of regional functional specialization and circuit formation. One Sentence SummaryGenomic patterning of the cortex is atypical in autistic toddlers with poor early language outcome.

neuroscience↗

bioRxiv2020

Fluid and crystallised intelligence are associated with distinct regionalisation patterns of cortical morphology

Cognitive performance in children is predictive of academic and social outcomes; therefore, understanding neurobiological mechanisms underlying individual differences in cognition during development may be important for improving quality of life. The belief that a single, psychological construct underlies many cognitive processes is pervasive throughout society. However, it is unclear if there is a consistent neural substrate underlying many cognitive processes. Here we show that a distributed configuration of cortical surface area and apparent thickness, when controlling for global imaging measures, is differentially associated with cognitive performance on different types of tasks in a large sample (N=10,145) of 9-11 year old children from the Adolescent Brain and Cognitive DevelopmentSM (ABCD) study. The minimal overlap in these regionalization patterns of association has implications for competing theories about developing intellectual functions. Surprisingly, not controlling for sociodemographic factors increased the similarity between these regionalization patterns. This highlights the importance of understanding the shared variance between sociodemographic factors, cognition and brain structure, particularly with a population-based sample such as ABCD.

neuroscience↗

bioRxiv2019

Quantifying the polygenic architecture of the human cerebral cortex: Extensive genetic overlap between cortical thickness and surface area

IntroductionThe thickness of the cerebral cortical sheet and its surface area are highly heritable traits thought to have largely distinct polygenic architectures. Despite large-scale efforts, the majority of their genetic determinants remains unknown. Our ability to identify causal genetic variants can be improved by employing better delineated, less noisy brain measures that better map onto the biology we seek to understand. Such measures may have fewer variants but with larger effects, i.e. lower polygenicity and higher discoverability. MethodsUsing Gaussian mixture modeling, we estimated the number of causal variants shared between mean cortical thickness and total surface area. We further determined the polygenicity and discoverability of regional cortical measures from five often-employed parcellation schemes. We made use of UK Biobank data from 31,312 healthy White European individuals (mean age 55.5, standard deviation (SD) 7.4, 52.1% female). ResultsContrary to previous reports, we found large genetic overlap between total surface area and mean thickness, sharing 4427 out of 7150 causal variants. Regional surface area was more discoverable (p=4.1x10-6) and less polygenic (p=.007) than regional thickness measures. We further found that genetically-informed and less granular parcellation schemes had highest discoverability, with no differences in polygenicity. ConclusionsThese findings may serve as a roadmap for improved future GWAS studies; Knowledge of which measures or parcellations are most discoverable, as well as the genetic overlap between these measures, may be used to boost identification of genetic predictors and thereby gain a better understanding of brain morphology.

neuroscience↗

bioRxiv2019

Spatially Resolved Estimation of Metabolic Oxygen Consumption From Optical Measurements in Cortex

The cerebral metabolic rate of oxygen (CMRO2) is an important indicator of brain function and pathology. Knowledge about its magnitude is also required for proper interpretation of the blood oxygenation level dependent (BOLD) signal measured with functional MRI (fMRI). The ability to measure CMRO2 with high spatial and temporal accuracy is thus highly desired. Traditionally the estimation of CMRO2 has been pursued with somewhat indirect approaches combining several different types of measurements with mathematical modeling of the underlying physiological processes. Given the numerous assumptions involved, questions have thus been raised about the accuracy of the resulting CMRO2 estimates. The recent ability to measure the level of oxygen (pO2) in cortex with high spatial resolution in in vivo conditions has provided a more direct way for estimating CMRO2. CMRO2 and pO2 are related via the Poisson partial differential equation. Assuming a constant CMRO2 and cylindrical symmetry around the blood vessel providing the oxygen, the so-called Krogh-Erlang formula relating the spatial pO2 profile to a constant CMRO2 value can be derived. This Krogh-Erlang formula has previously been used to estimate the average CMRO2 close to cortical blood vessels based on pO2 measurements in rats.\n\nHere we introduce a new method, the Laplace method, to provide spatial maps of CMRO2 based on the same measured pO2 profiles. The method has two key steps: First the measured pO2 profiles are spatially smoothed to reduce effects of spatial noise in the measurements. Next, the Laplace operator (a double spatial derivative) in two spatial dimensions is applied on the smoothed pO2 profiles to obtain spatially resolved CMRO2 estimates. The smoothing introduces a bias, and a balance must be found where the effects of the noise are sufficiently reduced without introducing too much bias. In this model-based study we explore this balance in situations where the ground truth, that is, spatial profile of CMRO2 is preset and thus known, and the corresponding pO2 profiles are found by solving the Poisson equation, either numerically or by taking advantage of the Krogh-Erlang formula. MATLAB code for using the Laplace method is provided.

neuroscience↗

bioRxiv2019

Determining the association between cortical morphology and cognition in 10,145 children from the Adolescent Brain and Cognitive Development (ABCD) study using the MOSTest

Individuals undergo protracted changes in cortical morphology during childhood and adolescence, coinciding with cognitive development. Studies quantifying the association between brain structure and cognition do not always assess regional cortical morphology relative to global brain measures and typically rely on mass univariate statistics or ROI-based analyses. After controlling for global brain measures, it is possible to detect a residual regionalisation pattern indicating the size or thickness of different regions relative to the total cortical surface area or mean thickness. Individual variability in regionalisation may be important for understanding and predicting between subject variability in cognitive performance. Here we sought to determine whether the relative configuration of cortical architecture across the whole cortex was associated with cognition using a novel multivariate omnibus statistical test (MOSTest) in 10,145 children aged 9-10 years from the Adolescent Brain and Cognitive Development (ABCD) Study. MOSTest is better powered to detect associations that are widely distributed across the cortex compared to methods that assume sparse associations. We then quantified the magnitude of the association between vertex-wise cortical morphology and cognitive performance using a linear weighted sum across vertices, based on the estimated vertex-wise effect sizes. We show that the relative pattern of cortical architecture, after removing the effects of global brain measures, predicted unique variance associated with cognition across different imaging modalities and cognitive domains. SIGNIFICANCE STATEMENTThis paper demonstrates a significant advance in our understanding of the relationship between cortical morphology and individual variability in cognition. There is increasing evidence that brain-behaviour associations are distributed across the cortex. Using the unprecedented sample from the Adolescent Brain and Cognitive Development (ABCD) study and a novel application of a multivariate statistical approach (MOSTest), we have discovered specific distributed regionalization patterns across the cortex associated with cognition across multiple cognitive domains. This furthers our understanding of the relationship between brain structure and cognition, namely that these associations are not sparse and localized as assumed with traditional neuroimaging analyses. This multivariate method is extremely versatile and can be used in several different applications.

neuroscience↗

bioRxiv2019

The polyvertex score (PVS): a whole-brain phenotypic prediction framework for neuroimaging studies

The traditional brain mapping approach has greatly advanced our understanding of the localized effect of the brain on behavior. However, the statistically significant brain regions identified by standard mass univariate models only explain minimal variance in behavior despite increased sample sizes and statistical power. This is potentially due to the generalizable explanatory signal in the brain being non-sparse, therefore not captured by the thresholded, localized model. Here we introduced the Bayesian polyvertex score (PVS-B), a whole-brain prediction framework that aggregates the effect sizes across all vertices to predict individual variability in behavior. The PVS-B estimates the posterior mean effect size at each vertex with mass univariate summary statistics and the correlation structure of the imaging phenotype, and weights the imaging phenotype of participants from an independent sample with these posterior mean effect sizes to estimate the generalizable effect of a brain-behavior association. Empirical data showed that the PVS-B was able to double the variance explained in general cognitive ability by an n-back fMRI contrast when compared to prediction models based on the mass univariate parameter estimates as well as models in which only vertices thresholded based on p-value were included. A fivefold improvement in variance explained by the PVS-B was observed using a stop signal task fMRI contrast to predict individual variability in the stop signal reaction time. We believe that the PVS-B can shed light on the multivariate investigation of brain-behavioral associations and will empower small scale neuroimaging studies with more reliable and accurate effect size estimates.

neuroscience↗

bioRxiv2019

Annotation-Informed Causal Mixture Modeling (AI-MiXeR) reveals phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories

Determining the contribution of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here we present Annotation Informed MiXeR: a likelihood-based method to estimate the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Applying the model to 11 complex phenotypes suggests diverse patterns of functional category-specific genetic architectures across human diseases and traits.

genetics↗

bioRxiv2019

Movement abilities and brain development in preschoolers born very preterm

AimTo examine how healthy preschoolers born very preterm (VPT) with and without significant movement impairments differ from full term (FT) controls in subcortical brain volume measures and white matter diffusion properties.\n\nMethodA case-control, observational study of fifty-four VPT-born and 32 FT-born children were administered the Movement Assessment Battery for Children - Second Edition (MABC-2) and underwent MRI within 6-months of starting kindergarten. Selected subcortical structural volumes, fractional anisotropy (FA), and mean diffusivity (MD) of selected white matter tracts were compared across VPT children with movement impairments (VPT-abnormal), and VPT and FT children without movement impairments.\n\nResultsThe VPT-abnormal group had higher MD in the corpus callosum and inferior frontal-occipital fasciculus and lower FA in the anterior thalamic radiations, corpus callosum, and cingulum than the FT group. The forceps major was particularly affected in the VPT-abnormal group compared with the VPT and FT groups without movement impairments. Both VPT groups had reduced brainstem and cerebellar white matter volumes and larger lateral ventricles compared to the FT group.\n\nInterpretationMovement impairments in healthy VPT preschoolers were associated with more abnormalities in white matter integrity and reduced subcortical brain volumes most likely reflecting a greater extent of white matter damage associated with their very preterm birth.

neuroscience↗

bioRxiv2019

Age dependence of modern clinical risk groups for localized prostate cancer -- a population-based study

BackgroundOptimal prostate cancer (PCa) screening strategies will focus on men most likely to have potentially-lethal, localized disease. Age-specific incidence rates (ASIRs) for clinical risk groups could guide risk-stratified screening.\n\nObjectiveDetermine ASIRs and proportions of PCa diagnoses in Norway for modern risk-group and Gleason score categories.\n\nDesign, Setting, and ParticipantsAll men diagnosed with PCa in Norway in 2014-2017 (n=20,356).\n\nOutcome Measurements and Statistical AnalysisPatients were assigned to clinical risk groups: low, favorable-intermediate, unfavorable-intermediate, high, regional, and metastatic, using Gleason score and clinical stage. Associations were assessed between age and (1) Gleason score (including Gleason 3+4 and 4+3) and (2) PCa risk group. Risk-group ASIRs were calculated by multiplying the overall Norwegian ASIR by the proportions observed for each category.\n\nResultsOlder age was significantly associated with higher Gleason score and more advanced disease. For example, among men aged 55-59, 65-69, 75-79, and 85-89 years, the percentage with Gleason 8-10 disease was 16.5%, 23.4%, 37.2%, and 59.9%, respectively (p<0.001); the percentage with at least high-risk disease was 29.3%, 39.1%, 60.4%, and 90.6%, respectively. Corresponding percentages for low-risk PCa were 24.0%, 17.9%, 10.2%, and 4.1% (p<0.001). The respective maximum ASIRs (per 100,000 men) for low-risk, favorable-intermediate-risk, unfavorable-intermediate-risk, high-risk, regional, and metastatic disease were: 157.1, 183.8, 194.8, 408.3, 172.3, and 330.0; incidence for low-risk and favorable-intermediate-risk PCa peaked before age 70, while more advanced categories peaked after 70. At age 75-79 years, the ASIR of high-risk disease was approximately 6 times greater than at 55-59 years.\n\nConclusionsRisk of clinically-significant, localized PCa increases with age. Healthy older men may be among those most likely to benefit from PCa screening.

epidemiology↗

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↗

bioRxiv2019

Sex-dependent polygenic effects on the clinical progressions of Alzheimer’s disease

Sex differences in the manifestations of Alzheimers disease (AD) are under intense investigations 1,2. Despite the emerging importance of polygenic predictions for AD 3-8, the sex-dependent polygenic effects have not been demonstrated. Here, using a sex crossover analysis, we show that sex-dependent autosomal genetic effects on AD can be revealed by characterizing disease progress via the hazard function. We first performed sex-stratified genome-wide associations, and then applied derived sex-dependent weights to two independent cohorts. Sex-matched polygenic hazard scores (PHS) have significantly stronger associations with age-at-disease-onset, clinical progressions, amyloid depositions, neurofibrillary tangles, and composite neuropathological scores, than sex-mismatched PHS, independent of apolipoprotein E. Models without using hazard weights, i.e. polygenic risk scores (PRS), have lower predictive power than PHS and show no evidence for sex differences. Our results indicate revealing sex-dependent genetic architecture requires the consideration of temporal processes of AD. This has strong implications not only for the genetic underpinning of AD but also for how we estimate sex-dependent polygenic effects for clinical use.

genetics↗

bioRxiv2018

Partitioning the genetic architecture of amyotrophic lateral sclerosis

The genetic basis of sporadic amyotrophic lateral sclerosis (ALS) is not well understood. Using large genome-wide association studies and validated tools to quantify genetic overlap, we systematically identified single nucleotide polymorphisms (SNPs) associated with ALS conditional on genetic data from 65 different traits and diseases from >3 million people. We found strong genetic enrichment between ALS and a number of disparate traits including frontotemporal dementia, coronary artery disease, C-reactive protein, celiac disease and memory function. Beyond C9ORF72, we detected novel genetic signal within numerous loci including GIPC1, ELMO1 and COL16A and confirmed previously reported variants, such as ATXN2, KIF5A, UNC13A and MOBP. We found that ALS variants form a small-world co-expression network characterized by highly inter-connected hub genes. This network clustered into smaller sub-networks, each associated with a unique function. Altered gene expression of several sub-networks and hubs was over-represented in neuropathological samples from ALS patients and SOD1 G93A mice. Our collective findings indicate that the genetic architecture of ALS can be partitioned into distinct components where some genes are highly important for developing disease. These findings have implications for stratification and enrichment strategies for ALS clinical trials.

genetics↗

bioRxiv2018

Beyond SNP Heritability: Polygenicity and Discoverability of Phenotypes Estimated with a Univariate Gaussian Mixture Model

Of signal interest in the genetics of human traits is estimating their polygenicity (the proportion of causally associated single nucleotide polymorphisms (SNPs)) and the discoverability (or effect size variance) of the causal SNPs. Narrow-sense heritability is proportional to the product of these quantities. We present a basic model, using detailed linkage disequilibrium structure from an extensive reference panel, to estimate these quantities from genome-wide association studies (GWAS) summary statistics for SNPs with minor allele frequency >1%. We apply the model to diverse phenotypes and validate the implementation with simulations. We find model polygenicities ranging from [~=] 2 x 10-5 to [~=] 4 x 10-3, with discoverabilities similarly ranging over two orders of magnitude. A power analysis allows us to estimate the proportions of phenotypic variance explained additively by causal SNPs at current sample sizes, and map out sample sizes required to explain larger portions of additive SNP heritability. The model also allows for estimating residual inflation.

genetics↗

bioRxiv2018

Genetic risk for coronary heart disease alters the influence of Alzheimer’s genetic risk on mild cognitive impairment

BACKGROUNDAlzheimers disease (AD) is under considerable genetic influence. However, known susceptibility loci only explain a modest proportion of variance in disease outcomes. This small proportion could occur if the etiology of AD is heterogeneous. We previously found that an AD polygenic risk score (PRS) was significantly associated with mild cognitive impairment (MCI), an early stage of AD. Poor cardiovascular health is also associated with increased risk for AD and has been found to interact with AD pathology. Conditions such as coronary artery disease (CAD) are also heritable, and may contribute to heterogeneity if there are interactions of genetic risk for these conditions as there is phenotypically. However, case-control designs based on prevalent cases of a disease with relatively high case-fatality rate such as CAD may be biased toward individuals who have long post-event survival times and may therefore also identify loci with protective effects.\n\nMETHODSWe compared interactions between an AD-PRS and two CAD-PRSs, one based on a GWAS of incident cases and one on prevalent cases, on MCI status in 1,209 individuals.\n\nRESULTSAs expected, the incidence-based CAD-PRS interacts with the AD-PRS to further increase MCI risk. Conversely, higher prevalence-based CAD-PRSs reduced the effect of AD genetic risk on MCI status.\n\nCONCLUSIONSThese results demonstrate: i) the utility of including multiple PRSs and their interaction effects; ii) how genetic risk for one disease may modify the impact of genetic risk for another; and iii) the importance of considering ascertainment procedures of GWAS being used for genetic risk prediction.

genomics↗

bioRxiv2018

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet we know little about the specific genetic loci influencing human cortical structure. To identify genetic variants, including structural variants, impacting cortical structure, we conducted a genome-wide association meta-analysis of brain MRI data from 51,662 individuals. We analysed the surface area and average thickness of the whole cortex and 34 regions with known functional specialisations. We identified 255 nominally significant loci (P [≤] 5 x 10-8); 199 survived multiple testing correction (P [≤] 8.3 x 10-10; 187 surface area; 12 thickness). We found significant enrichment for loci influencing total surface area within regulatory elements active during prenatal cortical development, supporting the radial unit hypothesis. Loci impacting regional surface area cluster near genes in Wnt signalling pathways, known to influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinsons disease, insomnia, depression and ADHD.\n\nOne Sentence SummaryCommon genetic variation is associated with inter-individual variation in the structure of the human cortex, both globally and within specific regions, and is shared with genetic risk factors for some neuropsychiatric disorders.

genetics↗

bioRxiv2018

Continuity and discontinuity in human cortical development and change from embryonic stages to old age

The human cerebral cortex is highly regionalized. We aimed to test whether principles of regionalization could be traced from embryonic development throughout the human lifespan. A data-driven fuzzy-clustering approach was used to identify regions of coordinated longitudinal development of cortical surface area (SA) and thickness (CT) over 1.5 years (n = 301, 4-12 years). First, the SA clusters were compared to patterns from embryonic cortical development. The earliest sign of cortical regionalization is the emergence of morphometric gradients in the cerebral vesicles, with a major gradient running along the anterior-posterior (AP) axis. We found that the principal divide for the developmental SA clusters extended from the inferior-posterior to the superior-anterior cortex, corresponding to the embryonic morphometric AP gradient. Second, embryonic factors showing a clear AP gradient were identified, and tests revealed significant differences in gene expression of these factors between the anterior and posterior clusters. Further, each identified developmental SA and CT cluster showed distinguishable lifespan trajectories in a larger longitudinal dataset (4-88 years, 1633 observations). This means that regions that developed together also changed together throughout life, demonstrating continuity in regionalization of cortical changes. The AP divide in SA development also characterized genetic patterning obtained in an adult twin sample, but otherwise regionalized CT development adhered more to the genetic boundaries. Finally, SA and CT clusters showed differential relationships to cognitive functions. In sum, the results suggest that development of cortical regionalization is a continuous process from the embryonic stage throughout human life.\n\nSignificance statement (120 words)The protomap and the radial unit theories of brain development have shown that graded expression patterns of several factors are responsible for shaping the ultimately highly partitioned and specialized neocortical landscape. The present study shows that the major anterior-posterior gradient of embryonic development can be detected in the regional cortical expansion profiles of children. The study further demonstrates that brain regions that develop together during childhood also tend to change together throughout the lifespan. This suggests that regional cortical development is a continuous process through the entire life, and that early-life factors have life-long impacts on this process.

neuroscience↗