Lifestyle Factors Counteract the Neurodevelopmental Impact of Genetic Risk for Accelerated Brain Aging in Adolescence

BACKGROUND: The transition from childhood to adolescence is characterized by enhanced neural plasticity and a consequent susceptibility to both bene ﬁ cial and adverse aspects of one ’ s milieu. METHODS: To understand the implications of the interplay between protective and risk-enhancing factors, we analyzed longitudinal data from the Adolescent Brain Cognitive Development (ABCD) Study ( n = 834; 394 female). We probed the maturational correlates of positive lifestyle variables (friendships, parental warmth, school engagement, physical exercise, healthy nutrition) and genetic vulnerability to neuropsychiatric disorders (major depressive disorder, Alzheimer ’ s disease, anxiety disorders, bipolar disorder, schizophrenia) and sought to further elucidate their implications for psychological well-being. RESULTS: Genetic risk factors and lifestyle buffers showed divergent relationships with later attentional and inter-personal problems. These effects were mediated by distinguishable functional neurodevelopmental deviations spanning the limbic, default mode, visual, and control systems. More speci ﬁ cally, greater genetic vulnerability was associated with alterations in the normative maturation of areas rich in dopamine (D 2 ), glutamate, and serotonin receptors and of areas with stronger expression of astrocytic and microglial genes, a molecular signature implicated in the brain disorders discussed here. Greater availability of lifestyle buffers predicted deviations in the normative functional development of higher density GABAergic (gamma-aminobutyric acidergic) receptor regions. The two pro ﬁ les of neurodevelopmental alterations showed complementary roles in protection against psychopathology, which varied with environmental stress levels. CONCLUSIONS: Our results underscore the importance of educational involvement and healthy nutrition in attenuating the neurodevelopmental sequelae of genetic risk factors. They also underscore the importance of characterizing early-life biomarkers associated with adult-onset pathologies.

The transition from childhood to adolescence is typified by a cascade of neurobiological and social environmental changes that accentuate sensitivity to both beneficial and adverse aspects of one's external milieu (1,2).A better understanding of the factors underpinning positive adjustment to stressors during this period is critical to designing interventions that foster optimal developmental trajectories (3).
Deviations from normative patterns of brain architecture, reflecting accelerated, decelerated, or merely atypical maturational trajectories, constitute a potential mechanism through which adversity and genetic risk for neuropsychiatric disorders hinder optimal psychological functioning (4-10).However, evidence is accruing that from very early in life, lifestyle factors, such as social relationships, healthy eating, and physical activity habits, can buffer against the effects of negative heritable or environmental factors (11)(12)(13)(14)(15).For example, positive parenting can dampen the impact of external stressors and genetic vulnerability to psychopathology, thereby promoting superior cognitive functioning in childhood and adolescence (16,17).Likewise, high-quality friendship during the teenage years alleviates the influence of prior social-affective deprivation and fosters interpersonal responsiveness (18).
With regard to nutrition, findings from studies with rodents suggest that gut microbiota distinguish adversity-resilient from adversity-vulnerable phenotypes (19).This effect is likely mediated by altered hypothalamic-pituitary-adrenal axis responses to stress, which have been linked to neurogenesis and myelination of limbic and prefrontal areas (13,(20)(21)(22).In humans, nutrition is thought to play a critical role in supporting lifespan structural and functional brain development.Therefore, the adequacy of nutrition both before birth and in the early formative years has lifelong consequences for cognitive capacity (23).For example, high rates of postnatal growth failure (associated with poorer neurological outcomes) in preterm infants have been attributed to an inability of nutritional practices to effectively mimic the exponential nutrient accumulation that typically occurs during the third trimester of pregnancy, particularly with respect to iron and iodine (24).Nutrients seem to operate as critical signals during childhood and adolescent brain development, acting either directly or indirectly via coupling mechanisms on receptors in relevant sensitive tissues (25).
Evidence of the neuroprotective role of physical activity comes mainly from adult and/or nonhuman samples in which it has been implicated in enhanced neurogenesis, preservation of functional brain specialization, and superior cognitive performance (11,26).Although less robust, studies based on adolescent samples still report cognitive control, particularly working memory, benefits from long-term engagement in exercise (27), which in turn is likely to enhance one's capacity to withstand adversity (28).
Despite substantial evidence supporting the potential of lifestyle factors to alleviate the impact of environmental stressors and genetic risk, the neurodevelopmental underpinnings of these effects remain poorly understood.Addressing this question is critical to designing interventions focused on extending optimal psychological functioning into older adulthood.To probe this issue, we applied a network neuroscience approach to longitudinal multimodal data from the Adolescent Brain Cognitive Development (ABCD) Study (29)(30)(31)(32).Our objective was to identify the brain maturation phenotypes associated with riskenhancing factors-i.e., genetic vulnerability to neuropsychiatric conditions typified by accelerated brain aging [cf.(7)]-and protective lifestyle factors-i.e., close friendships, parental warmth, school engagement, regular engagement in physical activity, healthy diet-and characterize their relationships with subsequent psychological problems.Genetic and environmental influences can lead to heterogeneous maturational trajectories, reflecting accelerated, decelerated, and/or merely atypical development (10).Consequently, rather than probing changes in maturational pace (33), in this study, we investigated individual deviations from normative brain maturation phenotypes on a task that tends to be optimally supported by (group-)typical connectomic patterns (34).
Prior literature suggests that adverse conditions may interact to either inoculate against or sensitize to subsequent stressor exposure (35).Thus, we investigated whether the psychological consequences of the risk-related versus protective neurodevelopmental phenotypes vary as a function of cumulative adversity exposure.We also explored the chemoarchitectonic and transcriptomic correlates of these phenotypes to gain insight into potential cellular-level mechanisms that could be further probed as candidate targets for pharmaceutical and/or cross-species interventions.A schematic representation of our model is presented in Figure 1.The objective was to identify neurodevelopmental patterns (path 1) and their molecular (cell-type and chemoarchitectural) correlates (paths 2, 3) that could explain the joint impact of lifestyle choices and genetic vulnerability on rising psychological problems in adolescence (path 4).The potential for cumulative adversity exposure to moderate the link between neurodevelopmental deviations and psychopathology (path 5) was also probed.We focused on baseline youth reports of close friendships, parental warmth, school engagement, and physical activity, as well as on parental reports of the youths' weekly nutritional intake, which were collected at the 1-year follow-up (46,47) (cf.Section 3 in Supplemental Methods).At the 3-year follow-up, lifetime exposure to negative events was estimated through youth and parent responses on the Adverse Life Events Scale (48).Residualized 2-to 3-year follow-up scores on the 8 subscales from the parent-report version of the Child Behavior Checklist (49) were used to assess cross-diagnostic increases in psychological problems.

Functional Neurodevelopment
Functional brain maturation was characterized with task-based data (Section 6.1 in Supplemental Methods) because it is most closely linked to cognition and behavior (50).Of the 3 ABCD Study functional magnetic resonance imaging (fMRI) tasks, we focused on the n-back task because it most comprehensively samples the mental processes that are transdiagnostically impaired in psychopathology [i.e., spatial and social information-related working memory/cognitive control, emotion reactivity/regulation (29)], including clinical conditions that are typified by accelerated brain aging (51,52).

fMRI Data Preprocessing and Analyses
Minimally preprocessed fMRI data available in the ABCD Study Curated Annual Release 4.0 were further cleaned by eliminating initial volumes to allow the MR signal to reach steadystate equilibrium and removing known confounds via linear regression [cf.(53)] from each voxel's time course (Section 6.3 in Supplemental Methods).
Our main fMRI analyses were based on the Schaefer 300 parcel-functional atlas (54), which was downloaded from https://github.com/ThomasYeoLab/CBIGand aligned in FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki) with the participants' native space for each of the 4 task runs.Pairwise Pearson correlations between the Schaefer regions of interest (ROIs) were expressed as Fisher's z-transformed scores.We retained the positive Fisher's z scores and set negative values to zero (55).Because fine-tuning of task-relevant functional architecture is a key maturational process (31,56), atypical neurodevelopment was operationalized as ROI-based individual deviations from group-normative patterns of functional community organization on the n-back task.This provided a regionally specific summary of maturation for functional brain organization.Functional community structure on the n-back task was estimated across the 100 iterations of a multilayer generalized Louvain-like community detection algorithm (57) implemented in the Network Community Toolbox (58).To quantify increasing functional deviations from time 1 to time 2, a difference score was computed between the probability of each ROI changing communities from the individual-to the group-level partitions at time 2 and time 1, respectively.The focus on ROI-rather than whole brain-level deviations provided us with the spatial specificity required for conducting the cell type-related transcriptomic and chemoarchitectural analyses described below (see also Sections 6.2-6.7 in Supplemental Methods).

Cell Type-Specific Gene Expression Profiles
We investigated the transcriptomic signature of specific cell types that have been implicated in stress responses and neural plasticity processes [astrocytes, microglia (59-63)], those relevant to key adolescent maturation events [i.e., myelination, oligodendrocytes (64)], and those shown to be sensitive to both adversity and environmental enrichment [excitatory/ inhibitory neurons (65,66)].Cell type-specific gene expression profiles [cf.(67)] were identified through microarray gene expression data from 6 postmortem brains and processed as described in Markello et al. (68).Given the interhemispheric gene expression symmetry, our main analyses focused on gene expression patterns mirrored across the 2 hemispheres to maximize comparability with our remaining analyses (Section 7 in Supplemental Methods).All results were replicated when using only the left hemisphere ROIs (Supplemental Results).

Statistical Analysis
We combined canonical correlation analysis (CCA) with partial least squares (PLS) correlation analysis (81)(82)(83)(84).Both were Genetic Risk, Lifestyle, and Neurodevelopment conducted in MATLAB (version 2022a; The MathWorks, Inc.) using a 10-fold cross-validation procedure and 99.9% CIs for each correlation coefficient (for CCA) or loading/salience (for PLS) (Sections 9.1 and 9.2 in Supplemental Methods).One moderated mediation analysis using Hayes' Process 4.2 macro for SPSS (85) was used to test whether the psychological consequences of the atypical neurodevelopment linked to genetic risk and the availability of lifestyle buffers varied with cumulative adversity exposure [cf.86,87)] (see Section 9.3 in Supplemental Methods for details).

Control Variables
The relationships documented herein were extracted from nonresidualized variables.However, the subsequent crossvalidation and moderated mediation analyses controlled for the following well-known confounders [cf.(88)(89)(90)]: chronological age, delay (in months) between baseline and the 2-year follow-up, biological sex, handedness, serious medical problems, scanner site, and average motion per participant for the n-back task (53), which showed some association with the PLS-extracted neurodevelopmental profiles (rs of 0.06 and 0.10 for the time 1 and time 2 motion metrics, respectively).

RESULTS
The results reported below were replicated with the Gordon atlas (91) (Figures S4-S9), thereby attesting to their generalizability across conceptually similar parcellations.

Genetic Risk for Accelerated Brain Aging Pathologies and Lifestyle Support Predict Attentional and Interpersonal Problems
Ten discovery CCAs identified a sole mode that was validated across all test samples (r = 0.11, permutation-based p = .002)(Figure 2C).The extracted pattern implied that greater genetic risk for anxiety disorders, AD, and MDD exacerbated whereas higher availability of lifestyle buffers reduced later increases in attentional and social problems, withdrawal, rule breaking, and aggressive behavior (Figure 2A, B).

Deviations From Normative Functional Connectomic Patterns on a Working Memory Task
The PLS analysis identified one significant brain-behavioral latent variable pair, which was validated across 10 test folds (r = 0.11, p = .003).Notably, a robust association with functional neurodevelopmental alterations emerged only for the gene/lifestyle, but not the psychopathology, CCA variate (r = 0.11, 95% CI, 0.04-0.18across all test samples) (Figure 3A).More specifically, greater genetic vulnerability was related to stronger deviations in the functional development of limbic, anterior default mode network (DMN), control, and dorsal attention regions (Figure 3B).Complementarily, greater availability of lifestyle buffers predicted alterations in typical maturation for visual, posterior DMN, and control areas (Figure 3C).
The unthresholded PLS brain latent variable, averaged across the 10 test folds, was entered in the transcriptomic and  S8).

Transcriptomic Correlates of Risk-Related Phenotypes
Ten discovery CCAs identified a sole mode of cell type covariation with the PLS-extracted functional neurodevelopmental profile described above.The cell-type brain maturation pattern was validated across all 10 test samples with permutation-based significance testing featuring 100,000 spatially constrained null brain maps generated with Vasa's algorithm (r = 0.20, p = .0002)(Figure 4B).The extracted CCA mode indicated that the limbic, anterior DMN, control, and dorsal attention deviations in functional connectomic patterns linked to genetic risk were associated with greater expression of astrocyte-and microglia-specific genes (Figure 4A).

Chemoarchitectonic Correlates of Risk-Related Profiles
To elucidate the overlap between the receptor density maps of neurotransmitters relevant to cognitive control/adversity exposure and the identified functional neurodevelopmental alterations associated with genetic risk and lifestyle buffers, we conducted a CCA with 10-fold cross-validation.A single mode, with robust contributions from GABA

3). (A)
Correlation coefficients describing the relationship between the observed cell type-specific gene expression and the predicted value of their corresponding canonical variate across all test CCAs.Panel (B) depicts the scatter plot describing the linear relationship between the predicted value of the brain latent variable extracted with partial least squares correlation (cf. Figure 3) and the cell type-specific gene expression CCA variate.Error bars are based on the bootstrapping procedure (99.9% CIs) as described in the text.CCA, canonical correlation analysis.

Genetic Risk, Lifestyle, and Neurodevelopment
Biological Psychiatry neurodevelopmental deviations with higher genetic risk overlapped areas of greater 5-HT, D 2 , and mGlu 5 receptor density (Figures 3B and 5C-E).Complementarily, greater GABA receptor density typified the visual, posterior DMN, and control areas showing functional connectomic alterations linked to greater lifestyle buffer availability (Figures 3C and 5F).

Functional Alterations Modulated the Impact of Genetic Risk and Lifestyle on Subsequent Psychopathology
Finally, we probed whether cumulative adversity exposure would shape the psychological consequences of the atypical neurodevelopment linked to genetic risk and the availability of lifestyle buffers.Thus, we specified the moderated mediation model presented in Figure 6.The gene-lifestyle and the psychopathology CCA variate constituted the main predictor and outcome variable, respectively.We observed a significant moderated mediation effect of functional neurodevelopmental deviations, with an index of 0.011 (SE = 0.006, 95% CI, 0.002-0.025).This was driven by the robust interactive effect of cumulative adversity and neurodevelopment on psychopathology risk (b = 0.010, SE = 0.044, t 805 = 2.191, p = .022).Using the Johnson-Neyman procedure in Hayes' Process 4.2 macro, we identified the adversity levels at which brain maturation and psychopathology were significantly related.Thus, for the 22.42% of the participants who were least exposed to adversity, the functional neurodevelopmental alterations linked to genetic risk exerted a protective role against psychopathology, whereas the alterations linked to lifestyle buffers predicted a slightly increased risk of psychopathology (Figure 6).Complementarily, for the 2.04% of the sample who were most exposed to adversity, the lifestyle-connected maturational alterations predicted reduced psychological vulnerability, whereas the genetic risk-connected alterations predicted increased vulnerability.The high adversity-linked result pattern was replicated with the Gordon atlas (91) for the 12.95% of participants with the highest cumulative stress exposure (Figure S9).

DISCUSSION
To our knowledge, this study provides novel evidence regarding the joint impact of genetic risk and lifestyle buffers on adolescent neurodevelopment and subsequent psychological vulnerability.More specifically, we documented deviations in the functional maturation of association areas that undergo substantial changes during the teenage years and play pivotal roles in mediating risk for psychopathology across the life course [cf.(92,93)].Genetic liability to disorders that are typified by accelerated brain aging was associated with altered development of cognitive control-and emotion-relevant functional connectomic patterns, particularly in anterior DMN,  Overall, the observed neurodevelopmental alterations were not significantly related to psychopathology risk (Figure 3A and Figure S4A).However, consistent with prior descriptions of dose-specific effects of adversity exposure (35,94), the observed maturational deviations were differentially related to subsequent psychological well-being as a function of environmental stress.The most consistent pattern, which emerged from both the Schaefer and Gordon atlas data, is that for adolescents who had experienced the highest level of adversity, the neurodevelopmental changes linked to lifestyle buffers mitigated risk for psychopathology, whereas those linked to genetic risk seemed to lead to suboptimal psychological functioning (Figure 6 and Figure S7).Interestingly, under the lowest environmental stress, the genetic vulnerability-linked brain deviations exerted a small yet robust protective effect against subsequent psychopathology, suggestive of compensatory processes (Figure 6B).Conversely, under low environmental stress, there was a small positive association between neurodevelopmental alterations connected to healthier lifestyle factors and subsequent psychopathology (Figure 6A), which likely underscores the adaptiveness of typical functional maturational trajectories [cf.(34,93)].Because greater expression of the "protective" brain profile implies relatively weaker expression of the genetic risk-related profile, the aforementioned finding conceptually replicates the positive relationship between psychopathology and changes in maturational pace observed among the low-risk youths (i.e., low-adversity exposure/low AD/MDD genetic risk) (33).However, the apparent protective role of the genetic risk-related brain profile observed under low-adversity conditions is not comparable to Petrican and Fornito (33), in which genetic and adversity factors formed a single risk index.Indeed, we should underscore the fact that comparisons between the two studies are difficult because Petrican and Fornito (33) focused on accelerated/decelerated (rather than merely atypical) development, sampled only risk factors (i.e., genes and environment) without considering the buffering role of lifestyle variables, and sought to characterize within-individual changes on reward-versus inhibitory control-related tasks rather than individual deviations from normative (group-based) neurodevelopmental patterns linked to both cognitive effort and affective processing.
Returning to the current research, positive lifestyle-related deviations from normative maturational profiles emerged in regions of higher GABAergic receptor density, a finding that echoes the well-documented relevance of this neurotransmitter to cognitive control and responses to stress (71,95).Conversely, departures from normative functional brain maturation linked to higher genetic vulnerability were primarily observed in areas with greater expression of astrocyte-and microglia-specific genes, as well as greater 5-HT, D 2 , and

Genetic Risk, Lifestyle, and Neurodevelopment
Biological Psychiatry mGlu 5 receptor density.The current findings extend prior reports linking adversity exposure and genetic risk for AD/MDD to changes in the maturational pace of inhibitory controlrelevant regions with high D 2 , mGlu 5 , and GABA receptor density (33).More broadly, the developmental deviations observed in greater mGlu 5 , 5-HT, and D 2 receptor density regions reaffirm the former's involvement in stress susceptibility and coping with adversity (72,73,75), as well as the 5-HT and D 2 receptors' relevance to psychopathology and cognitive control (74,76,(96)(97)(98).
Our cell type-specific findings extend evidence from studies conducted with rodents on the role of astrocytes and microglia in shaping adolescent brain (network) maturation processes (61), including synaptogenesis (59,63,99) and regulation of neuroplasticity windows [astrocytes (62)].They are also consistent with previous reports that astrocytes regulate dopamine expression and that astrocyte-microglia interactions affect synaptic glutamate levels and thus indirectly regulate responses to stress, including coping strategies and goaldirected behaviors such as working memory [cf.(59,70,95,100)].Importantly, the involvement of microglial and astrocytic gene expression implies that the observed alterations in functional brain maturation could reflect inflammatory pathways through which genetic risk influences psychological functioning (5,63,101).This finding adds greater specificity to the reported interrelationships among genetic risk for AD/MDD, greater expression of stress susceptibility genes, and changes in brain maturation pace (33).The robust association of atypical functional neurodevelopment with microglial and astrocytic, but not neuronal, gene expression profiles is consistent with existing evidence that astrocytic and microglial signaling can shape neuronal activity and network organization (56,63,102,103).These effects are particularly strong under learning-relevant circumstances that require integration of internal (mental) states with external environmental information (104)(105)(106), as on the ABCD n-back task.
Of the factors that we scrutinized, perceptions of greater school connectedness emerged as the strongest potential buffer against environmental adversity.Thus, our results are consistent with extant theory and evidence on the role of academic pursuits in shielding against deviant activities [e.g., substance use (107)] by fostering self-esteem and resilience to adversity during childhood and adolescence (108,109).While the ABCD Study's global measure of school engagement evidenced good reliability suggestive of a unitary construct, a more fine-grained examination of its components (e.g., connectedness to one's teachers vs. personal involvement with the school environment) may be worth pursuing in future research.Personal involvement with the school environment could stem from the intellectual stimulation that it provides.If so, its buffering role, particularly with regard to cognitive functioning and attentional engagement, may be mediated by the sense of curiosity it triggers which, in turn, is reportedly foundational to both learning and memory (110).In parallel, proof of the neuroprotective function of student-teacher relationships could complement findings on the stress-buffering role of parental warmth, thereby shedding light on the differential relevance of relationships likely to vary in psychological distance.
Extending prior descriptions of the neuroprotective effects associated with positive caregiving (15,111), our results highlight the key role that youth perceptions of parental warmth play in psychological functioning.Thus, we extend prior rodent and human evidence that child and adolescent exposure to enriched and emotionally responsive environments can reverse the sequelae of prior exposure to adversity (112)(113)(114)(115) by demonstrating that responsive parenting could foster the emergence of protective functional neurodevelopmental alterations.
Our current findings also indicated that a healthy diet contributed a robust effect to positive psychological outcomes (i.e., superior attentional skills and interpersonal outcomes).Given that diet is a key determinant of gut microbiota community structure and function (116) and that gut microbiota are strongly implicated in the regulation of brain activity and cognitive function via microbial mediation of communication along the microbiota-gut-brain axis (117), this seems like a plausible explanatory mechanism for the observed effects.Future research should seek to explore this further.
A link between children's social environmental factors and the lifestyle buffers studied here has been already suggested.The home environment is a critical context for the development of eating behaviors (118) and adiposity in childhood (119) because diet-related behaviors and diet quality are strongly influenced by social environmental factors such as role modeling, policies (rules around eating), and family meals (120).Positive associations have been identified between parenting styles and adolescent dietary behaviors including frequency of breakfast, fruit, and unhealthy snack consumption (118).Parental socialization behaviors have also been found to significantly influence child and adolescent physical activity levels (121).The significant effect found for physical activity in the current study whereby it contributed to an attenuation of the impact of genetic vulnerability on later psychological outcomes suggests that interventions that support positive parental influence on both diet and activity would be beneficial for optimal neurological development in youth.

Limitations and Future Directions
Our study has paved the way for several lines of inquiry.First, extension of our findings to other life stages would be worth pursuing in the future given prior reports that the impact of adversity fluctuates with age (1), and thus the buffering effectiveness of lifestyle factors may vary similarly.Second, while our results generalized across sexes, there are welldocumented differences between males and females in the incidence of the disorders studied here (122)(123)(124).Consequently, understanding the preclinical mechanisms, including neurodevelopmental trajectories, that may yield such sex differences warrants further investigation.Third, the moderating role of adversity exposure documented herein was thought to reflect the compounded allostatic load related to negative life experiences, genetic risk for neuropsychiatric disorders, and fewer lifestyle buffers.Inclusion of cellular senescence markers (e.g., DNA methylation) would allow a direct test of this hypothesis and a more fine-grained exploration of the underlying mechanisms.Fourth, further understanding of the stressbuffering function associated with lifestyle factors would benefit from the inclusion of peripheral inflammation markers, which have been linked to greater psychopathology risk and Genetic Risk, Lifestyle, and Neurodevelopment specifically implicated in the brain disorders investigated herein (5,(125)(126)(127).Fifth, there is compelling evidence that different cell types (e.g., astrocytes) undergo disorder-specific changes, which contribute to the distinct profile of each condition (128)(129)(130).Characterizing cell-specific changes from early life onward may provide key insights into personalizing interventions to delay or avoid the clinical onset of brain aging disorders.Sixth, for children who live with their biological parents, shared genetic influences may inflate estimates of environmental effects such as parental warmth.Thus, future investigations that combine biological and adoptive families would be critical for elucidating the extent to which the apparent stress-buffering effect of parental warmth reflects a "true" environmental effect or rather the impact of shared genes on resilience-promoting traits.

Conclusions
The current study provided suggestive evidence for the protective function of lifestyle factors (warm parenting, school connectedness, physical activity, healthy nutrition) among adolescents at genetic risk for brain disorders linked to accelerated aging.We also identified distinguishable functional neurodevelopmental deviations associated with genetic risk versus availability of lifestyle buffers.The 2 profiles of atypical brain maturation had distinguishable cellular signatures and exerted complementary psychopathology-protective roles, which varied with environmental stress levels.Taken together, our findings underscore the importance of educational engagement and healthy nutrition in shielding vulnerable adolescents.They further reinforce the importance of characterizing early-life biomarkers associated with adult-onset pathologies to personalize detection and intervention paradigms.

Figure 1 .
Figure 1.Schematic representation of our conceptual model.(A, B, C) Genetic risk for neuropsychiatric disorders associated with accelerated brain aging (B) was expected to interact with lifestyle factors (A) to derail normative patterns of working memory-relevant functional brain development (C).(D) The objective was to identify neurodevelopmental patterns (path 1) and their molecular (cell-type and chemoarchitectural) correlates (paths 2, 3) that could explain the joint impact of lifestyle choices and genetic vulnerability on rising psychological problems in adolescence (path 4).The potential for cumulative adversity exposure to moderate the link between neurodevelopmental deviations and psychopathology (path 5) was also probed.5-HT, serotonin; Ach, acetylcholine; DA, dopamine; GABA, gammaaminobutyric acid; GLU, glutamate.Photograph 1 by Kenny Eliason (from Unsplash.com).Photograph 2 by Sammie Chaffin (from Unsplash.com).Photograph 3 by Benjamin Manley (from Unsplash.com).Photograph 4 by Jane Doan (from www.pexels.com).Photograph 5 by Ella Olsson (from www.pexels.com).Photograph 6 by Andrea Piacquadio (from www.pexels.com).Photograph 7 by Arran Lewis; attribution 4.0 International (CC BY 4.0).

Figure 2 .
Figure 2. (A, B) Correlation coefficients describing the relationship between the observed genetic risk/lifestyle/psychopathology variables and the predicted value of their corresponding canonical variate across all CCAs.Panel (C) depicts the scatter plot describing the linear relationship between the predicted value of the two variates.Error bars are based on the bootstrapping procedure (99.9% CIs) as described in the text.AD, Alzheimer's disease; CCA, canonical correlation analysis; MDD, major depressive disorder; PRS, polygenic risk score; SCZ, schizophrenia.

CFigure 3 .Figure 4 .
Figure 3.The brain LV from the behavioral-PLS correlation analysis linking the genetic risk/lifestyle and psychopathology CCA variates to functional brain development.Panel (A) shows the correlations between the CCA variates and the predicted brain scores in each condition (based on the 10-fold cross-validation procedure).Panels (B) and (C) depict the Schaefer regions of interest with robust loadings (based on crossvalidated 99.9% CI, as described in the main text) on the LV in panel (A).Region-of-interest colors reflect network assignments by Schaefer et al. (54).In panel (A), error bars are the 95% CIs from the bootstrap procedure.Confidence intervals that do not include 0 reflect robust correlations between the respective CCA variate and the predicted brain score in a given condition across all participants.CCA, canonical correlation analysis; DAN, dorsal attention network; DMN, default mode network; LB, limbic network; LV, latent variable; PLS, partial least squares; SAL/VAN, salience/ventral attention network; SM-A, somatomotor-A network; SM-B, somatomotor-B network; TP, temporoparietal network; VIS, visual network.

FFigure 5 .
Figure 5. Receptor density maps linked by CCA to the observed profile of neurodevelopmental deviations (cf.Figure 3).(A) Correlation coefficients

Figure 3 )
Figure 5. Receptor density maps linked by CCA to the observed profile of neurodevelopmental deviations (cf.Figure 3).(A) Correlation coefficients describing the relationship between the observed receptor density maps and the predicted value of their corresponding canonical variate across all test CCAs.Panel (B) depicts the scatter plot describing the linear relationship between the predicted value of the brain latent variable extracted with partial least squares correlation (cf. Figure 3) and the receptor density CCA variate.Panels (C) to (F) depict the (5-)HT, D2, mGlu 5 , and GABA receptor density maps thresholded at a z score value . 1 for presentational purposes only.Region-of-interest colors reflect network assignments by Schaefer et al.Error bars are based on the bootstrapping procedure (99.9% CIs) as described in the text.(5-)HT, serotonin; Ach, acetylcholine; CCA, canonical correlation analysis; D, dopamine; DAN, dorsal attention network; DMN, default mode network; GABA, gamma-aminobutyric acid; GLU, glutamate; LB, limbic network; SAL/VAN, salience/ventral attention network; SM-A, somatomotor-A network; SM-B, somatomotor-B network; TP, temporoparietal network; VIS, visual network.

Figure 6 .
Figure 6.Moderated mediational model linking the genetic risk/lifestyle CCA variate to increases in psychological problems from the 2-to the 3-year followup.The brain profiles are split into protective (A) and high risk (B) for presentational purposes only.The region of significance for each effect, as presented in the Johnson-Neyman output, appears within brackets on the paths linking the brain and psychological functioning variables.CCA, canonical correlation analysis.Photograph 1 by Kenny Eliason (from Unsplash.com).Photograph 2 by Benjamin Manley (from Unsplash.com).Photograph 3 by Jane Doan (from www.pexels.com).Photograph 4 by Ella Olsson (from www.pexels.com).Photograph 5 by Andrea Piacquadio (from www.pexels.com).