Abstract
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental condition with a complex neurobiological basis spanning neurotransmitter systems, brain structure and connectivity, genetics, cognition, and emerging domains such as neuroinflammation. This narrative review synthesizes the current evidence across these domains, drawing on large-scale consortium studies, meta-analyses, genome-wide association studies, and mechanistic research. The picture that emerges is one of a highly heritable, polygenic disorder characterized by catecholaminergic dysfunction, subtle but widespread structural and functional brain differences, distributed neural network dysconnectivity, and heterogeneous cognitive-motivational profiles. Despite substantial progress, effect sizes for individual neurobiological markers remain small, and no single mechanism is necessary or sufficient to explain all cases. The field is moving toward integrative, multi-pathway models that acknowledge ADHD's neurobiological heterogeneity and its continuity with the general population.
1. Introduction
ADHD affects approximately 5% of children and 2.5% of adults worldwide and is defined by persistent, impairing patterns of inattention, hyperactivity, and impulsivity.[1][2] Although the clinical phenomenology of ADHD has been recognized for over a century, the neurobiological underpinnings have only come into sharper focus over the past three decades, driven by advances in neuroimaging, molecular genetics, and cognitive neuroscience. This review provides a comprehensive overview of the neurobiology of ADHD, organized by level of analysis: neurotransmitter systems, brain structure, functional connectivity, white matter microstructure, genetics, cognitive and motivational models, environmental and immune contributions, and the neurobiological effects of pharmacotherapy.
2. Neurotransmitter Systems
2.1 The Catecholamine Hypothesis
The dopaminergic and noradrenergic systems have long been central to models of ADHD pathophysiology. Brain imaging studies have identified dysfunction of dopamine pathways involved in attention, executive function, and motivation/reward, as well as dysfunction in noradrenergic pathways innervating the prefrontal cortex.[3] The strongest indirect evidence comes from pharmacology: stimulant medications (amphetamine and methylphenidate), the most effective treatments for ADHD, increase central dopamine and norepinephrine activity through transporter inhibition and, in the case of amphetamine, vesicular monoamine transporter 2 (VMAT-2) inhibition and monoamine oxidase inhibition.[4] Atomoxetine, a nonstimulant, selectively blocks the norepinephrine transporter (NET), increasing both noradrenergic signaling and, in prefrontal regions lacking the dopamine transporter, dopaminergic transmission.[5]
Positron emission tomography (PET) studies have investigated dopamine transporter and receptor availability in ADHD, though results remain somewhat inconsistent. Reduced dopamine release and reduced D2 receptor availability have been reported in the caudate and ventral striatum of adults with ADHD.[6] The proposition that methylphenidate, amphetamine, and atomoxetine may all induce therapeutic response partly via NET modulation suggests that noradrenergic factors play a role in ADHD pathogenesis beyond what dopamine alone can explain.[5]
2.2 The Noradrenergic System and the Locus Coeruleus
The locus coeruleus (LC), a compact brainstem nucleus, is the brain's principal source of noradrenaline and has widespread cortical and subcortical projections.[7][8] The LC-norepinephrine system modulates arousal, attention, vigilance, and executive function through dynamic tonic and phasic firing patterns.[5][9] Tonic LC activity sets the overall level of arousal, while phasic bursts optimize the signal-to-noise ratio for task-relevant stimuli — a mechanism formalized in the Adaptive Gain Theory.[9] Dysregulation of this system — whether through hypoactivity leading to poor sustained attention or hyperactivity leading to distractibility — maps directly onto core ADHD symptoms.[10] The clinical efficacy of alpha-2 adrenergic agonists (guanfacine, clonidine) in ADHD further supports the noradrenergic hypothesis.[10]
2.3 Beyond Catecholamines
There is emerging evidence for interactions with serotonergic, glutamatergic, and opioid systems. Methylphenidate has agonist activity at the serotonin 5-HT1A receptor, and both stimulants show evidence of interactions with glutamate and opioid systems.[4] The serotonin transporter gene (SLC6A4) and the serotonin receptor gene HTR1B have shown replicated, though modest, associations with ADHD in candidate gene meta-analyses.[11] These findings suggest that while catecholamines are the dominant neurotransmitter systems in ADHD, the disorder's neurochemistry is not reducible to dopamine and norepinephrine alone.
3. Brain Structure
3.1 Subcortical Volumes
The ENIGMA-ADHD consortium conducted the largest mega-analysis of subcortical brain volumes in ADHD, comparing 1,713 individuals with ADHD to 1,529 controls across 23 sites.[12] Significantly smaller volumes were found in the nucleus accumbens (Cohen's d = −0.15), amygdala (d = −0.19), caudate nucleus (d = −0.11), hippocampus (d = −0.11), putamen (d = −0.14), and total intracranial volume (d = −0.10).[12][13] These structures are components of the frontostriatal and mesolimbic circuits implicated in executive function and reward processing. Importantly, all effect sizes were small, and a follow-up meta-analysis confirmed the mega-analysis results.[12]
3.2 Cortical Morphology
A coordinated ENIGMA-ADHD analysis of cortical measures (N = 2,246 ADHD, N = 1,934 controls) found lower cortical surface area in children with ADHD, mainly in frontal, cingulate, and temporal regions, with the largest effect for total surface area (d = −0.21).[14] Fusiform gyrus and temporal pole cortical thickness were also lower in children with ADHD. Notably, neither surface area nor thickness differences were found in adolescent or adult groups, suggesting possible normalization or developmental compensation.[14] Surface area alterations behaved as endophenotypes in families and were linked to ADHD symptoms in the general population, extending evidence that ADHD operates along a continuous trait distribution.[14]
3.3 Cortical Maturation Delay
A landmark finding in ADHD neurobiology is the approximately 2–3 year delay in reaching peak cortical thickness, particularly in the prefrontal cortex.[1][2] This maturational lag is consistent with the clinical observation that many children with ADHD show symptom improvement with age, and it aligns with the cortical surface area findings that are prominent in childhood but attenuate by adolescence.[1][14]
3.4 The Cerebellum
The cerebellum, traditionally considered a motor structure, is increasingly recognized for its role in cognition, attention, and emotion regulation.[15] In ADHD, cerebellar findings include smaller overall cerebellar volumes, vermis atrophy correlated with inattentive and hyperactive indices, and consistent gray matter reductions bilaterally in lobule IX.[16][17] Longitudinal data show a lower developmental trajectory for cerebellar volume in children with ADHD compared to controls.[15] Functional connectivity studies reveal increased cerebro-cerebellar connectivity in the somatomotor network in ADHD, with age-dependent patterns suggesting that enhanced cerebellar involvement may compensate for cortical dysfunction.[18] Compressed cerebro-cerebellar functional gradients in ADHD implicate co-occurring low-order (visual processing) and high-order (default mode) cognitive dysfunction.[15] The COMT Val158Met polymorphism has been shown to modulate cortico-cerebellar executive function connectivity in children with ADHD, linking genetic variation to cerebellar circuit function.[19]
3.5 Interpretive Caveats
Despite these advances, several concerns persist. Most neuroimaging studies are cross-sectional, precluding causal interpretation. Effect sizes across all regions are small (Cohen's d 0.2), meaning there is substantial overlap between ADHD and typically developing populations, and neuroimaging is not currently useful as a diagnostic tool.[1][2] Many previous studies were underpowered and risked false-positive results, and the small effect sizes reported by large mega-analyses underscore the need for methodological advances before neuroimaging can have clinical diagnostic utility.[1]
4. Functional Brain Networks
4.1 From Regions to Networks
The contemporary understanding of ADHD neurobiology has shifted from discrete regional abnormalities to distributed neural circuit dysfunction. Over the last decade, neuroimaging research has recognized the importance of understanding the function, organization, and development of interacting brain regions rather than isolated structures.[1]
4.2 The Default Mode Network
The default mode network (DMN) has emerged as a central focus in ADHD research. Functional neuroimaging studies show reduced connectivity within the DMN of children with ADHD and a pattern suggestive of delayed DMN neuromaturation.[1] The DMN is hypothesized to underlie mind-wandering and introspection, but in ADHD may reflect a tendency toward distractibility due to impaired regulation of attentional resources.[1]
A mega-analysis of over 2,600 subjects (1,301 ADHD, 1,301 matched controls) confirmed that ADHD is associated with less anticorrelation between the DMN and task-positive networks, including the salience/ventral attention (d = 0.14), somatomotor (d = 0.14), and dorsal attention networks (d = 0.17).[20] These findings were robust to sensitivity analyses considering comorbid internalizing and externalizing problems and psychostimulant medication, and similar patterns were observed when examining ADHD traits in a population sample of over 10,000 individuals.[20] This supports the "default mode interference" hypothesis — the DMN intrudes upon and disrupts externally focused attention.[20]
A system-neuroscience-based meta-analysis of 20 resting-state studies (944 ADHD, 1,121 controls) further characterized DMN dysconnectivity, finding reduced connectivity in the core DMN subsystem but elevated connectivity in the dorsal medial prefrontal cortex subsystem.[21] When restricted to children and adolescents, additional reduced connectivity was detected between the DMN and cognitive control, affective/motivational, and salience networks, consistent with the hypothesis that pediatric ADHD is fundamentally a DMN-dysconnectivity disorder.[21]
4.3 Frontostriatal and Frontoparietal Circuits
Meta-analyses of task-based fMRI studies consistently implicate hypoactivation of frontostriatal and frontoparietal circuits during inhibitory control and attention tasks. A meta-analysis of 55 studies found ADHD-associated hypoactivation in the right inferior frontal cortex, supplementary motor area, anterior cingulate cortex, caudate, and dorsolateral prefrontal cortex.[22][23] These represent two distinct, domain-dissociated right-hemispheric fronto-basal ganglia networks: one for inhibition (inferior frontal cortex, supplementary motor area, anterior cingulate) and one for attention (dorsolateral prefrontal cortex, parietal, and cerebellar areas).[22] Preliminary evidence suggests that long-term stimulant medication use may be associated with more normal activation in the right caudate during attention tasks.[22]
4.4 Mesocorticolimbic (Reward) Circuit
Individuals with ADHD manifest abnormalities within the dopaminergic mesolimbic system. A meta-analysis reported that six of seven studies using the monetary incentive delay task found hypoactivation of the ventral striatum during reward anticipation in ADHD (d = 0.48), a moderate effect size not seen during reward receipt.[23] Reduced nucleus accumbens volume and reduced fractional anisotropy within mesolimbic white matter tracts further support the involvement of this circuit in the motivational deficits characteristic of ADHD.[1][23]
4.5 Neurobiologically Distinct Biotypes
A recent study using data-driven clustering identified three neurobiologically distinct ADHD biotypes based on topological deviations in morphometric similarity networks.[24] Biotype 1, characterized by widespread medial prefrontal cortex-pallidum alterations, exhibited the most severe symptomatology across both clinical domains. Biotype 2, with anterior cingulate cortex-pallidum circuit alterations, showed a predominantly hyperactive/impulsive profile. Biotype 3, marked by superior frontal gyrus alterations, demonstrated a predominantly inattentive presentation.[24] These findings provide neurobiological validation of clinically observable ADHD subtypes and suggest potential targets for individualized therapeutic interventions.
5. White Matter Microstructure
Diffusion-weighted imaging (DWI) studies have investigated the integrity of white matter tracts in ADHD. A systematic review and meta-analysis of 129 DWI studies (6,739 ADHD participants, 6,476 controls) found consistent reduced fractional anisotropy (FA) in the splenium and body of the corpus callosum, extending to the cingulum.[25] Lower FA was related to older age, and case-control differences did not survive in the pediatric-only meta-analysis, possibly reflecting the late development of callosal fibers that may enhance case-control differences in adulthood.[25]
A mega-analysis of over 6,900 participants from five cohorts found that both the diagnosis and symptoms of ADHD were associated with lower FA of the inferior longitudinal fasciculus and left uncinate fasciculus, with small effect sizes (strongest partial r = −0.14, largest case-control d = −0.3).[26] These microstructural anomalies were specific to ADHD and not present for anxiety, mood, or externalizing problems.[26]
Systematic reviews of pediatric studies highlight atypical white matter organization in frontostriatal tracts, the corpus callosum, superior longitudinal fasciculus, cingulum bundle, thalamic radiations, internal capsule, and corona radiata.[27] Connectomic analyses demonstrate global underconnectivity between functionally specialized networks.[27] Mediation analyses suggest that ADHD symptom severity partially mediates the relationship between white matter alterations and functional impairment.[28]
6. Genetics
6.1 Heritability
ADHD is one of the most heritable psychiatric disorders. Family, twin, and adoption studies consistently estimate heritability at approximately 70–80%.[1][2][29] The DSM-5 cites heritability at approximately 74%.[30] This high heritability motivated the search for specific susceptibility genes.
6.2 Candidate Gene Studies
Meta-analyses of candidate gene association studies have identified several genes with replicated associations with ADHD, most prominently within dopaminergic pathways:[11][31][32]
- DRD4 (dopamine receptor D4): The 7-repeat allele of the exon 3 VNTR confers increased risk (OR = 1.34, 95% CI 1.23–1.45), and the 5-repeat allele also shows association (OR = 1.68). The DRD4 7-repeat allele is associated with deficits in attentional orienting and response preparation on electrophysiological measures. Notably, the 7-repeat allele is rare in East Asian populations, where the functionally equivalent 2-repeat allele shows association with ADHD instead.[32][33][34]
- DRD5 (dopamine receptor D5): The 148-bp allele of a nearby microsatellite is associated with increased risk (OR = 1.34, 95% CI 1.21–1.49).[32]
- DAT1/SLC6A3 (dopamine transporter): Despite being one of the most studied candidate genes, meta-analytic evidence for the 480-bp (10-repeat) allele is inconsistent (OR = 1.04, 95% CI 0.98–1.11, p = 0.20 in one large meta-analysis), though a comprehensive meta-analytic review did find a significant, if modest, association.[11][32]
- SNAP-25, SLC6A4 (serotonin transporter), HTR1B (serotonin receptor 1B), and DBH (dopamine beta-hydroxylase) show weaker but replicated associations.[11][31]
6.3 Genome-Wide Association Studies
GWAS have transformed the understanding of ADHD genetics. The first landmark GWAS meta-analysis (20,183 ADHD cases, 35,191 controls) identified 12 genome-wide significant loci, with enrichment in evolutionarily constrained genomic regions, loss-of-function intolerant genes, and brain-expressed regulatory marks.[35] A subsequent, larger GWAS (38,691 ADHD cases, 186,843 controls) identified 27 genome-wide significant loci, highlighting 76 potential risk genes enriched among genes expressed in early brain development, with overall genetic risk associated with midbrain dopaminergic neurons.[36] The most recent GWAS meta-analysis identified 39 independent loci, of which 17 were new, and identified 22 potential ADHD effector genes implicating several new biological processes.[37]
These studies confirm that ADHD's genetic architecture is highly polygenic, with thousands of common variants each having small effects collectively contributing to risk.[29][38] Approximately one-third of ADHD's heritability is accounted for by a polygenic component of common variants.[29] Bivariate modeling estimates that 84–98% of ADHD-influencing variants are shared with other psychiatric disorders.[36] Rare copy number variants (CNVs) are more frequent in ADHD than controls and overlap with CNVs found in autism.[38] Moderate negative genetic correlations (rg −0.40) are observed with multiple cognitive traits.[37]
6.4 Polygenic Risk and Brain Mediation
Polygenic risk scores for ADHD map to hyperactive-impulsive symptoms through white matter microstructure (e.g., axial diffusivity of the corona radiata), cortical anatomy, and cognition, suggesting that common genetic variants influence ADHD symptoms partly through their effects on brain structure.[1] There are currently no diagnostic genetic tests for ADHD, and routine genetic testing for stimulant selection is not justified, though CYP2D6 genotyping for atomoxetine dosing has pharmacogenetic support.[38]
7. Cognitive and Motivational Models
7.1 Executive Function Deficits
A meta-analysis of 83 studies (3,734 ADHD, 2,969 controls) found that groups with ADHD exhibited significant impairment on all executive function (EF) tasks, with effect sizes in the medium range (d = 0.46–0.69).[39] The strongest and most consistent effects were for response inhibition, vigilance, working memory, and planning.[39] EF weaknesses were significant in both clinic-referred and community samples and were not explained by group differences in intelligence, academic achievement, or symptoms of other disorders.[39] However, moderate effect sizes and lack of universality suggest that EF weaknesses are neither necessary nor sufficient to cause all cases of ADHD.[39]
Within ADHD groups, the specific pattern of individual EF impairment varies dramatically: some individuals show pervasive impairment across multiple EF domains, others show profound impairment in one domain but not others, and some show no EF impairment at all.[1] Recent evidence distinguishes "cool" EF (motor response inhibition, working memory, sustained attention, cognitive switching) from "hot" EF (motivational dysfunction, delay aversion, sensitivity to reward and punishment, emotional processing), with cool EF deficits being a greater predictor of inattention and hot EF deficits having a more significant effect on hyperactivity/impulsivity.[13][40]
7.2 The Dual-Pathway and Multi-Pathway Models
The dual-pathway model, proposed by Sonuga-Barke, presents ADHD as arising from two separable but interacting psychopathophysiological pathways.[41] The cognitive pathway involves deficits in executive function, underpinned by disturbances in the fronto-dorsal striatal circuit and mesocortical dopamine branches. The motivational pathway involves altered reward processes and delay aversion, implicating fronto-ventral striatal reward circuits and mesolimbic dopamine branches terminating in the nucleus accumbens.[41] These two pathways are modulated by different branches of the dopamine system and may represent different developmental trajectories.[41]
This model was subsequently extended into a three-way model incorporating a third pathway: deficits in temporal processing, mediated by cortico-cerebellar loop disturbance.[13] ADHD individuals appear consistently compromised in motor timing, perceptual timing, and temporal prediction.[13]
Familial factor analyses support the separability of these pathways. A multivariate analysis found two common familial factors underlying ADHD: one capturing nearly all familial influences on reaction time performance (both mean speed and variability, reflecting subcortical arousal mechanisms) and a second capturing familial influences on response accuracy (commission and omission errors, reflecting prefrontal executive control).[42]
7.3 Cognitive-Energetic and State Regulation Deficits
The cognitive-energetic model emphasizes that ADHD involves difficulty modulating arousal in response to environmental demands. Patients with ADHD make more errors than controls specifically under very fast and very slow stimulus presentation rates, suggesting that performance is most impaired when the task demands are either over- or under-stimulating.[1] This explains the well-known clinical observation that ADHD symptoms are exacerbated during lengthy, monotonous tasks and that performance varies dramatically by context.
8. Environmental Risk Factors
Although ADHD is highly heritable, environmental factors also contribute. An umbrella review of meta-analyses identified eight environmental risk factors associated with ADHD with high-level evidence:[43]
- Convincing evidence (Class I): Maternal pre-pregnancy obesity, childhood eczema, hypertensive disorders during pregnancy, preeclampsia, and maternal acetaminophen exposure during pregnancy.
- Highly suggestive evidence (Class II): Maternal smoking during pregnancy, childhood asthma, and maternal pre-pregnancy overweight.
In subset analyses restricted to prospective cohort studies, only maternal smoking during pregnancy, maternal acetaminophen exposure during pregnancy, and maternal pre-pregnancy obesity/overweight retained their level of evidence.[43]
Importantly, many of these associations have not been definitively shown to be causal. Quasi-experimental designs suggest that most or all of the association between prenatal smoking and offspring ADHD is explained by unmeasured confounding factors, including shared genetic liability.[1][44] Prematurity and low birthweight have been more consistently associated with ADHD, with family studies suggesting these effects cannot be fully explained by genetic confounding.[1] Associations between ADHD and parenting style are likely due to evocative gene-environment correlation, whereby a child's behavior elicits harsh parenting rather than the reverse.[1]
Environmental toxins — lead, organophosphate pesticides, and polychlorinated biphenyls — are associated with ADHD, though the evidence is largely correlational.[44] Experimental evidence shows that artificial food colorings and flavorings increase ADHD symptom severity, but the effects are small.[1]
9. Neuroinflammation and Immune Mechanisms
An emerging area of investigation concerns the role of neuroinflammation in ADHD pathophysiology. Several lines of evidence support this hypothesis:[45][46]
1. Above-chance comorbidity of ADHD with inflammatory and autoimmune disorders.
2. Initial studies indicating associations between ADHD and increased serum cytokines, including a Th1/Th17-dominated proinflammatory profile with elevated IL-12, IL-17, IL-23, IL-4, and IL-10 in adolescents with ADHD.[47]
3. Genetic associations between polymorphisms in inflammatory pathway genes and ADHD.
4. Evidence that early-life exposure to environmental factors may increase ADHD risk via inflammatory mechanisms.
5. Mechanistic evidence from animal models of maternal immune activation documenting behavioral and neural outcomes consistent with ADHD.[45]
A large retrospective study found that elevated inflammatory markers (total WBC, neutrophils, eosinophils, lymphocytes) were detectable in clinically healthy 1-year-old children who were later diagnosed with ADHD, suggesting a potential preclinical inflammatory phenotype.[48] Maternal inflammatory proteins during pregnancy, including IL-6 and MCP-1, have been associated with higher ADHD risk in offspring.[49] The association of maternal metabolic syndrome and acetaminophen use during pregnancy with both ADHD and autism spectrum disorder suggests potential transdiagnostic inflammatory risk factors.[43]
Gut dysbiosis has also been implicated, with compositional differences in taxa important to gut-brain axis pathways (particularly Bacteroides species and Faecalibacterium) potentially contributing to inflammation and neural disturbances in ADHD.[50] While accumulating evidence supports a potential role for neuroinflammation, confirmation of causal mechanisms remains an active area of research.[45]
10. Neurobiological Effects of Pharmacotherapy
10.1 Acute Effects of Stimulants
Across randomized trials, the most consistent acute effect of stimulants is enhancement of activity in the right inferior frontal cortex and insula during neuropsychological tasks requiring attention control and inhibition.[51] Methylphenidate also temporarily normalizes the pattern of activation of the default mode network, which is usually deactivated during attention-demanding tasks but is less deactivated in untreated ADHD.[51] A comprehensive review of stimulant effects found that stimulant-induced modulation of dopamine and norepinephrine neurotransmission optimizes engagement of task-related brain networks, increases perceived saliency, and reduces interference from the default mode network.[52]
10.2 Longer-Term Structural and Functional Effects
Patients with ADHD who have received stimulants for more than 6 months may show activation in the right caudate nucleus that is generally close to normal levels during attention tasks, whereas activation in this area is usually reduced in untreated persons.[51] A qualitative review of 29 MRI studies found that, despite heterogeneity in methods, results were consistent: therapeutic oral doses of stimulant medication attenuate structural and functional alterations found in unmedicated ADHD subjects.[53]
A large cross-sectional study from the ABCD cohort (N > 6,600) found that children with high ADHD symptoms who were unmedicated showed lower cortical thickness in the right insula and lower volume in the left nucleus accumbens compared to both stimulant-treated children with low ADHD symptoms and typically developing controls.[54] There was no difference in brain structural measures between stimulant-treated children and controls, suggesting that stimulant effects may normalize ADHD-associated brain structural abnormalities in regions associated with saliency and reward processing.[54]
A longitudinal MRI study found that in children under 12 years, increased cumulative methylphenidate dosage was associated with increased gray matter volumes in several frontal areas, and greater volumetric increases in specific frontal regions correlated with more significant improvements in oppositional symptoms.[55] This age-dependent effect was not observed in children over 12 years, suggesting a sensitive period for stimulant effects on brain morphology.[55] A recent ABCD Study analysis found that amphetamine and methylphenidate effects on cortical structure were generally opposite in direction to ADHD-associated differences (i.e., "attenuation" toward the control phenotype), while nonstimulants showed a weaker pattern.[56]
10.3 Limitations
Potential effects of prolonged treatment remain controversial. Studies are often limited by small samples, short or no follow-up, and methodological heterogeneity.[52] Smaller average cortical dimensions in several brain regions have been found at the group level in children with ADHD compared to controls, but stimulant treatment did not fully account for these differences.[51]
11. Synthesis and Future Directions
The neurobiology of ADHD is best understood as a multi-level, multi-pathway phenomenon. At the neurotransmitter level, catecholaminergic dysfunction — particularly in dopaminergic and noradrenergic systems — remains the most robustly supported mechanism, though serotonergic, glutamatergic, and immune-inflammatory pathways are increasingly recognized. At the structural level, large-scale consortium studies have identified subtle but widespread differences in subcortical volumes, cortical surface area, cortical maturation, cerebellar morphology, and white matter microstructure. At the network level, dysconnectivity of the default mode network, frontostriatal/frontoparietal circuits, and mesocorticolimbic reward circuits converges with cognitive models emphasizing separable executive, motivational, and temporal processing pathways.
Genetically, ADHD is highly heritable and polygenic, with GWAS identifying dozens of risk loci enriched in neurodevelopmental pathways and midbrain dopaminergic neurons. Environmental risk factors — particularly maternal metabolic and inflammatory exposures — interact with genetic predisposition, and neuroinflammatory mechanisms represent a promising frontier.
Several critical challenges remain. Effect sizes for individual neurobiological markers are small, and there is substantial heterogeneity both within ADHD and between studies. Most neuroimaging studies are cross-sectional, limiting causal inference. The identification of neurobiologically distinct biotypes and the integration of multi-omics data with longitudinal neuroimaging represent promising approaches to parsing this heterogeneity.[24] Ultimately, the goal is to move from group-level statistical associations to mechanistic understanding that can inform individualized diagnosis and treatment.
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