Research into the predominantly inattentive presentation of Attention-Deficit/Hyperactivity Disorder (ADHD-PI) is crucial due to its significant prevalence. Paradoxically, ADHD-PI often remains under-recognized and consequently, undertreated. The persistent nature of inattentive symptoms plays a key role in the high global prevalence of ADHD-PI. Evidence suggests that the characteristics of attentional deficits in ADHD-PI differ from those in other ADHD presentations. Furthermore, individuals with ADHD-PI exhibit impairments in neuropsychological, neurocognitive, and social functioning, which can be distinct to this presentation, such as in processing speed, social perception, and social skills, or differ in severity compared to other types of ADHD. Neuroimaging studies have also identified neuropathological differences specific to ADHD-PI, as well as those shared with other ADHD presentations. Comorbidity is high with learning disabilities and internalizing disorders like anxiety and depression in ADHD-PI. Currently, there is no strong evidence pointing to unique genetic causes for ADHD-PI or differing responses to ADHD medications across presentations. Animal models, like the Wistar Kyoto/NCrl substrain, are being used in translational studies but require further validation as specific models for ADHD-PI. Importantly, much of ADHD-PI research has been framed within the Diagnostic and Statistical Manual (DSM), which may not fully capture the widely accepted dimensional view of ADHD. The Research Domain Criteria (RDoC) offers a promising alternative framework for understanding neuropsychiatric conditions, potentially leading to improved diagnosis and treatment.
Keywords: ADHD Predominantly Inattentive, Inattention, Adhd Pi Diagnosis, Neuroimaging, Comorbidity, Genetics, Pharmacotherapy, Wistar Kyoto/NCrl, RDoC
1. Introduction
Attention-Deficit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental condition beginning in childhood, characterized by developmentally inappropriate and impairing symptoms of inattention, hyperactivity, and impulsivity, often persisting into adulthood [1,2]. ADHD significantly impacts various life domains, including academic and professional success, family dynamics, and social interactions [3]. ADHD is highly heterogeneous, manifesting differently across individuals in behavior, origins, developmental pathways, co-occurring conditions, and treatment responses [3,4]. This heterogeneity is reflected in the different presentations of ADHD: predominantly inattentive (ADHD-PI), predominantly hyperactive-impulsive (ADHD-HI), and combined (ADHD-C).
The terminology and diagnostic criteria for ADHD, like other neuropsychiatric disorders, have evolved over the past half-century, reflecting our growing understanding of the core deficits of this condition [4,5]. Current ADHD diagnosis relies on the Diagnostic and Statistical Manual of Mental Disorders (DSM) and the International Classification of Diseases (ICD), which categorize ADHD as a distinct diagnostic entity [4]. However, this categorical approach has limitations, prompting the exploration of alternative diagnostic frameworks for ADHD [4].
1.1. The Evolution of ADHD-PI in Diagnostic Classifications
The ADHD-PI presentation has been a subject of debate since its introduction in the DSM [5,6]. Initially, before its inclusion in the DSM-III in 1980, the concept of children experiencing significant attention problems without hyperactivity and impulsivity was not widely recognized [7]. Since then, numerous studies have investigated the validity of ADHD-PI [5,6,7,8]. The work of Lahey et al. [9,10] and Healey et al. [11] was crucial in identifying two core symptom clusters: inattention and hyperactivity/impulsivity. This distinction led to the DSM-IV categorization of three ADHD subtypes: combined (ADHD-C), hyperactive-impulsive (ADHD-HI), and predominantly inattentive (ADHD-PI). ADHD-C involves significant levels of both hyperactivity/impulsivity and inattention; ADHD-HI is characterized by hyperactivity/impulsivity with less prominent inattention; and ADHD-PI features significant inattention with less pronounced hyperactivity and impulsivity. Table 1 outlines the DSM-5 criteria for ADHD. The DSM-5 revised the DSM-IV criteria and introduced key updates, including the change from “subtypes” to “presentations” and the addition of ADHD modifiers.
Table 1. DSM-5 Criteria for Attention-Deficit/Hyperactivity Disorder (ADHD).
| Criterion | Description |
|---|---|
| A | A persistent pattern of inattention and/or hyperactivity-impulsivity that interferes with functioning or development, as characterized by (1) and/or (2): |
| 1. Inattention: Six (or more) of the following symptoms have persisted for at least 6 months to a degree that is inconsistent with developmental level and that negatively impacts directly on social and academic/occupational activities: Note: The symptoms are not solely a manifestation of oppositional behavior, defiance, hostility, or failure to understand tasks or instructions. For older adolescents and adults (age 17 and older), at least five symptoms are required. – Often fails to give close attention to details or makes careless mistakes in schoolwork, at work, or during other activities (e.g., overlooks or misses details, work is inaccurate). – Often has difficulty sustaining attention in tasks or play activities (e.g., has difficulty remaining focused during lectures, conversations, or lengthy reading). – Often does not seem to listen when spoken to directly (e.g., mind seems elsewhere, even in the absence of any obvious distraction). – Often does not follow through on instructions and fails to finish schoolwork, chores, or duties in the workplace (e.g., starts tasks but quickly loses focus and is easily sidetracked). – Often has difficulty organizing tasks and activities (e.g., difficulty managing sequential tasks; difficulty keeping materials and belongings in order; messy, disorganized work; has poor time management; fails to meet deadlines). – Often avoids, dislikes, or is reluctant to engage in tasks that require sustained mental effort (e.g., schoolwork or homework; for older adolescents and adults, preparing reports, completing forms, reviewing lengthy papers). – Often loses things necessary for tasks or activities (e.g., school materials, pencils, books, tools, wallets, keys, paperwork, eyeglasses, mobile telephones). – Is often easily distracted by extraneous stimuli (for older adolescents and adults, may include unrelated thoughts). – Is often forgetful in daily activities (e.g., doing chores, running errands; for older adolescents and adults, returning calls, paying bills, keeping appointments). | |
| – 2.Hyperactivity and Impulsivity: Six (or more) of the following symptoms have persisted for at least 6 months to a degree that is inconsistent with developmental level and that negatively impacts directly on social and academic/occupational activities: Note: The symptoms are not solely a manifestation of oppositional behavior, defiance, hostility, or a failure to understand tasks or instructions. For older adolescents and adults (age 17 and older), at least five symptoms are required. – Often fidgets with or taps hands or feet or squirms in seat. – Often leaves seat in situations when remaining seated is expected (e.g., leaves his or her place in the classroom, in the office or other workplace, or in other situations that require remaining in place). – Often runs about or climbs in situations where it is inappropriate. (Note: In adolescents or adults, may be limited to feeling restless.) – Often unable to play or engage in leisure activities quietly. – Is often “on the go,” acting as if “driven by a motor” (e.g., is unable to be or uncomfortable being still for extended time, as in restaurants, meetings; may be experienced by others as being restless or difficult to keep up with). – Often talks excessively. – Often blurts out an answer before a question has been completed (e.g., completes people’s sentences; cannot wait for turn in conversation). – Often has difficulty waiting his or her turn (e.g., while waiting in line). – Often interrupts or intrudes on others (e.g., butts into conversations, games, or activities; may start using other people’s things without asking or receiving permission; for adolescents and adults, may intrude into or take over what others are doing). | |
| B | Several inattentive or hyperactive-impulsive symptoms were present prior to age 12 years. |
| C | Several inattentive or hyperactive-impulsive symptoms are present in two or more settings (e.g., at home, school, or work; with friends or relatives; in other activities). |
| D | There is clear evidence that the symptoms interfere with, or reduce the quality of, social, academic, or occupational functioning. |
| E | The symptoms do not occur exclusively during the course of schizophrenia or another psychotic disorder and are not better explained by another mental disorder (e.g., mood disorder, anxiety disorder, dissociative disorder, personality disorder, substance intoxication or withdrawal). |
| Specify whether: | |
| – Combined presentation: If both Criterion A1 (inattention) and Criterion A2 (hyperactivity-impulsivity) are met for the past 6 months. – Predominantly inattentive presentation: If Criterion A1 (inattention) is met but Criterion A2 (hyperactivity-impulsivity) is not met for the past 6 months. – Predominantly hyperactive/impulsive presentation: If Criterion A2 (hyperactivity-impulsivity) is met but Criterion A1 (inattention) is not met over the past 6 months. | |
| Specify if: | |
| In partial remission: When full criteria were previously met, fewer than the full criteria have been met for the past 6 months, and the symptoms still result in impairment in social, academic, or occupational functioning. | |
| Specify current severity: | |
| – Mild: Few, if any, symptoms in excess of those required to make the diagnosis are present, and symptoms result in only minor functional impairments. – Moderate: Symptoms or functional impairment between “mild” and “severe” are present. – Severe: Many symptoms in excess of those required to make the diagnosis, or several symptoms that are particularly severe, are present, or the symptoms result in marked impairment in social or occupational functioning. |
Note: American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (Copyright © 2013).
1.2. Shifting from “Subtype” to “Presentation” in ADHD
The DSM-5’s shift from ADHD “subtypes” to “presentations” reflects the understanding that ADHD symptoms can change over time within individuals [12,13]. For example, many children initially diagnosed with ADHD-C may transition to ADHD-PI as they age, given the relative stability of inattentive symptoms across development, while hyperactivity/impulsivity tends to decrease with age [14]. The term “presentation” therefore better describes an individual’s current symptom profile, which can fluctuate, compared to the more fixed, trait-like implication of “subtype” [15].
Despite this terminological shift, research continues to explore the neurobiological basis of ADHD presentations. A long-standing debate also persists: are these presentations distinct disorders requiring different classifications, or are they clinically significant points along a spectrum of ADHD [4,16,17]? Addressing this debate is beyond this review’s scope. This article aims to discuss key advancements in ADHD-PI research, focusing on findings from neuropsychology, neuroimaging, genetics, and pharmacotherapy. Given its high prevalence, the limited research attention it has historically received, and the persistence of inattentive symptoms, providing updated information on ADHD-PI is essential. Translational research, including the use of animal models to understand complex neuropsychiatric disorders, is increasingly vital. This review also includes findings from studies using animal models of ADHD-PI.
2. Methods
This review examined over 100 articles investigating behavioral and neurocognitive impairments, comorbid conditions, neurobiology, genetics, and pharmacotherapy of ADHD-PI. Articles were identified through systematic searches of EMBASE and PubMed and manual review of references from included studies. Search terms are listed in Table S1. No date restrictions were applied, with the final search conducted in April 2020. For human studies, inclusion criteria were: English language, clinical ADHD diagnosis prior to the study, meeting ADHD criteria based on clinical tools (e.g., DSM-IV, DSM-5, ICD-10) as rated by clinicians, teachers, or parents. Studies using earlier DSM versions (DSM-II or DSM-III) were excluded due to different diagnostic approaches. Clear identification of ADHD presentations in the analysis of measures (neuropsychological, neuroimaging, genetic, etc.) was required. Editorials, reviews, commentaries, and case reports were excluded.
Initial screening removed duplicates, and titles and abstracts were assessed for relevance based on inclusion/exclusion criteria. Rejection criteria included: non-English language, reviews, commentaries, case reports, editorials, and topics outside the study scope. Two reviewers (M.P. and C.G.T.) independently screened titles and abstracts. Disagreements were resolved by a third reviewer (ID). Full texts were retrieved for remaining records and checked against eligibility criteria. Papers were rejected if ADHD-PI diagnosis didn’t use DSM or ICD-10, or used earlier DSM versions. Studies lacking quantitative data were also excluded. Eligible papers were included in the review. Three authors (I.D., M.P., and T.A.) independently extracted data, including author, year, study design, setting, clinical tool, and key findings, using a PRISMA-compliant data extraction form [18].
3. Prevalence of ADHD-PI
A comprehensive meta-analysis of 86 ADHD studies in children and adolescents and 11 in adults worldwide indicated that ADHD-PI, as defined by DSM-IV, was the most prevalent presentation in community samples [19]. Prevalence rates were 23% in preschool children with ADHD, increasing to 45% in elementary school children and 75% in adolescents. Unlike ADHD-HI and ADHD-C, ADHD-PI prevalence did not decrease in adult samples, remaining the most common ADHD presentation in adults [19]. However, ADHD-PI may be under-recognized and undertreated, as individuals with this presentation are less likely to be referred for clinical services than those with ADHD-C [19]. A 2017 study in China, a region with a large and diverse population, also found ADHD-PI to be the most common presentation, accounting for 67.43% of diagnosed ADHD cases in elementary school students [20]. Similarly, a recent meta-analysis of ADHD prevalence in Africa showed ADHD-PI as the most common subtype, followed by ADHD-HI and ADHD-C [21]. These studies suggest a consistent global predominance of ADHD-PI in prevalence studies. The stability of inattentive symptoms over time may contribute to this higher prevalence [14]. Huang et al. [20] also found that while hyperactivity/impulsivity symptoms tend to decrease early in life, inattention persists in individuals with ADHD. Furthermore, ADHD-PI shows a gender difference, with females more likely to be diagnosed than males [22,23], although overall, boys with ADHD outnumber girls [24]. Females are better represented in ADHD-PI than ADHD-C, especially in non-referred community samples [25]. Interestingly, the African meta-analysis found ADHD-PI most common in both boys and girls [21]. Further research is needed to understand gender differences in ADHD epidemiology across different regions.
4. Behavioral, Neurocognitive, and Neuropsychological Characteristics of ADHD-PI
ADHD-PI symptoms include difficulty paying close attention to detail, struggling to maintain focus, not following instructions, failing to complete tasks, difficulty listening, organizational problems, avoiding tasks requiring sustained effort, losing items, easy distractibility, and forgetfulness (Table 1). While both ADHD-PI and ADHD-C involve attention deficits, clinically significant hyperactivity and impulsivity are primarily seen in ADHD-C. It’s also proposed that the nature of inattention differs between ADHD-PI and ADHD-C. ADHD-PI is linked to sensory processing issues and poorly focused attention [26,27,28], while ADHD-C is characterized by difficulties in sustained attention, distractibility, lack of persistence, and disorganization [8,29]. Children with ADHD-PI may also exhibit more pronounced sluggish cognitive tempo (SCT) symptoms, such as slow responses to cognitive and social cues [26], compared to ADHD-C [8,30,31,32,33].
Inattentive behaviors are complex and thought to be related to neurocognitive function abnormalities [13,34]. Continuous performance tests (CPT) can effectively measure attention skills and identify deficits in ADHD [35]. A meta-analysis of CPT studies found that individuals with ADHD show significant impairments in omissions, indicating a deficit in selective attention [36]. Studies using Conner’s CPT have shown that children with ADHD-PI perform worse than controls and those with ADHD-C on omissions [37,38], suggesting this deficit is strongly linked to inattention [37,38]. Another CPT study found ADHD-PI individuals underperformed compared to typically developing controls in selective attention (omissions), sustained attention, vigilance, processing speed, inhibitory control, and maintaining consistent response times [39]. Subtype-specific differences couldn’t be determined in this study as other subtypes were not included. Other tests also explore inattention in ADHD-PI and differences across subtypes. In a counting Stroop task, assessing cognitive interference and sustained attention, both ADHD-PI and ADHD-C groups showed greater cognitive interference than controls, suggesting similar deficits in sustained attention and interference control [40]. In a dichotic listening task, examining attention, cognitive control, and perception, children and adolescents with ADHD-PI showed a stronger right-ear advantage even in forced left conditions compared to ADHD-C and controls. This suggests a cognitive control deficit in ADHD-PI, indicating difficulty inhibiting irrelevant stimuli and refocusing on relevant cues [41].
Executive function abnormalities, including difficulties in focusing and sustaining attention [42], are also relevant to ADHD. While executive function problems are well-documented in ADHD-C, less is known about deficits in ADHD-PI and whether they differ from other presentations. A study using teacher ratings of school-related executive function difficulties in Finnish children found that those with ADHD-PI had a broader range of challenges, including planning, initiation, and attention, compared to ADHD-C [43]. However, a study of preschoolers in China found that ADHD-C children showed poorer executive function on the Behavior Rating Scale of Executive Function Preschool Version (BRIEF-P) [44]. These conflicting findings might be due to differences in subject age and rating scales used. Larger, methodologically consistent studies are needed to clarify subtype-specific executive function deficits. Performance-based cognitive tests for executive function could further illuminate weaknesses in ADHD-PI.
Neuropsychological processes like working memory and processing speed are also important in ADHD [45]. Working memory, an essential executive function, involves holding and manipulating information briefly [46]. Working memory deficits are seen across ADHD presentations [47,48]. However, one study showed ADHD-PI children performed worse on backward versus forward working memory tasks compared to ADHD-C, suggesting different patterns of working memory deficits [49]. Processing speed, the ability to process information and respond quickly [50], is also relevant. Studies indicate a higher risk of processing speed deficits in ADHD-PI compared to typically developing children [51,52] and ADHD-C [48]. Adults with ADHD-HI may show faster processing speed [53], while inattentive symptoms are linked to slower processing speed [53,54], suggesting processing speed impairments are specific to ADHD-PI. A recent study confirmed that processing speed deficits are primarily related to inattention, not hyperactivity/impulsivity [55], suggesting inattention leads to less efficient performance on tasks with higher perceptual or psychomotor demands, while hyperactivity/impulsivity affects psychomotor speed and incidental learning through inaccuracy or reduced efficiency [55].
Despite evidence of neuropsychological differences between ADHD-PI and ADHD-C, a meta-analysis found limited support for neuropsychological distinctions between these presentations [8], suggesting they may differ only in severity [34]. However, this remains debated. Other evidence points to distinctions between ADHD presentations, and alternative research frameworks are proposed to better understand ADHD’s neurobiology and heterogeneity (see Section 10).
In social functioning, ADHD-PI individuals often struggle and have social perception difficulties. A study comparing social functioning in ADHD-PI and ADHD-C found impaired assertiveness in ADHD-PI youths, while ADHD-C youths had self-control deficits [56]. Social perception differences were also observed, with ADHD-PI performing worse on direct measures of social understanding and skills [57]. Affect recognition is also impaired in adults with ADHD, particularly ADHD-PI compared to ADHD-C [58]. Recent research highlights social skills deficits, lack of assertiveness, and functional impairments at home and school in ADHD-PI youths [59]. Social impairments in ADHD-PI children are often attributed to passive, withdrawn behaviors and lack of social knowledge, leading to peer neglect and isolation. In contrast, ADHD-C children are more impulsive and intrusive, leading to active peer rejection [7,8,56]. Laboratory studies show ADHD-PI children struggle with attending to social cues and engaging in social interactions [60].
In summary, evidence suggests differences in the nature of attentional deficits between ADHD-PI and other presentations. Neuropsychological, neurocognitive, and social functioning differences are apparent in ADHD-PI, potentially subtype-specific (e.g., processing speed, social perception, social skills) or differing in severity (e.g., executive functions, working memory). Small sample sizes limit the generalizability of many studies. Future research should include ADHD-HI in assessments to fully establish ADHD-PI-specific impairments. However, recruiting ADHD-HI patients is challenging due to their lower prevalence in samples compared to other presentations [61].
5. Comorbidity Patterns in ADHD-PI
ADHD has significant comorbidity with other childhood-onset neurodevelopmental and psychiatric disorders [2]. While early studies suggested comparable comorbidity rates across ADHD presentations [62,63], more recent research [64] indicates ADHD-PI may be more vulnerable, especially concerning internalizing problems like withdrawal and depression [8,65]. A study of Turkish children found comorbid anxiety disorder more common in ADHD-PI, while oppositional defiant disorder (ODD) was more frequent in ADHD-C [66]. ODD scores were also higher in boys with ADHD-C in a Japanese study [67]. High comorbidity between childhood ADHD, particularly ADHD-PI, and social anxiety disorder (SAD) was found in Turkish outpatient psychiatry settings [68]. A Spanish cross-sectional study also showed adolescents with ADHD-PI had greater social anxiety than those with ADHD-HI and ADHD-C [69]. Hyperactivity and impulsivity symptoms are more associated with comorbidities like aggressive behavior, conduct problems, criminal behavior, personal failure, and negative self-statements [8,66,70,71,72,73,74]. A German study of clinic-referred adult ADHD patients found higher rates of externalizing behaviors in ADHD-HI and combined presentations [75]. A Taiwanese study of ADHD adults also showed ADHD-PI individuals were less likely to develop persistent ODD and conduct disorders compared to ADHD-C [76].
Regarding substance use, stronger links between hyperactivity/impulsivity symptoms and substance use and abuse/dependence have been observed [77], consistent with impulsivity being a risk factor for substance use disorders [78]. A cross-sectional study found higher gambling problems in those screening positive for ADHD-C compared to ADHD-PI [79], though both subtypes were equally likely to gamble compared to non-ADHD controls. While ADHD-PI children also show some impulsivity (e.g., poor response inhibition), their impulsivity is often described as difficulty finishing tasks when tired or bored [80].
ADHD-PI is also more likely to co-occur with learning disabilities and long-term academic difficulties, sometimes more severe than in other ADHD presentations [81,82,83]. Reading and math learning disorders are associated with both ADHD-PI and ADHD-C [84]. Other studies highlight a significant link between ADHD-PI and overall reading problems [85,86,87]. For instance, in a clinical sample, inattentive behaviors, but not hyperactivity/impulsivity, were associated with reading fluency and comprehension [87]. A more recent study found ADHD-PI children were at higher risk of being in the lowest 10th percentile for reading, writing, and math compared to ADHD-C and ADHD-HI, even after controlling for IQ and gender [88]. Conversely, higher risks for reading/spelling and math difficulties have been found in children with high hyperactivity scores [89]. These differing outcomes may be due to factors like teacher versus parent ratings of ADHD symptoms. Objective tests are needed to reliably assess achievement levels.
Other comorbidities include sleep disruptions like sleep impairment, sleepiness, and poor sleep quality [76,90,91,92]. While ADHD subtypes generally show worse sleep quality than controls [93], findings on which subtypes have greater sleep dysfunction are inconsistent [76,91,93], potentially due to gender, treatments, and comorbid psychiatric issues. However, comorbid anxiety has been significantly linked to impaired sleep in ADHD-PI [90].
In conclusion, ADHD-PI shows high comorbidity with learning and internalizing disorders (anxiety, depression). Longitudinal studies exploring comorbidity development across ages are needed to understand underlying causes and design interventions. The overlap between ADHD-PI and anxiety disorders can contribute to misdiagnosis or overdiagnosis of ADHD-PI [94,95]. Differential diagnosis of ADHD-PI and anxiety, especially regarding inattention, is challenging [95]. As research supports different origins of inattention in ADHD and anxiety [96,97,98], developing neuropsychological and diagnostic tools to better distinguish these conditions is crucial.
6. Neuroimaging Findings in ADHD-PI
Neuroimaging has significantly advanced our understanding of ADHD’s neurobiological bases and helped explore neuropathological similarities and differences between ADHD presentations [99,100]. Few studies have examined structural volume changes in ADHD subtypes. In contrast to controls, ADHD-PI children showed smaller volumes in the anterior cingulate cortex, left medial frontal gyri, caudate, thalamus, and right postcentral gyrus gray matter. ADHD-C children showed volume reductions in frontal, parietal, temporal, and occipital lobes [101]. However, some studies found no significant volume differences in basal ganglia structures between ADHD-PI, ADHD-C, and controls [102,103,104]. Conversely, other studies reported smaller bilateral caudate and anterior cingulate cortex volumes in ADHD-C compared to ADHD-PI and controls [105]. More research, considering factors like age and gender, is needed to clarify these inconsistent findings, given the limited number of studies in this area.
Functional neuroimaging, allowing non-invasive brain function measurement, has furthered our understanding of ADHD-PI and other presentations [106]. Solanto et al. [26] first showed greater activation in middle frontal, temporal, and parietal regions in ADHD-PI children. ADHD-C children showed greater bilateral medial occipital lobe activation compared to ADHD-PI. A meta-analysis of fMRI studies using Go/no-go, Stop, and N-back tasks aimed to identify consistent neural dysfunction patterns in ADHD subtypes [107]. This meta-analysis revealed more pronounced underactivation in the right superior and inferior frontal gyrus during the Stop task, right caudate during Go/no-go, and right cerebellum during the N-back task in ADHD-C compared to ADHD-PI [107]. Default mode network (DMN) areas, including medial frontal and occipital regions, were more significantly activated in ADHD-C compared to controls during these tasks [107]. The DMN, more active during rest than cognitive activity [108], is implicated in regulating goal-directed activity, motivation, and attention in ADHD [109]. DMN dysregulation during tasks due to sustained attention deficits is linked to increased errors and decreased attention [110,111], and associated with impulsivity and impaired response inhibition in ADHD-C [112,113,114].
In an fMRI auditory oddball task, assessing attentional orienting and working memory updates [115], ADHD-PI youths showed abnormal activity in frontoparietal regions associated with early sensory processing and orienting, with little fronto-striatal abnormalities, contrasting with ADHD-C adolescents who showed caudate and lateral prefrontal oddball activation deficits [116,117]. Parietal area abnormalities may be a key difference between ADHD-PI and ADHD-C [118], aligning with norepinephrine pathway involvement in ADHD [119] and oddball-elicited event-related potentials [120]. Fronto-striatal deficits are particularly linked to hyperactive/impulsive symptoms [116,117]. However, frontoparietal deficits in both ADHD-PI and ADHD-C suggest shared impairment in this pathway [117], potentially more pronounced in ADHD-PI given greater parietal, insular, and cingulate abnormalities [116]. Conversely, a recent fMRI study showed fronto-striatal network abnormalities in both ADHD-PI and ADHD-C adults during a counting Stroop task [118], but more dramatic hypoactivation in the fronto-striato-parietal network in ADHD-C, suggesting broader neurocognitive impairment beyond fronto-striatal networks. Fronto-striato-parietal networks are involved in attention, decision-making, and working memory for Stroop task performance [121].
Reward and motivation dysfunctions and drug addiction susceptibility are also ADHD characteristics [53,122,123]. In a motivational fMRI study, ADHD-PI adults showed bilateral ventral striatal deficits during reward anticipation, while ADHD-C subjects showed orbitofrontal hypoactivation to reward feedback [124], an interesting finding given the negative correlation between hyperactivity/impulsivity and ventral striatal activation during reward anticipation [53,124,125].
Functional and structural connectivity analyses are increasingly used to understand brain connectivity in ADHD presentations, suggesting distinct altered neural networks [126,127]. Classification analysis of multimodal imaging and phenotypic data linked structural graph theory network measures of the DMN to ADHD-PI compared to ADHD-C, ADHD-HI, and controls [128]. Resting-state fMRI (rs-fcMRI) studies using graph theory also reported differential neural activation in sensorimotor and DMN in ADHD-PI versus ADHD-C [112] and ADHD-PI versus controls [129]. Future research should examine correlations between DMN functional differences and volume and structural covariance within this network. However, no functional connectivity differences were found between ADHD-PI and ADHD-C in drug-naïve adults with ADHD [130], and ADHD-C and ADHD-PI individuals were evenly distributed along a dimensional biotype axis in childhood-onset adult ADHD (see Section 9) [130].
Diffusion tensor imaging (DTI) has also provided insights into structural and white matter connectivity defects in ADHD subtypes [131,132,133,134]. DTI measures directional water diffusion along axons, reflecting white matter microstructure [134,135]. Fractional anisotropy (FA) values indicate white matter microstructure changes [39,137]. One DTI study showed ADHD-PI children had higher FA in anterior thalamic radiations (ATR), bilateral inferior longitudinal fasciculus (ILF), and left corticospinal tract (CST) [131]. ATR connects frontal cortex with thalamic nuclei, important for fronto-striato-thalamic circuits involved in executive, social, and motivated behaviors [138,139]. ILF connects temporal regions, and abnormalities may contribute to learning difficulties in ADHD-PI [30,140]. CST white matter alterations in ADHD-PI may relate to motor development and fine/gross motor skill alterations in ADHD [141]. ADHD-C, conversely, showed higher FA in the bilateral cingulum bundle (CB) [131], facilitating DMN hub interactions [142], consistent with DMN alterations in ADHD-C (McCarthy et al., 2014) and potentially underlying executive function and sustained attention deficits in ADHD-C [140]. Significant radial diffusivity abnormalities in the ventral corpus callosum (FMi) were found in ADHD-PI [131], associated with processing speed [143], which is slower in ADHD-PI than ADHD-C [144].
A structural connectome study of ADHD-PI and ADHD-C revealed network organization differences with preserved volume [99]. Nodal degree differences, reflecting network connections, were found between ADHD-PI and ADHD-C [99]. In ADHD-PI, nodal degree was higher in limbic, visual, and ventral attention network regions, consistent with disrupted frontoparietal and limbic pathways [99,112,145,146] observed mainly in ADHD-PI [116,117]. Amygdala nodal degree was also higher in ADHD-PI compared to controls, potentially relating to poor emotional regulation and social cognition issues [147]. In ADHD-C, nodal degree was higher in the cerebellum [99], associated with motor networks and frontoparietal executive control circuits [99], compared to ADHD-PI. Nodal degree was also higher in the anterior cingulate (DMN key node), middle frontal gyrus, and putamen in ADHD-C compared to controls, related to impulsivity, disinhibition, distractibility, goal-directed action, and attention deficits in ADHD-C [148]. Limitations of this study include lack of cognitive measures and small sample size, limiting generalizability [99].
In summary, neuroimaging studies have significantly contributed to understanding ADHD-PI and other presentations. Small sample sizes, methodological differences, and reproducibility remain challenges in neuroimaging, potentially addressed by multicenter collaborations [4]. Cross-sectional designs limit establishing causality between neural correlates and ADHD traits. Pharmaco-imaging (neuroimaging combined with controlled trials) can address causality and identify intervention effects [149]. Including female subjects in neuroimaging is also vital given the higher ADHD-PI rate in females.
7. Genetic Factors in ADHD-PI
Like other psychiatric disorders, ADHD likely arises from interactions between genetic and environmental risks [1]. Genetic influences in ADHD are well-documented [1,4,150]. ADHD is highly heritable, estimated at 70–80% [1,151].
Association studies aim to identify ADHD susceptibility genes, including those specific to subtypes. Subtype-specific genetic analyses aim to reduce heterogeneity and identify candidate genes [152]. Evidence for dopaminergic system involvement in ADHD has led to studies of dopamine-related genes like dopamine transporter (SLC6A3/DAT1), and dopamine receptors (DRD4 and DRD5) [151]. A family-based study of Chinese children with ADHD reported DAT1 gene variations, particularly haplotype rs27048 (C)/rs429699 (T), significantly associated with inattentive subtype and severity [153]. No allele or haplotype was linked to hyperactivity/impulsivity severity. Some studies found stronger DRD4 polymorphism associations with inattention than hyperactivity-impulsivity [154,155]. Children with high levels of an inattentive endophenotype showed a stronger association between inattentive symptoms and DRD4 [154]. DRD5 has been linked to both ADHD-PI and ADHD-C [156].
The noradrenergic system, crucial for behavioral activation, alertness, and attention, is another key neurotransmitter system in ADHD. Associations between the MspI polymorphism at the adrenergic α2A receptor (ADRA2A) gene and inattention have been reported in Brazilian youths with ADHD [157,158]. Pharmacogenetic studies showed greater improvement in inattentive symptoms after methylphenidate treatment in children with the G allele at the ADRA2A-1291 C > G polymorphism [159]. Follow-up studies in non-referred ADHD-PI children also showed greater methylphenidate improvement in inattention in those with the G allele [160]. Limitations in sample size and study design [160] prevent definitive conclusions about the direct link between ADRA2A polymorphisms, ADHD-PI, and methylphenidate response.
Besides dopamine and norepinephrine, other neurotransmitter systems, like serotonergic and cholinergic systems, are implicated in ADHD. Genes related to receptors, transport, synthesis, and metabolism (e.g., COMT, MAO, DDC) of these neurotransmitters have been studied in ADHD-PI. Molecular genetic studies in Han Chinese populations showed genes for serotonergic receptor 5-HT1B and cholinergic receptor CHRNA4, as well as COMT, MAO-A, and DDC, were predominantly associated with ADHD-PI [161,162,163,164,165]. Conversely, serotonergic receptor genes 5-HTR2C and 5-HT1D, noradrenergic receptor ADRA2C, dopaminergic receptor-associated gene DRD3, and norepinephrine transporter gene NET1 were primarily linked to ADHD-C [161,162,163,164,165].
Beyond neurotransmitter systems, genes regulating other neural processes are also relevant in ADHD [166]. Disturbances in cerebral asymmetry have been suggested in ADHD pathogenesis [167]. The cerebral asymmetry gene BAIAP2, on 17q25, encoding brain-specific angiogenesis inhibitor 1-associated protein 2 (BAIAP2), has been linked to ADHD in European populations [168]. BAIAP2 has also been associated with childhood ADHD in Han Chinese, especially ADHD-PI [169].
These findings represent progress in identifying genetic factors in ADHD-PI, but causal links need to be established. The role of other genes in basic processes (cell division, adhesion, neuronal migration, synaptic plasticity, etc.) in ADHD-PI pathology should be investigated [150,170]. Small sample sizes in genetic studies are a limitation, contributing to weak gene-trait associations. Large-scale, multicenter studies are being used to decipher ADHD’s genetic architecture [4,149], potentially uncovering subtype-specific genetic causes.
8. Pharmacotherapy for ADHD-PI
ADHD treatments include behavioral therapy and medications, like stimulants (methylphenidate, amphetamine) and non-stimulants (atomoxetine). Few studies examine medication effects on ADHD presentations. Most studies focus on psychostimulants, particularly methylphenidate. Stein et al. [171] reported 60% of ADHD-PI children showed optimal response to lower methylphenidate doses based on parent and teacher ratings, while 66–75% of ADHD-C children needed higher doses. They suggested lower doses effectively treat inattention, while higher doses target hyperactivity and impulsivity [171]. However, Solanto et al. [172] found no significant difference in response to different methylphenidate doses between ADHD subtypes, with predominantly linear drug effects for both ADHD-C and ADHD-PI. These conflicting outcomes may be due to patient characteristics, study design, rating scales, and outcome measures [61]. In ADHD children previously treated with immediate-release methylphenidate, OROS methylphenidate for 21 days improved (parent-rated) symptoms, especially in older children (10–16 years), higher doses (36 or 54 mg), and those with ADHD-PI [173]. A recent study [61] found boys with high hyperactivity-impulsivity (ADHD-HI) showed greater methylphenidate response than ADHD-PI, consistent with Stein et al. [171]. However, this study didn’t include girls, examine different doses, or fully isolate medication effects from combined behavioral interventions [61].
Methylphenidate response in adults with ADHD has also been studied. Dexmethylphenidate extended-release (ER) was found effective compared to placebo [174], with no significant difference in subtype-specific responses, equally improving ADHD-PI and ADHD-C symptoms [174], consistent with a German study showing similar methylphenidate clinical response in ADHD-PI and ADHD-C adults [175]. However, methylphenidate response differed between ADHD patients with and without psychiatric comorbidities like depression, with non-depressed patients benefiting more. A Chinese study showed methylphenidate improved IQ scores in ADHD children compared to untreated controls, with no subtype-related difference in cognitive improvement [176].
Chronic methylphenidate treatment effects on neurosteroid levels (allopregnanolone, DHEA) and daily fluctuations in ADHD children were examined to understand the drug’s mechanism. Methylphenidate doubled allopregnanolone levels in ADHD-PI children without depression, but didn’t alter DHEA levels differently between subtypes. Distinct allopregnanolone and DHEA responses suggest differential effects on attention and impulse control, and allopregnanolone may be a biomarker for ADHD-PI [177]. The same group found decreased serum BDNF in ADHD patients compared to controls, with further BDNF decreases after chronic methylphenidate in ADHD-PI, but not ADHD-C. Conflicting findings exist on methylphenidate’s BDNF effects, so the significance of this finding is unclear [178].
Lisdexamfetamine, a D-amphetamine prodrug, effectively reduced ADHD symptoms in adults with ADHD-C, ADHD-HI, and ADHD-PI [179], with no subtype-specific clinical response differences, similar to methylphenidate findings in adults. Small ADHD-HI subgroup size is a caveat of this study [179].
Atomoxetine, a non-stimulant, has moderate overall effect size in ADHD. Placebo-controlled trials in adults and young adults with ADHD, including those with comorbid social anxiety or alcohol use disorders, showed similar ADHD symptom reduction in ADHD-PI and ADHD-HI [180]. Guanfacine, another non-stimulant, reduced ADHD symptoms across subtypes in youths (6–17 years) [181]. ADHD-C youths showed greater placebo-adjusted improvements than ADHD-PI, possibly due to baseline symptom differences [181].
Overall, stimulant and non-stimulant ADHD treatment responses seem similar across ADHD presentations [182,183,184]. Interestingly, a metadoxine trial reported efficacy and tolerability in treating adult ADHD, with greater efficacy in ADHD-PI than ADHD-HI [185]. Metadoxine is a non-stimulant under investigation for ADHD [185]. Subtype-specific metadoxine effects need replication in larger studies, especially in children and youths. Including females with ADHD-PI in future pharmacotherapy studies is crucial due to high ADHD-PI prevalence in females and their more severe academic and social impairments compared to boys with ADHD-PI [186]. Examining behavioral treatment efficacy alongside pharmacotherapy to assess multimodal treatment utility for ADHD-PI is also important.
9. Animal Models for ADHD-PI Translational Research
Animal models are vital for understanding disease mechanisms and treatment effects. While not perfectly mimicking human psychiatric disorders, they provide controlled experimental setups for studying neurobiology, neuropathology, and chronic drug treatment effects in ways impossible in human studies [187,188]. ADHD research has benefited from animal models.
Sagvolden et al. first proposed the adolescent Wistar Kyoto WKY/NCrl substrain (Charles River, Germany) as an ADHD-PI model, using Wistar Kyoto rat or WKY/NHsd (Harlan, UK) as controls (reviewed in [29]). Specifying subline codes and origin is crucial for result consistency and interpretation [29]. WKY/NCrl is genetically diverse from WKY/NHsd, with upregulated genes including tyrosine hydroxylase (TH), DAT1, and SLC9a9 (NHE9) [189,190]. Behaviorally, WKY/NCrl showed inattention without overactivity or impulsivity in visual discrimination tasks compared to WKY/NHsd [191]. Spontaneously hypertensive rat (SHR)/NCrl (Charles River, Germany) showed all ADHD-like behaviors [191]. SHR/NCrl characterization led to its recognition as the best-validated ADHD-C animal model compared to WKY/NHsd (reviewed in [29]). Several studies show inattentive-like behavior in WKY/NCrl and SHR/NCrl compared to outbred Sprague Dawley (SD) and Wistar/HanTac strains (Taconic Europe) [192,193,194]. However, SD and Wistar/HanTac are discouraged as controls due to genetic/behavioral differences from WKY/NHsd [29,195]. Their use could avoid confusion from using WKY as a control [196] or represent “normal” heterogeneous populations [197,198]. Studies found WKY/NCrl more inattentive than SHR/NCrl [197] in Y-maze tasks measuring attention-dependent spontaneous alternation. Both WKY/NCrl and SHR/NCrl showed inattentiveness compared to outbred Wistar rats (Charles River). Behavioral tools for measuring animal attention have limitations [199], as attention is multidimensional [200]. Further studies are needed to validate WKY/NCrl inattentive-like behavior using more sophisticated paradigms (e.g., five-choice serial reaction time task, CPT) [201] and confirm its validity as an ADHD-PI model, using appropriate controls including “heterogeneous” strains for accurate interpretations and reproducibility.
Roessner et al. [195] examined dopaminergic neurotransmission in WKY/NCrl, finding increased DAT and TH gene expression in substantia nigra (SN) or ventral tegmental area (VTA) of WKY/NCrl and SHR/NCrl compared to WKY/NHsd, indicating elevated dopamine synthesis and reuptake in these strains. However, unlike SHR/NCrl, dopamine breakdown wasn’t accelerated, and excitatory DRD1 drive to SN/VTA wasn’t increased in WKY/NCrl [195]. Striatal DAT density was increased in both strains, but more in SHR/NCrl than WKY/NCrl. Elevated DAT density is linked to impulsivity [202], more prominent in ADHD-C, potentially explaining behavioral differences between WKY/NCrl and SHR/NCrl. Roessner et al. [195] also found decreased striatal DAT binding with age in WKY/NCrl and SHR/NCrl, potentially explaining hyperactivity/impulsivity symptom decline with age [14,195]. Miller et al. [203] also showed differences in dopamine release and uptake regulation in striatum and nucleus accumbens between WKY/NCrl, SHR/NCrl, and controls WKY/NHsd and SD. WKY/NCrl showed faster dopamine uptake in nucleus accumbens versus SD control, while SHR/NCrl had faster uptake in ventral striatum and nucleus accumbens versus WKY/NHsd and SD [203]. These differences could underlie behavioral distinctions between ADHD animal models and controls.
Franke et al. suggested involvement of basic neuronal processes in ADHD [150,170]. Studies found WKY/NCrl and SHR/NCrl showed prefrontal cortical expression alterations in genes related to transcription (Creg1, Thrsp, Zeb2), synaptic transmission (Atp2b2, Syt12, Chrna5), neurological system processes (Atg7, Cacnb4, Grin3a), and immune response (Atg7, Ip6k2, Mx2) compared to Wistar controls [197]. Overexpression of thyroid hormone-responsive (Thrsp) gene in mouse striatum induced inattention in novel object recognition and Y-maze tasks [204], also altering striatal dopamine-related gene expression [204]. Translational value for ADHD-PI needs further study.
Stimulus control differences between WKY/NCrl and SHR/NCrl support proposed inattention profile differences between ADHD-C and ADHD-PI [205]. WKY/NCrl behavior wasn’t cue-light controlled, similar to passive, orientation, alertness, and sensory processing deficits in human ADHD-PI [205].
These findings highlight WKY/NCrl’s potential as an ADHD-PI animal model. Further behavioral, genetic, and neurobiological characterization and ADHD treatment effect studies are needed to verify predictive validity. Including female WKY/NCrl animals is crucial for face validity. WKY/NCrl has also been used for depression and anxiety models [206,207], allowing study of neurobiological correlates of ADHD-PI, anxiety, and depression comorbidity.
10. Research Domain Criteria (RDoC) for ADHD Neurobiology
DSM-5 and ICD-11’s categorical ADHD diagnosis is criticized for not reflecting the dimensional view of ADHD, where ADHD is seen as the extreme end of a continuum, differing in degree, not kind [4]. The Research Domain Criteria (RDoC) framework by the National Institute of Mental Health offers an alternative [208]. RDoC aims to understand mental health and illness as varying degrees of dysfunction in psychological/biological systems [209] and to identify neural circuitry underlying typical and atypical behaviors to improve diagnosis, treatment, and prevention [208,210]. RDoC initially links symptoms across diagnoses, including healthy controls, with endophenotypes to identify etiologies [211]. In RDoC, individual ADHD symptoms may have different causes and mechanisms, potentially resembling neurobiological underpinnings in other neurodevelopmental/neuropsychiatric disorders or typical development (e.g., executive dysfunction in ADHD and autism, hyperactivity/impulsivity in ADHD and typical children) [212,213]. ADHD presentations may not be distinct subtypes, but rather individual symptoms with different neurobiological bases. Genomics findings show shared genetic vulnerability across psychiatric disorders [214]. RDoC suggests the same treatment may target the same symptom across conditions [213]. RDoC is being applied to ADHD research and related behaviors like conduct problems [215], working memory, and reward processing deficits [216], showing promise, but its long-term advantages and disadvantages are still emerging.
11. Conclusions
ADHD-PI, a prevalent but under-recognized presentation, with persistent inattentive symptoms, requires further research into its neurobiological basis and the inattention symptom itself. Progress has been made, particularly in neuroimaging, but clinical implications are limited by methodological issues and small sample sizes [4]. With increasing acceptance of the dimensional view of ADHD, adopting new strategies like the RDoC framework is crucial for studying psychiatric disorder pathophysiology. RDoC application to ADHD has shown advancements and challenges [4,215,216,217,218]. Integrating RDoC with developmental psychopathology is proposed to better understand ADHD symptom development and determinants [216].
Translational ADHD-PI research is still developing. The WKY/NCrl model requires further characterization to validate it as a reliable ADHD-PI model [219]. Accurately modeling different ADHD presentations in animals is crucial for understanding neurobiology and preclinical subtype-specific treatment investigations. This is challenging, especially within the RDoC context, given the complexity of cognitive domains and human disorder development and psychosocial influences [220].
Supplementary Materials
The following are available online at https://www.mdpi.com/2076-3425/10/5/292/s1, Table S1: Systematic search process and terms for study questions.
Click here for additional data file. (132.7KB, pdf)
Author Contributions
Conceptualization, I.C.d.l.P.; Writing, I.C.d.l.P. and M.C.P.; Data curation and analysis, I.C.d.l.P., M.C.P., C.G.T. and T.A.; Review and editing, I.C.d.l.P., M.C.P., C.G.T. and T.A. All authors have read and agreed to the published version of the manuscript.
Funding
This research received no external funding and the APC was funded by the Loma Linda University School of Pharmacy.
Conflicts of Interest
The authors declare no conflict of interest.
References
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Click here for additional data file. (132.7KB, pdf)
Alt texts for images:
- Alt: Table outlining the DSM-5 diagnostic criteria for Attention-Deficit/Hyperactivity Disorder (ADHD), detailing Criterion A for inattention and hyperactivity-impulsivity, Criterion B for age of onset, Criterion C for multi-setting presence, Criterion D for functional interference, and Criterion E for exclusion of other disorders, along with specifications for presentation, remission, and severity.
- Alt: Graphical representation of the DSM-5 criteria for ADHD, visually summarizing the diagnostic requirements for inattention and hyperactivity-impulsivity, and specifying the different presentations including combined, predominantly inattentive, and predominantly hyperactive/impulsive types.
