Toward Precision Neuropsychiatry of Dementia: Neuropsychiatric Symptoms as Multidimensional Clinical Phenotypes

ABSTRACT

Neuropsychiatric symptoms (NPS) are the most clinically consequential manifestations of dementia, yet they are frequently underestimated as secondary behavioural complications. This review introduces a precision neuropsychiatry framework that conceptualises NPS—including apathy, agitation, psychosis, depression, and sleep disturbances—as multidimensional clinical phenotypes. These phenotypes bridge neurodegeneration, biological aging, brain network disruption, psychosocial context, functional decline, and caregiver burden. We trace the conceptual evolution from dementia to neurocognitive disorders, and from behavioural and psychological symptoms of dementia (BPSD) to NPS and mild behavioural impairment (MBI). Precision neuropsychiatry stratifies NPS based on disease background, clinical stage, neural networks, biological aging, physical vulnerability, and psychosocial context to optimise differential diagnosis, prognostic prediction, and targeted interventions. Although conventional symptom‐based classification remains practically useful, it must be complemented by biological, functional, and contextual stratification; identical symptom labels often arise from distinct mechanisms and express differently based on personality, life history, environmental mismatch, and available resources. Emerging evidence from MBI, neuroimaging, brain‐age paradigms, frailty, neuroinflammation, Alzheimer's disease (AD) biomarkers, and international consensus criteria supports this multidimensional shift. Future research should advance from cross‐sectional symptom descriptions toward longitudinal, mechanism‐informed, and context‐sensitive models to translate these findings into real‐world psychogeriatric care.

1. Introduction

The term “dementia” has served for over a century to label acquired, progressive cognitive decline that impairs daily independence. It effectively communicates the clinical realities of Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), Lewy body disease (LBD), and vascular cognitive impairment. However, this traditional construct historically overemphasises memory deficits, frequently relegating behavioural and emotional symptoms to secondary complications rather than recognising them as core manifestations.

While the DSM‐5 reframed dementia as major or mild neurocognitive disorders to accommodate etiological heterogeneity and early symptomatic states, this terminology still centers on cognition [1]. Consequently, it fails to explain why patients and caregivers experience neuropsychiatric symptoms (NPS) as the most disruptive disease aspects. Symptoms such as apathy, agitation, psychosis, depression, anxiety, irritability, sleep disturbances, and eating changes strongly influence functional decline, family distress, institutionalisation, and mortality [2, 3, 4, 5]. A clinically viable model must therefore integrate cognition, NPS, functional impairment, and care burden. These symptoms are not merely secondary reactions; they are associated with acute emergency utilisation, prolonged hospitalisation, rapid institutionalisation, and psychotropic prescribing [6, 7, 8, 9, 10].

Historically, the term “behavioral and psychological symptoms of dementia” (BPSD) grouped these non‐cognitive features into a practical, care‐oriented framework [11], and the Neuropsychiatric Inventory (NPI) allowed these symptoms to be measured systematically across dementia syndromes [12]. However, BPSD aggregates phenomenologically diverse symptoms with heterogeneous etiologies and is less suitable for describing disease‐specific behavioural changes, especially in early stages. Conversely, the term “NPS” emphasises direct links to neurodegenerative biology, neural network dysfunction, and somatic vulnerability within a biopsychosocial framework.

This review argues for reframing NPS as multidimensional clinical phenotypes connecting dementia biology, biological aging, network disruption, psychosocial context, and real‐world care outcomes. We define precision neuropsychiatry as an approach that stratifies NPS across these layers to enhance differential diagnosis, prognostic accuracy, and therapeutic selection. In this review, precision neuropsychiatry is used in a pragmatic and clinically grounded sense. It does not refer only to genomics or biomarker‐driven medicine, but to the stratification of NPS by integrating symptom profiles, disease background, clinical stage, physical vulnerability, psychosocial context, care environment, and treatment response. The proposed framework is not intended as an alternative to the biopsychosocial model. Rather, it operationalizes that model for dementia‐related NPS by linking disease aetiology and clinical stage, network‐level expression, individual biological and physical vulnerability, modifiable psychosocial and care‐context factors, real‐world outcomes, and treatment‐response stratification.

Recent perspectives have summarised the historical development, measurement, and treatment pipeline of NPS in AD [13]. The present review extends this discussion by proposing a dementia‐wide precision neuropsychiatry framework that integrates biological aging, brain networks, psychosocial and care‐context factors, real‐world outcomes, and treatment‐response stratification across neurocognitive disorders.

Four core developments drive this paradigm: first, biomarker‐based frameworks for AD enable highly precise biological definition and staging [14, 15]; second, the concept of mild behavioural impairment (MBI) positions later‐life emergent behavioural shifts as early markers of neurodegeneration [16, 17, 18]; third, advances in neuroimaging, neuroinflammation, brain‐age estimation, and frailty indices reveal measurable biological correlates of behaviour, despite current translation hurdles [19, 20, 21, 22, 23, 24]; and fourth, the operationalization of specific syndromes, such as agitation, through international consensus criteria provides clear clinical and trial endpoints [25, 26, 27, 28, 29]. Rather than reducing complex behaviours entirely to neurodegeneration, this multi‐layered framework positions neurological disease and biological aging as sources of structural and functional vulnerabilities, while psychosocial and environmental factors modulate how these vulnerabilities are expressed, perceived, sustained, and treated.

Early consideration of a precision approach to NPS is therefore needed for two reasons. Cross‐sectionally, NPS arise from multiple interacting biological, psychological, physical, and care‐context factors, and their mechanisms are often complex rather than reducible to a single disease process. Longitudinally, earlier and more precise stratification of NPS may help improve patient prognosis, identify unmet needs, reduce caregiver burden, and guide interventions that are meaningful to patients, families, and care systems. Figure 1 provides the conceptual entry point of this review.

FIGURE 1.

Conceptual shift from a cognition‐oriented model to a multidimensional functional impact model. This figure contrasts a traditional model, in which cognitive symptoms are viewed as the primary driver of functional impairment, with a multidimensional model, in which cognitive symptoms, NPS, movement disorders, and autonomic symptoms jointly contribute to functional impairment. The overlaps in this schematic represent partial clinical co‐occurrence and shared impact on function, rather than strict equivalence or shared pathophysiology. ANS, autonomic symptoms; BPSD, behavioural and psychological symptoms of dementia; NPS, neuropsychiatric symptoms.

2. Conceptual Foundations of Precision Neuropsychiatry

2.1. Changes in Terminology From BPSD to NPS and MBI

BPSD remains an essential clinical language for managing immediate care, guiding environmental modifications, caregiver education, non‐pharmacological protocols, and cautious prescribing. In contrast, NPS provides a disease‐oriented framework to link behavioural and psychiatric sleep–wake disturbances to neural pathways, biomarkers, and treatment responses. These frameworks are complementary, not competitive.

The concept of MBI extends this neuropsychiatric lens into pre‐dementia stages. Many older adults exhibit later‐life emergent changes across the five MBI domains: decreased motivation, affective dysregulation, impulse dyscontrol, social inappropriateness, and abnormal perception or thought content, including psychotic symptoms, before cognitive decline warrants a dementia diagnosis. MBI is defined by later‐life emergent and persistent NPS that represent a change from an individual's longstanding pattern of behaviour or personality. Although such changes may historically have been attributed to primary psychiatric disorders or personality change, longitudinal and clinicopathological data suggest that MBI may represent an early clinical manifestation of underlying neurodegeneration [16, 17, 18].

In a precision neuropsychiatry framework, BPSD captures real‐world care challenges, NPS links symptoms to brain biology, and MBI identifies early risk before overt cognitive failure. Recognising these states as meaningful phenotypes—rather than mere secondary reactions—is vital for early diagnosis, prognosis, and tailored intervention planning.

2.2. From Symptom‐Based Classification to Mechanism‐Informed Phenotyping

Current practice classifies NPS by observable behavioural clusters: apathy, agitation, depression, psychosis, anxiety, disinhibition, or sleep disturbances. While practical for communication, this cross‐sectional approach may obscure biological and psychosocial heterogeneity. Identical clinical labels may reflect different underlying mechanisms. For example, apathy can stem from frontostriatal network degeneration, major depression, vascular injury, frailty, or environmental deprivation. Agitation may reflect occult pain, delirium, sleep–wake inversion, psychotic features, or caregiver‐patient mismatch. Delusions occur across AD, dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD), but their management and genetic underpinnings differ markedly.

Attempts to cluster NPI domains provide an important intermediate step between simple symptom lists and mechanism‐informed phenotyping. Previous studies have shown that NPI symptoms tend to co‐occur as subsyndromes, such as affective, psychotic, apathy‐related, and hyperactivity‐related clusters [30, 31]. More recent multilevel factor analytic work has further distinguished between subsyndromes representing between‐person BPSD profiles and symptom clusters representing within‐person daily symptom experiences [32]. These approaches are useful because they move NPS assessment beyond isolated symptom labels and capture clinically meaningful patterns of co‐occurring symptoms. More recent work has also linked NPS subsyndromes to functional connectivity patterns and dementia subtypes, suggesting that symptom clusters may provide a bridge between clinical phenomenology and brain network models [19]. However, NPI‐derived clusters are statistical groupings and do not by themselves establish shared pathophysiology or treatment response. They should therefore be viewed as an intermediate layer that supports, but does not replace, disease‐, network‐, biological‐, and context‐informed phenotyping. This limitation is particularly salient in young‐onset dementia and FTD. Early‐onset dementia is prevalent in specialised memory clinics, displaying unique clinical characteristics and etiological distributions compared to late‐onset cases [33]. Psychiatric profiles vary significantly between early‐ and late‐onset FTD [34], and psychotic symptoms—once considered rare—are highly relevant in specific genetic variants [35]. Clinicopathological evaluations of C9ORF72‐associated FTD presenting with delusions emphasise the necessity of interpreting psychosis within precise genetic and neurodegenerative contexts [36]. Furthermore, community clinicians frequently over‐diagnose behavioural variant FTD (bvFTD) by focusing on superficial behavioural symptoms without adhering strictly to diagnostic criteria or incorporating specialist differential assessments [37].

Symptoms are important for diagnosis; however, they do not necessarily indicate underlying mechanisms. Delusions may indicate AD‐associated psychosis, LBD, C9ORF72 mutations, late‐onset schizophrenia‐like states, or acute delirium. Consequently, precise diagnosis requires interpreting these behaviours alongside cognitive trajectories, neurological signs, structural and functional neuroimaging, and fluid or molecular biomarkers [38, 39].

Precision neuropsychiatry therefore transitions from symptom‐based classification to mechanism‐informed phenotyping. This approach addresses four fundamental clinical questions: First, what specific symptom phenotype is present, and how is it precisely quantified? Second, in what neurodegenerative disease context and clinical stage does it manifest? Third, which biological, network, somatic, or psychosocial mechanisms may contribute to the phenotype? Fourth, what outcome does this phenotype predict, and what specific intervention target does it reveal? This layered phenotyping enhances the utility of conventional tools. Apathy should be characterized by its onset, relationship to mood, motor features, and reward sensitivity. Agitation requires mapping against precipitating triggers, temporal patterns, pain indices, and sleep architecture. Psychosis should be evaluated alongside sensory deficits, cognitive fluctuations, extrapyramidal signs, and disease‐specific biomarkers. Mechanism‐informed phenotyping may help shift interventions from symptomatic management toward targeted problem solving. Table 1 summarises the main stratification domains, key assessments, and clinical implications for common NPS phenotypes.

TABLE 1.

Stratification domains for major neuropsychiatric symptoms in dementia.

Symptom phenotype	Main stratification domains	Key assessments	Clinical implication
Apathy	Frontostriatal/salience network dysfunction; depression; frailty; social isolation; reduced meaningful activity	NPI/NPI‐C; depression scales; ADL/IADL; frailty assessment; pre‐dementia scales when relevant	Distinguish motivational‐network dysfunction from depression, frailty, or environmental deprivation.
Agitation	Pain; delirium; sleep disturbance; psychosis; anxiety; environmental overstimulation; communication failure	NPI/NPI‐C; pain assessment; delirium screening; sleep assessment; medication and environment review	Identify reversible triggers and safety risks before pharmacotherapy; match intervention to the dominant contributor.
Psychosis	AD psychosis; DLB; C9ORF72‐associated FTD; sensory impairment; delirium; medication effects; social isolation	NPI/NPI‐C; sensory assessment; DLB‐related markers; cognitive fluctuation assessment; medication review	Clarify disease context and modifiable contributors; use antipsychotics cautiously, especially when DLB is possible.
Depression/anxiety	Mood disorder; vascular or medical burden; sleep disturbance; inflammation; bereavement; loneliness; psychosocial stress	Mood and anxiety scales; sleep assessment; medical review; psychosocial assessment	Separate primary mood symptoms from dementia‐related, medical, sleep‐related, or contextual contributors.
Disinhibition	Orbitofrontal dysfunction; bvFTD; impulse dyscontrol; reduced social cognition; environmental triggers	NPI/NPI‐C; caregiver report; social cognition assessment; pre‐dementia scales when relevant	Distinguish bvFTD‐related disinhibition from modifiable contextual triggers and unsafe behavioural patterns.
Sleep disturbance	Circadian dysregulation; neurodegeneration; pain; mood symptoms; medication effects; environmental disruption	Sleep history; caregiver sleep report; NPI night‐time behaviour; actigraphy when available; medication review	Treat sleep, pain, medication, mood, and environmental contributors; consider caregiver sleep burden.

Note: Candidate mechanisms listed in this table do not imply established causality. They represent clinically plausible stratification domains that require different levels of empirical support and should be interpreted together with disease stage, physical health, psychosocial context, and care setting.

Abbreviations: AD, Alzheimer's disease; ADL, activities of daily living; bvFTD, behavioural variant frontotemporal dementia; DLB, dementia with Lewy bodies; FTD, frontotemporal dementia; IADL, instrumental activities of daily living; NPI, Neuropsychiatric Inventory; NPI‐C, Neuropsychiatric Inventory‐Clinician rating scale; NPS, neuropsychiatric symptoms.

3. Multilayer Contributors to NPS Phenotypes

3.1. Biological Aging and individual Vulnerability

While chronological age is the strongest risk factor for dementia, it serves as an imprecise proxy for biological vulnerability. Patients with identical diagnoses and cognitive scores often exhibit vastly different neuropsychiatric trajectories and caregiver burdens, highlighting the influence of underlying biological aging.

This framework incorporates three distinct vulnerability layers. First, neuroimaging‐derived vulnerability: Higher brain age—estimated via machine learning on structural MRI—is associated with severe depressive and apathetic symptoms in MCI and early dementia [20]. While not establishing causality, accelerated brain aging represents a candidate vulnerability marker for specific NPS, though neuroimaging correlates remain heterogeneous and require rigorous validation [21]. Second, molecular and epigenetic vulnerability: Rather than relying solely on global epigenetic clocks [23], direct evidence links specific behaviours to symptom‐linked DNA methylation changes. For instance, reduced blood DNA methylation in the WNT5A gene promoter region has been associated with agitation phenotypes in dementia, suggesting a possible link with Wnt signalling pathways [40]. Third, geriatric and physical vulnerability: physical frailty is longitudinally associated with depression, anxiety, and apathy in cognitive disorders, likely mediated by shared pathways of brain atrophy, chronic neuroinflammation, and peripheral immune dysregulation [24]. Frailty, sensory deprivation, and multimorbidity may interact with neurodegeneration and amplify motivational and affective deficits. In summary, geriatric and physical vulnerability may contribute to depression, anxiety, and apathy in cognitive disorders, alongside disease‐specific effects.

Crucially, these imaging, molecular, and somatic markers are currently candidate stratification tools rather than actionable clinical biomarkers. Their immediate value lies in research—explaining clinical heterogeneity and generating testable stratification models. Translating these markers into routine practice requires validation across large, longitudinal, and ethnically diverse cohorts to account for biological noise and ensure clinical reproducibility. None of these markers should currently be used to classify or treat individual patients. Their value lies in generating hypotheses and identifying vulnerability patterns that require validation in longitudinal and intervention studies.

3.2. Brain Network Models of NPS

Disease biology and brain networks are separated analytically because they represent different levels of explanation. Disease biology refers to underlying etiological and pathological processes, whereas brain networks refer to the structural and functional systems through which these processes may be expressed as NPS. These levels are interdependent rather than independent: disease pathology may disrupt brain networks, while similar network disturbances may arise across different diseases. Their clinical expression may also be modified by biological aging, physical health, and psychosocial context.

Neuroimaging techniques—including structural MRI, SPECT, FDG‐PET, amyloid/tau PET, fMRI and diffusion imaging—demonstrate that NPS reflect network‐level disruptions rather than single‐region pathology [19, 21, 22]. These context‐dependent, fluctuating clinical expressions involve complex interactions across frontal, temporal, limbic, striatal, default mode, salience, and sensorimotor networks.

Network models avoid oversimplified localization. Apathy reflects disruption within motivation, reward, and frontostriatal‐salience circuits. Agitation involves dysregulation of emotional salience, threat perception, and circadian pacemakers. Psychosis arises from altered connectivity in networks governing reality monitoring and salience assignment. Mood symptoms reflect disrupted limbic‐prefrontal regulation interacting with somatic frailty and psychosocial stress. This network perspective integrates disease‐specific features: the early disinhibition and loss of empathy characteristic of bvFTD map to anterior insular and anterior cingulate salience network hubs [38]; the visual hallucinations and cognitive fluctuations of DLB correlate with frontoparietal and visual network instability [39]; and the emergent agitation of AD reflects tau propagation through limbic and temporoparietal nodes [41].

Rather than deterministic maps, network models provide testable hypotheses to distinguish clinically actionable subgroups. An agitation phenotype driven by sleep–wake network desynchronization requires entirely different management compared to agitation driven by psychotic‐network disruption or acute pain networks. Network modelling is valuable only when it delineates these distinct therapeutic pathways.

3.3. Physical and Medical Contributors

Physical and medical factors can precipitate, amplify, or maintain NPS independently of, or in interaction with, neurodegenerative pathology. Pain, sleep disturbance, sensory impairment, infection, delirium, medication adverse effects, and multimorbidity should therefore be assessed systematically before symptoms are attributed to dementia itself. These contributors are clinically important because many are potentially reversible and may alter both symptom expression and treatment tolerability.

3.4. Psychosocial and Care‐Context Factors

Neurodegeneration and biological aging create structural and functional vulnerability, whereas psychosocial and care‐context factors modulate how this vulnerability is expressed, sustained, and perceived. Premorbid personality, life history, communication patterns, environmental overstimulation, social isolation, and caregiver resources are direct moderators of symptom expression and key therapeutic targets. For instance, a patient with AD‐related network vulnerability may remain behaviorally stable in a structured, predictable environment but develop severe agitation when exposed to sensory overstimulation, unfamiliar staff, or communication failure. Similarly, apathy‐related disability amplifies when social stimulation and structured activities are absent, while psychotic distress worsens under conditions of sensory isolation or nighttime disorientation.

Consequently, treatment should integrate biological, physical, medical, and psychosocial strategies. After systematic assessment of physical and medical contributors, individualised care algorithms should optimise the physical environment, support caregiver communication and education, and use targeted pharmacotherapy only when safety is compromised. Academic research should measure contextual variables directly—including caregiver distress scales and environmental predictability indices—to avoid overattributing symptoms solely to neurodegeneration.

4. Clinical and Translational Implications

4.1. From NPS Phenotypes to Real‐World Care Outcomes

NPS are functionally consequential clinical features associated with decline in activities of daily living (ADL), caregiver burden, emergency service utilisation, institutionalisation, and psychotropic prescribing [6, 7, 8, 9, 10, 42, 43, 44, 45, 46]. Their importance is determined by their real‐world consequences rather than scale scores alone. International data confirm that specific NPS domains are strongly linked to caregiver depression and primary care burden [45, 46]. In Japan, community‐based and web‐based data show that caregiver burden and quality of life are heavily influenced by the specific qualitative profile of NPS rather than simple symptom frequency or severity [6, 43, 44]. Different NPS domains may have different outcome profiles: agitation and psychosis are more likely to trigger urgent safety concerns and psychotropic prescribing, whereas apathy and sleep disturbance may contribute more gradually to inactivity, caregiver exhaustion, and functional decline.

For young‐onset dementia and FTD, behavioural management dominates care requirements, necessitating robust non‐pharmacological interventions [47, 48]. In AD, longitudinal data confirm that NPS independently accelerate ADL decline, indicating they are functional drivers rather than passive markers of distress [42]. Furthermore, lower educational attainment is associated with distinct NPS subsyndromes in amnestic MCI, suggesting that cognitive reserve modulates behavioural presentation [49]. Precision neuropsychiatry should incorporate these real‐world outcomes into prognostic modelling and clinical trials. An agitation phenotype should be evaluated not merely by a rating scale score, but by its association with acute caregiver distress, injury risks, and imminent service utilisation. Apathy must be evaluated by its capacity to accelerate physical dependency and increase caregiver burnout.

4.2. Agitation as an Illustrative Model for Translational NPS Research

Agitation serves as an illustrative model because its operational criteria, biological correlates, real‐world data, and treatment studies have begun to converge. The International Psychogeriatric Association (IPA) definition and subsequent consensus work clarified the syndrome and linked assessment with non‐pharmacological and cautious pharmacological management [25, 26, 27]. In parallel, brexpiprazole trials and CMAI analyses provide examples of treatment evaluation and clinically meaningful change beyond statistical significance [28, 29, 50].

Biologically, neuroimaging studies link agitation and affective distress across AD, DLB, and MCI to measurable structural and network alterations [51], while aggressive behaviours in early AD correlate with frontal lobe asymmetry, specifically right‐sided atrophy [52]. At the molecular level, lower blood DNA methylation in the WNT5A promoter region has been associated with agitation in dementia [40]. Real‐world practice data bridge these domains: a Japanese web‐based survey of physicians revealed that clinical perceptions and prescribing habits for agitation vary widely by medical specialty, highlighting a clear gap between consensus guidelines and routine practice [53]. Agitation demonstrates how a single behavioural domain can be operationalised across rating scales, network imaging, molecular epigenetics, clinical practices, and targeted therapeutics. Apathy, psychosis, depression, and disinhibition require analogous but symptom‐specific translational pathways to overcome current fragmentation in neuropsychiatric research.

4.3. Clinical Application of the Precision Neuropsychiatry Framework

We propose a multilayered framework in which disease biology and clinical stage influence network‐level expression, while biological aging, physical and medical factors, psychosocial context, and care context interact to shape specific NPS phenotypes. These phenotypes are associated with functional decline and caregiver burden and may guide individualised intervention (Figure 2). This model has six practical implications: first, standardise NPS and caregiver distress tracking using validated tools (NPI, NPI‐C, NPI‐Q) [11, 12, 54, 55]; second, contextualise NPS within specific disease etiologies, stages, and somatic health profiles; third, systematically assess psychosocial and environmental triggers; fourth, differentiate between symptom presence, severity, distress, and functional impact; fifth, define precise behavioural phenotypes for clinical trial enrollment rather than broad diagnostic categories; and sixth, target real‐world outcomes (ADL preservation, caregiver burden, institutionalisation delay) as primary endpoints.

FIGURE 2.

Multilayer contributors to neuropsychiatric symptoms and related outcomes in dementia. This operational stratification framework is built on a biopsychosocial foundation. Disease pathology and aetiology may contribute to neuropsychiatric symptoms (NPS) directly and through network‐level alterations, while biological aging and vulnerability further modify their clinical expression. Physical factors, medical comorbidity, medication effects, psychosocial context, and care context may precipitate, amplify, or maintain NPS. These symptom phenotypes are associated with clinically relevant outcomes, including functional decline, caregiver burden, and health‐care use. The domains shown represent interacting stratification factors rather than independent or deterministic causes.

This framework is also relevant to treatment selection. In current practice, NPS treatment usually begins with guideline‐based assessment, identification of reversible causes, non‐pharmacological intervention, caregiver education, environmental modification, and cautious pharmacotherapy when risk is high. However, when pharmacotherapy is required, commonly used first‐line pharmacological options often provide only modest average benefit and are constrained by adverse events, especially in older patients with dementia [4, 5, 13]. Some patients respond to this approach, whereas others have persistent or treatment‐resistant NPS and need individualised assessment of mechanisms, comorbidity, caregiver context, and treatment response. Urgent symptoms such as severe agitation, psychosis, aggression, delirium‐related behavioural disturbance, or safety‐threatening behaviour require rapid risk assessment and time‐limited intervention. Precision neuropsychiatry should therefore add to, rather than replace, guideline‐based care.

Analyses by the authors using the Clinical Antipsychotic Trials of Intervention Effectiveness‐Alzheimer's Disease (CATIE‐AD) dataset support this treatment‐oriented view. Baseline clinical characteristics and early symptom improvement helped predict antipsychotic continuation and response in AD with psychosis or aggressive symptoms [56, 57]. Neurocognitive preservation was also associated with NPS improvement during treatment, suggesting that disease stage or cognitive reserve may influence benefit [58]. Work on pharmacological treatment‐resistant NPS further emphasises individualised interventions when standard approaches fail [59]. These findings illustrate how precision neuropsychiatry can support response prediction, early treatment adjustment, and individualised risk–benefit decisions.

A practical treatment pathway for NPS can be organised into three grades. The first is standard care based on guidelines and consensus algorithms: structured assessment, identification of reversible contributors, non‐pharmacological intervention, caregiver education, environmental modification, and cautious pharmacotherapy when indicated. The second is individualised care for persistent or treatment‐resistant NPS, using symptom course, early treatment response, cognitive and functional status, comorbidity, caregiver burden, and environmental context to revise the treatment plan. The third is emergency precision triage for high‐risk symptoms. Even when immediate safety and short‐term symptom control are required, clinicians should rapidly screen for reversible and actionable contributors, such as delirium, pain, infection, medication adverse effects, sleep disruption, sensory impairment, and environmental mismatch. Any urgent pharmacological intervention should be time‐limited, repeatedly reviewed, and linked to a mechanism‐informed treatment plan.

In countries like Japan, clinicians possess broad access to structural and nuclear imaging (SPECT, dopamine transporter SPECT, and MIBG scintigraphy), enabling imaging‐informed stratification that reflects specific phenotypic characteristics [39]. However, this approach risks promoting resource‐intensive models that are difficult to implement in general practice. True precision means matching mechanisms to interventions across all resource levels: utilising functional imaging and fluid biomarkers in specialised memory clinics while implementing structured symptom checklists, medication reconciliations, and caregiver training in primary and long‐term care settings.

5. Research Roadmap

The roadmap for precision neuropsychiatry proceeds across four sequential phases:

1. Deep Phenotyping: Cross‐sectional integration of standardised NPS scales with somatic measures (pain, sleep) and digital phenotyping (e.g., wearable actigraphy) to capture real‐time behavioural fluctuations.

2. Longitudinal Prediction: Modelling behavioural phenotypes against clinically important outcomes, including cognitive trajectory, functional loss, conversion rates, and institutionalisation.

3. Treatment Stratification: Evaluating therapeutic responses within mechanistic subgroups, recognising that apathy driven by frontostriatal decay may require different strategies than apathy rooted in depression or frailty.

4. Implementation: Developing practical assessment algorithms, electronic decision‐support systems, and clinical pathways scalable across hospitals, memory clinics, and home‐care settings

Methodological discipline remains paramount: cross‐sectional associations must not be equated with causality; brain age and epigenetic markers must be treated as investigational tools; and biological markers must never strip NPS of their vital psychosocial dimensions. This translational roadmap directly aligns with the Lancet Commission's emphasis on managing dementia through systemic, life‐course approaches [60].

6. Conclusions

NPS are core, functionally consequential features of neurodegenerative diseases. A precision neuropsychiatry framework moves the field beyond descriptive symptom classification toward mechanism‐informed stratification and individualised care. Precision in this context should be understood as clinically meaningful stratification rather than genetic or biomarker determinism. The immediate task is to construct reproducible models that synthesise behavioural phenotypes, biomarkers, network disruptions, biological aging, somatic vulnerabilities, and real‐world caregiver interactions. This approach aims to improve the lives of patients, their families, and the care systems supporting them.

Funding

This work was supported by the JSPS KAKENHI Grant Number 24K10690 and AMED under Grant Numbers JP24wm0625505.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

Data sharing is not applicable to this article as no new data were created or analysed in this review.