Psychopathology and comorbidities

Mental disorders are not distinct entities with entirely separate mechanisms but rather reflect and exhibit a mix of disorder-specific and transdiagnostic factors, and this includes addictions. While psychopathology has long been the foundation of psychiatric diagnosis, addictions have historically received less attention in psychopathological frameworks compared to disorders such as depression or schizophrenia. However, growing evidence suggests significant overlap in symptoms, diagnoses, and underlying mechanisms across psychiatric conditions.

Several studies have identified shared psychopathological features between addictions and other mental disorders:

Mood disorders: Conway et al. (Reference Conway, Compton, Stinson and Grant2006) highlighted high comorbidity rates between addictions and mood disorders. These comorbidities have been explored through a psychological framework, with dependence, craving, negative reinforcement, and rumination having emerged as important common factors (Delgadillo et al. Reference Delgadillo, Böhnke, Hughes and Gilbody2016). Common underlying factors between bipolar and substance use disorders have also been proposed, including impulsivity, disrupted modulation of motivation and responses to rewards, and vulnerability to behavioral sensitization (Swann Reference Swann2010).

Anxiety disorders: Conway et al. (Reference Conway, Compton, Stinson and Grant2006) also characterized the high comorbidity between addictions and anxiety disorders, in addition to mood disorders, with a similar psychological framework and common underlying factors. Similar in Vorspan et al.’s (Reference Vorspan, Mehtelli, Dupuy, Bloch and Lépine2015) review, the authors identify a high prevalence of substance use and misuse associated with anxiety disorders. There is evidence that this link is both driven by a acute anxiety reduction as a motive for use (i.e. the self-medication hypothesis) and by longer term substance-induced increased anxiety symptoms. There is high co-occurrence across many anxiety disorders and substance classes, and the authors emphasize that concurrent disorders must be addressed in conjunction.

Post-traumatic stress disorder (PTSD): McCauley et al. (Reference McCauley, Killeen, Gros, Brady and Back2012) have summarized explanations for the high co-occurrence observed between PTSD and substance use disorders, including the self-medication hypothesis (substance use is used to acutely alleviate PTSD symptoms), the high-risk hypothesis (propensity to be in high-risk situations underlies substance use and exposure to traumatic events), and the susceptibility hypothesis (underlying anxiety that accompanies addiction increases biological vulnerability to developing PTSD after trauma exposure).

Schizophrenia: Mueser et al. (Reference Mueser, Bellack and Blanchard1992) examined the intersection of schizophrenia and substance abuse, noting overlap in the transient psychotic symptoms caused by substance use and the psychotic symptoms seen in schizophrenia, such as paranoia and hallucinations, as well as in cognitive deficits. These overlapping features have been hypothesized to stem from common underlying vulnerabilities (Volkow Reference Volkow2009; Khokhar et al. Reference Khokhar, Dwiel, Henricks, Doucette and Green2018). Furthermore, the concept of “double reality” or “double bookkeeping” observed in schizophrenia may have parallels in addictions-related cognitive distortions (Lam et al. Reference Lam, Froese and Schütz2024).

Personality disorders: Approximately 50% of people with a personality disorder have a comorbid substance use disorder (Köck and Walter Reference Köck and Walter2018). Those diagnosed with antisocial and borderline personality disorders are likely to be at the highest risk, with increased impulsivity (Trull et al. Reference Trull2000; Köck and Walter Reference Köck and Walter2018) and affective instability, as well as potential mechanistic overlap. People with co-occurring personality disorders and substance use disorders also tend to have more severe clinical trajectories than those without concurrent disorders (Köck and Walter Reference Köck and Walter2018).

More recently, there have been emerging efforts to develop a transdiagnostic psychopathology profile of addictions. Using an exploratory principal component factor analysis, Maremmani et al. (Reference Maremmani, Pani, Rovai, Bacciardi and Maremmani2017) found five factors to describe a specific psychopathology of substance use disorders: depressive, somatic, sensitivity-psychoticism, panic-anxiety, and violence-suicide dimensions.

Data-driven hierarchical models have also been developed to map transdiagnostic dimensions of psychopathology. Caspi et al. (Reference Caspi, Houts, Belsky, Goldman-Mellor, Harrington and Israel2014) proposed a model identifying three core clusters – internalization, externalization, and cognitive dysfunction – with an additional higher-order p-factor representing general psychopathology underlying all mental disorders. Caspi et al.’s (Reference Caspi, Houts, Belsky, Goldman-Mellor, Harrington and Israel2014) study, addictions mapped onto the externalizing factor. Similarly, the Hierarchical Taxonomy of Psychopathology (HiTOP; Kotov et al. Reference Kotov, Krueger, Watson, Achenbach, Althoff and Bagby2017, Reference Kotov, Cicero, Conway, DeYoung, Dombrovski and Eaton2022) framework has been proposed as an alternative to traditional categorical classifications, aiming to capture the dimensional structure of mental disorders, including addictions conceptualized under the externalizing superspectrum (Eaton et al. Reference Eaton, Rodriguez-Seijas, Carragher and Krueger2015).

Genetics: the same genetic risk factors can contribute to both addictions and other mental disorders

Shared genetic risk factors contribute to addictions and other mental disorders. Twin and family studies consistently indicate high heritability estimates across psychiatric conditions, including addictions (Pettersson et al. Reference Pettersson, Larsson and Lichtenstein2016; Deak and Johnson Reference Deak and Johnson2021; Uher and Zwicker Reference Uher and Zwicker2017). One of the largest studies (Pettersson et al. Reference Pettersson, Larsson and Lichtenstein2016), analyzing 3.5 million individuals, delineated general, psychosis-related, non-psychosis-related, and disorder-specific heritability components, alongside shared and non-shared environmental influences. Notably, schizophrenia, schizoaffective disorder, and drug use disorders shared approximately 30% of their heritability, while alcohol use disorder and bipolar disorder shared ∼20%, and a general heritability factor was present across all disorders (∼10%). In contrast, there is little to no shared heritability observed with neurological disorders. Individually, heritability estimates were highest for schizophrenia and drug use disorders (∼80%) and lowest for major depressive disorder (MDD; <30%). This is consistent with other heritability estimates (Uher et al. Reference Uher and Zwicker2017; Nurnberger et al. Reference Nurnberger, Berrettini, Niculescu, Fatemi and Clayton2016; Baselmans et al. Reference Baselmans, Yengo, van Rheenen and Wray2021). However, when considering molecular genetic markers (e.g. polymorphisms), the explained heritability drops to 30% or less for schizophrenia and SUDs and below 5% for MDD – this has been called the “heritability gap” (Uher et al. Reference Uher and Zwicker2017; Deak and Johnson Reference Deak and Johnson2021). While individual genes have very small effect sizes in explaining specific mental disorders, numerous genes have been implicated in both addictions and other psychiatric disorders. For instance, genes related to neurotransmitters that influence mood, impulsivity, and reward processing, such as COMT, DRD2, ANKK1, MAOA, and SLC6A4 are linked to a variety of mental disorders such as schizophrenia, bipolar disorder, depression (Nurnberger et al. Reference Nurnberger, Berrettini, Niculescu, Fatemi and Clayton2016), and addictions (Lopez-Leon et al. Reference Lopez-Leon, González-Giraldo, Wegman-Ostrosky and Forero2021). Other genes critical for inhibitory neurotransmission, such as GABRA2, are repeatedly implicated in alcohol dependence and mood and anxiety disorders (Agrawal et al. Reference Agrawal, Verweij, Gillespie, Heath, Lessov-Schlaggar and Martin2012; Engin et al. Reference Engin, Liu and Rudolph2012). Notably, anxiety and mood disorders most frequently co-occur with alcohol use disorders (Baillie et al. Reference Baillie, Pham, Morley, Stapinski, Mills and Marel2021). Additionally, BDNF, a gene critical for synaptic transmission and plasticity, has been linked to most substance addictions (Lopez-Leon et al. Reference Lopez-Leon, González-Giraldo, Wegman-Ostrosky and Forero2021) and mood disorders (Nurnberger et al. Reference Nurnberger, Berrettini, Niculescu, Fatemi and Clayton2016). These findings highlight a substantial genetic overlap between addictions and other psychiatric conditions, yet past research has often examined psychiatric disorders in isolation from addictions (Tsuang et al. Reference Tsuang, Glatt, Faraone, Runge and Patterson2006; Walters et al. Reference Walters, Polimanti, Johnson, McClintick and Adams2018; Kendler Reference Kendler2019). Furthermore, addictive disorders exhibit substantial SNP-based genetic correlations with mental disorders, with magnitudes comparable to those observed among mental disorders themselves. For instance, alcohol dependence shows genetic correlations of 0.46, 0.52, and 0.35 with attention-deficit/hyperactivity disorder (ADHD), MDD, and schizophrenia, respectively – similar to the genetic correlations among these mental disorders (r _g = 0.54 and 0..37; Walters et al. Reference Walters, Polimanti, Johnson, McClintick and Adams2018; Abdellaoui et al. Reference Abdellaoui, Smit, van den Brink, Denys and Verweij2021). ADHD, schizophrenia, and MDD have also been genetically correlated with other addictions, including cocaine (Cabana-Domínguez et al. Reference Cabana-Domínguez, Shivalikanjli, Fernàndez-Castillo and Cormand2019) and nicotine use (Abdellaoui et al. Reference Abdellaoui, Smit, van den Brink, Denys and Verweij2021), and disordered gambling (Piasecki et al. Reference Piasecki, Gizer and Slutske2019). Clearly, substantial genetic correlations exist between addictive and other psychiatric disorders. However, the pleiotropic effects of this genetic overlap remain poorly understood, particularly whether common genes influence multiple disorders or increase susceptibility indirectly to one another. Future research on psychiatric disorders should explicitly incorporate addiction to better explore the mechanisms underlying this genetic overlap and its relationship with transdiagnostic dimensions of psychopathology.

Shared systemic and individual environmental risk factors

Environmental risk factors contribute to both addictions and other mental disorders, interacting with genetic predispositions to shape individual susceptibility. Genetic risks are inherently environment-dependent, and understanding these interactions is crucial for a comprehensive etiological perspective, though they will not be discussed in detail here. While numerous studies have examined the transdiagnostic impact of genetic factors – including addictions – systematic reviews of environmental risk factors from a transdiagnostic perspective remain limited, particularly regarding transdiagnostic approaches between addictions and other mental disorders.

Still, recent research has identified several environmental factors that increase the risk for multiple psychiatric disorders, including addictions. These include psychosocial, familial, and cultural influences. Indicators of socioeconomic status are associated with many mental health disorders (McLaughlin et al. Reference McLaughlin, Costello, Leblanc, Sampson and Kessler2012a), including substance use disorders (Calling et al. Reference Calling, Ohlsson, Sundquist, Sundquist and Kendler2019; McLaughlin et al. Reference McLaughlin, Costello, Leblanc, Sampson and Kessler2012a), schizophrenia (Byrne et al. Reference Byrne, Agerbo, Eaton and Mortensen2004), ADHD (Russell et al. Reference Russell, Ford, Williams and Russell2016), and mood disorders (McLaughlin et al. Reference McLaughlin, Costello, Leblanc, Sampson and Kessler2012a). Again, comorbidities among these disorders, including addictions, are high (McMillan et al. Reference McMillan, Enns, Cox and Sareen2009; Lai et al. Reference Lai, Cleary, Sitharthan and Hunt2015; Capusan et al. Reference Capusan, Bendtsen, Marteinsdottir and Larsson2019). Racial, ethnic, gender, and sexual minorities (among other under-resourced groups) are at increased risk of mental health disorders, including substance use disorders (Lehavot and Simoni Reference Lehavot and Simoni2011; McLaughlin et al. Reference McLaughlin, Greif Green, Gruber, Sampson, Zaslavsky and Kessler2012b; Eaton Reference Eaton2014). According to the minority stress model, this can be attributed to social inequities, discrimination, and more limited accessibility of social protective factors faced by minority groups (Lehavot and Simoni Reference Lehavot and Simoni2011; Frost and Meyer Reference Frost and Meyer2023).

There is growing evidence highlighting the impact of adverse life events, particularly childhood trauma and adult traumatic experiences. For instance, exposure to four or more adverse childhood events (ACEs), as measured by the ACE screener, has been associated with: a fourfold increased risk for MDD, a fourfold increased risk of anxiety disorders, a sixfold increased risk of severe mental disorder, a sixfold increased risk of alcohol use disorder, and a sixfold increased risk of illicit drug use disorder (Anda et al. Reference Anda, Felitti, Bremner, Walker, Whitfield and Perry2006; Daníelsdóttir et al. Reference Daníelsdóttir, Aspelund, Shen, Halldorsdottir, Jakobsdóttir and Song2024). One study (McLaughlin et al. Reference McLaughlin, Greif Green, Gruber, Sampson, Zaslavsky and Kessler2012b) found that ACEs increased overall risk of any psychiatric disorder in adolescents by 30 to 90%, although some disorder- and ACE-specific findings were non-significant. The global population-attributable risk proportion for ACEs across mood, anxiety, behavior, and substance use disorders is estimated to be at 29.8; thus, a reduction in ACEs is estimated to make a substantial positive impact on the prevalence of all of these disorders (Kessler et al. Reference Kessler, McLaughlin, Green, Gruber, Sampson and Zaslavsky2010). However, one umbrella meta-analysis on trauma and transdiagnostic risk for mental health disorders (Hogg et al. Reference Hogg, Gardoki-Souto, Valiente-Gómez, Rosa, Fortea and Radua2023) found no search results for meta-analyses and reviews on substance use disorders after applying their (quite broad) criteria. Evidently, there is a glaring need for quality research integrating trauma, addictions, and their comorbidities. A meta-analysis of parental and offspring psychosis, mood, anxiety, substance use, borderline personality, and ADHD risk found that offspring of parents with any mental health diagnosis have 2.3 times higher risk of a diagnosis themselves, with some variation between diagnoses.

In the context of mental disorder development, including addictions, both genetic predispositions and environmental risk factors influence neurodevelopmental trajectories and neural functioning, shaping vulnerability to psychopathology and neuropathology.

The brain: common structural and functional patterns across diagnoses

Human neuroimaging methods such as magnetic resonance imaging (MRI) and positron emission tomography (PET) have been instrumental in bridging neurobiology and psychiatry. Traditionally, neuroimaging studies have focused on individual diagnoses, often comparing clinical populations to healthy controls. Transdiagnostic neuroimaging research remains limited, often comparing isolated diagnoses and excluding comorbidities. These limitations are likely, at least in part, due to the resource-intensive nature of neuroimaging research and the need for large samples to do transdiagnostic work. However, in the past decade, some large cross-sectional studies, meta-analyses, and reviews have synthesized neuroimaging data across diagnoses or examined neural correlates of p-factor scores, a measure of general psychopathology (Goodkind et al. Reference Goodkind, Eickhoff, Oathes, Jiang, Chang and Jones-Hagata2015; Downar et al. Reference Downar, Blumberger and Daskalakis2016; McTeague et al. Reference McTeague, Huemer, Carreon, Jiang, Eickhoff and Etkin2017, Reference McTeague, Rosenberg, Lopez, Carreon, Huemer and Jiang2020; Vanes and Dolan Reference Vanes and Dolan2021; Yan et al. Reference Yan, Lau, Eickhoff, Long, Song and Wang2022).

While differences across disorders have been identified, commonalities between disorders also exist. One common pattern across disorders is reduced gray matter and aberrant functioning in the bilateral insula and the dorsal anterior cingulate cortex (dACC), typically considered part of the salience network (Goodkind et al. Reference Goodkind, Eickhoff, Oathes, Jiang, Chang and Jones-Hagata2015; Downar et al. Reference Downar, Blumberger and Daskalakis2016; Yan et al. Reference Yan, Lau, Eickhoff, Long, Song and Wang2022). Its extensive connectivity suggests a central role in modulating other networks with widespread functions and, consequently, psychopathology. Unsurprisingly, many subregions of the prefrontal cortex, including those that involve “reward” and “non-reward” processing pathways, are also frequently implicated (Goodkind et al. Reference Goodkind, Eickhoff, Oathes, Jiang, Chang and Jones-Hagata2015; Fettes et al. Reference Fettes, Schulze and Downar2017; McTeague et al. Reference McTeague, Huemer, Carreon, Jiang, Eickhoff and Etkin2017, McTeague et al. Reference McTeague, Rosenberg, Lopez, Carreon, Huemer and Jiang2020; Vanes and Dolan Reference Vanes and Dolan2021). Yan and colleagues’ (Yan et al. Reference Yan, Lau, Eickhoff, Long, Song and Wang2022) meta-analysis of cognitive and MRI, PET, and SPECT studies of inhibitory control identified structural and functional aberrations including the medial right supplementary motor area, parietal cortex, basal ganglia, medial prefrontal cortex, and the right ventrolateral prefrontal cortex alongside the insula. A scoping review of standalone studies and meta-analyses (Vanes and Dolan Reference Vanes and Dolan2021) suggest that the prefrontal cortex, including connectivity with temporo-limbic regions, may indicate early psychopathology risk. Similarly to other studies, the authors suggest that aberrations in the anterior insula and the salience network are consistent between diagnoses.

Overall, these findings suggest, at least to some degree, a common psychoneuropathology. Notably, the regions often identified in these studies are centrally involved in cognitive control/inhibition, reward processing, and executive functioning more broadly (Goodkind et al. Reference Goodkind, Eickhoff, Oathes, Jiang, Chang and Jones-Hagata2015; Yan et al. Reference Yan, Lau, Eickhoff, Long, Song and Wang2022), functions that are negatively impacted among mental health and addictive disorders (Lynch et al. Reference Lynch, Sunderland, Newton and Chapman2021). The convergence observed in these studies underscores the value of neuroimaging in elucidating shared neurobiological mechanisms to shape and improve our diagnostic and treatment approaches. It also firmly establishes addictions within mental health disorders. In turn, backward translation from clinical practice and patient experiences to research design, such as taking a transdiagnostic approach to neurobiological research, is necessary. Understanding these transdiagnostic neural substrates is crucial for integrating genetic, epigenetic, environmental, behavioral, and phenomenological factors in psychiatric research and practice, with the brain serving as a central mediator in these interactions. More research on concurrent diagnoses and further integration of neuroimaging findings with other disciplines of research and with clinical practice is necessary to further guide our theories of mental health and psychiatric diagnoses.

Transdiagnostic approaches to treatment

Traditional psychiatric treatment frameworks emphasize diagnosis-specific interventions. Clinical guidelines recommend treatments based on a specific disorder’s presumed etiology and symptomatology (Stein et al. Reference Stein, Shoptaw, Vigo, Lund, Cuijpers and Bantjes2022). However, psychiatric disorders – including addictions – share common risk factors and have high comorbidity, leading to overlapping various psychiatric interventions being used transdiagnostically beyond their original indications.

Psychotherapy, initially developed for distinct mental disorders, has been successfully adapted for addictions based on shared underlying psychological processes. Dialectical behavior therapy (DBT), originally designed for borderline personality disorder, has been shown to improve emotion regulation and reduce substance use (Cavicchioli et al. Reference Cavicchioli, Movalli, Vassena, Ramella, Prudenziati and Maffei2019). Given the role of emotional dysregulation in both conditions, DBT has been effective for alcohol use disorder and co-occurring addictions. Cognitive behavioral therapy (CBT), widely used for mood and anxiety disorders, has demonstrated efficacy in treating alcohol, stimulant, and opioid use disorders, particularly when combined with pharmacotherapy (Ray et al. Reference Ray, Meredith, Kiluk, Walthers, Carroll and Magill2020; Tran et al. Reference Tran, Luong, Le Minh, Dunne and Baker2021; Van Amsterdam et al. Reference Van Amsterdam, Blanken, Spijkerman, Van Den Brink and Hendriks2022).

Pharmacotherapies originally designed for psychiatric conditions are increasingly being applied to addictions, often targeting overlapping neurobiological pathways. Antipsychotics have been associated with reductions in substance use and cravings in individuals with schizophrenia and comorbid addictions (Krause et al. Reference Krause, Huhn, Schneider-Thoma, Bighelli, Gutsmiedl and Leucht2019). For example, clozapine has been shown to significantly improve abstinence rates and reduce psychiatric hospitalizations in this population (Rafizadeh et al. Reference Rafizadeh, Danilewitz, Bousman, Mathew, White and Bahji2023). Its effects on multiple neurotransmitter systems – including GABA-B, muscarinic, alpha-2 adrenergic, and norepinephrine pathways – may underlie these benefits. Anticonvulsants, primarily used in bipolar disorder, are also being repurposed for addictions. Non-benzodiazepine anticonvulsants such as topiramate, gabapentin, and carbamazepine have demonstrated efficacy in alcohol use disorder (Hammond et al. Reference Hammond, Niciu, Drew and Arias2015). Gabapentin has further shown promise in cannabis use disorder by mitigating withdrawal symptoms and improving cognitive functioning (Mason et al. Reference Mason, Crean, Goodell, Light, Quello and Shadan2012).

Novel and (re-)emerging approaches, such as neurostimulation and psychedelic-assisted therapy, are also showing promise as transdiagnostic treatments. For example, repetitive transcranial magnetic stimulation (rTMS), already approved for depression, reduced cravings in stimulant use disorder (Chang et al. Reference Chang, Liou, Liu, Lu and Chen2022; Gay et al. Reference Gay, Cabe, De Chazeron, Lambert, Defour and Bhoowabul2022). A shared connectivity pattern across addictions involving the dorsal cingulate, lateral prefrontal cortex, and insula may be a common neuromodulatory target (Joutsa et al. Reference Joutsa, Moussawi, Siddiqi, Abdolahi, Drew and Cohen2022). Psilocybin-assisted therapy has yielded promising results in MDD, obsessive–compulsive disorder, tobacco use disorder, and stimulant use disorder (Richard and Garcia-Romeu Reference Richard and Garcia-Romeu2025). Improvements in cognitive flexibility – a transdiagnostic deficit observed in most psychiatric disorders – may be one of several underlying therapeutic effects of psychedelics.

The broad applicability of existing psychiatric treatments underscores the need for a scientific psychopathology that embraces transdiagnostic neurobiological frameworks beyond categorical diagnoses. Many psychiatric disorders, including addictions, involve impairments in core cognitive and emotional processes such as impulse control, reward sensitivity, and emotional regulation. Yet, research and treatment development efforts largely focus on single diagnoses, excluding patients with comorbidities. Those with substance use disorders in particular are commonly excluded from studies on other mental health disorders. Further, people with polysubstance use disorders are often excluded even from substance use disorder research. This limits the generalizability of research findings, restricts our understanding of underlying risk factors and mechanisms behind these disorders, and hinders our ability to develop effective treatment approaches. Treatments targeting shared vulnerabilities – whether through psychotherapeutic, pharmacological, or neuromodulatory approaches – may offer more effective and individualized interventions.