The biology of aggressive behavior in bipolar disorder: A systematic review

Fico, Giovanna; Anmella, Gerard; Pacchiarotti, Isabella; Verdolini, Norma; Sagué-Vilavella, María; Corponi, Filippo; Manchia, Mirko; Vieta, Eduard; Murru, Andréa

doi:10.1016/j.neubiorev.2020.09.015

Cited by 16 publications

(9 citation statements)

References 123 publications

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“…Thus, diverse genetic and neurobiological pathways may rather reflect into differently severe patient subgroups. 50 In the present study, although no genetic or neurobiological correlates were investigated, a family history of mood disorders, a proxy for possible genetic liability, independently contributed to the regression model showing positive association to seasonality, coherently with previous evidence. 9,51 The etiology of seasonal fluctuations in BD is still unclear, but biorhythm alterations, such as in levels of energy, sleep quality/quantity, and duration among others, are structural characteristics of an acute mood episode, 8 possibly accounting for a part of the clinical heterogeneity witnessed both in euphoric states and even more in depression.…”

Section: Discussionsupporting

confidence: 89%

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Clinical correlates of seasonality in bipolar disorder: A specifier that needs specification?

Fico

Toffol

Anmella

et al. 2020

Acta Psychiatr Scand

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Objective Seasonal pattern (SP) is a bipolar disorder (BD) specifier that indicates a tendency towards affective relapses during specific moments of the year. SP affects 15%–25% of BD patients. In the past, SP was applied only to depressive relapses while, in DSM‐5, SP may be applied to both depressive and (hypo)manic episodes. We examined the association between different clinical correlates of BD and SP according to its current definition in a cohort of patients with BD type I (BDI) and II (BDII). Methods Patients were recruited from a specialized unit and assessed according to the season of relapse and type of episode per season. SP and non‐SP patients were compared looking into sociodemographic and clinical correlates. Significant variables at univariate comparisons were included in multivariate logistic regression with SP as the dependent variable. Results 708 patients were enrolled (503 BDI, 205 BDII), and 117 (16.5%) fulfilled DSM‐5 criteria for SP. The mean age was 45.3 years (SD = 14.18), and 389 were female (54.9%). The logistic regression model included a significant contribution of BDII (OR = 2.23, CI 1.4–3.55), family history of mood disorder (OR = 1.97, CI 1.29–3.01), undetermined predominant polarity (OR = 0.44, CI 0.28–0.70), and aggressive behavior (OR = 0.42, CI 0.23–0.75). Conclusion Our results outline a novel positive association of SP with undetermined predominant polarity, BDII, family history of mood disorder, and with fewer aggressiveness‐related symptoms. Seasonality is associated with a biphasic pattern with similar dominance of (hypo)mania and depression and is more frequent in BDII as compared to BDI. Seasonal episodes may be easier to predict, but difficult to prevent.

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Section: Discussionsupporting

confidence: 89%

“…Furthermore, a deregulation of the circadian system at a genetic level has been shown both in seasonality 48 and certain types of aggression, 49 accounting for complex shared genetic underpinnings. Thus, diverse genetic and neurobiological pathways may rather reflect into differently severe patient subgroups 50 …”

Section: Discussionmentioning

confidence: 99%

Clinical correlates of seasonality in bipolar disorder: A specifier that needs specification?

Fico

Toffol

Anmella

et al. 2020

Acta Psychiatr Scand

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“…Bipolar disorder is associated with an increased risk of aggressive behavior[ 128 - 131 ]. A high risk of aggressive behavior has also been demonstrated in bipolar patients in remission[ 110 , 132 - 134 ].…”

Section: Aggression In Different Psychiatric Disordersmentioning

confidence: 99%

“…Serotonergic hypoactivation has been hypothesized to play a role in the neurobiological basis of aggression in bipolar illness[ 131 ]. The association between prefrontal cortical dysfunction and aggressive behavior in bipolar patients has been repeatedly confirmed[ 152 - 154 ].…”

Section: Aggression In Different Psychiatric Disordersmentioning

confidence: 99%

Prevalence and correlates of aggressive behavior in psychiatric inpatient populations

Girasek¹,

Nagy²,

Fekete³

et al. 2022

WJP

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Aggressive behavior in patients with psychiatric disorders is attracting increasing research interest. One reason for this is that psychiatric patients are generally considered more likely to be aggressive, which raises a related question of whether diagnoses of psychiatric disorders predict the prevalence of aggressive behavior. Predicting aggression in psychiatric wards is crucial, because aggressive behavior not only endangers the safety of both patients and staff, but it also extends the hospitalization times. Predictions of aggressive behavior also need careful attention to ensure effective treatment planning. This literature review explores the relationship between aggressive behavior and psychiatric disorders and syndromes (dementia, psychoactive substance use, acute psychotic disorder, schizophrenia, bipolar affective disorder, major depressive disorder, obsessive-compulsive disorder, personality disorders and intellectual disability). The prevalence of aggressive behavior and its underlying risk factors, such as sex, age, comorbid psychiatric disorders, socioeconomic status, and history of aggressive behavior are discussed as these are the components that mostly contribute to the increased risk of aggressive behavior. Measurement tools commonly used to predict and detect aggressive behavior and to differentiate between different forms of aggressive behavior in both research and clinical practice are also reviewed. Successful aggression prevention programs can be developed based on the current findings of the correlates of aggressive behavior in psychiatric patients.

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“…Proneness to impulsivity may lead to greater involvement in substance use and an increased risk for criminal, violent, or aggressive acts. However, these premises and the existence of putative common biological underpinnings of aggressive behavior and BD suggest that this undesirable outcome might result from environmental–gene interactions [ 69 ].…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Prediction of Comorbid Substance Use Disorders among People with Bipolar Disorder

Oliva

Prisco

Pons-Cabrera

et al. 2022

JCM

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Substance use disorder (SUD) is a common comorbidity in individuals with bipolar disorder (BD), and it is associated with a severe course of illness, making early identification of the risk factors for SUD in BD warranted. We aimed to identify, through machine-learning models, the factors associated with different types of SUD in BD. We recruited 508 individuals with BD from a specialized unit. Lifetime SUDs were defined according to the DSM criteria. Random forest (RF) models were trained to identify the presence of (i) any (SUD) in the total sample, (ii) alcohol use disorder (AUD) in the total sample, (iii) AUD co-occurrence with at least another SUD in the total sample (AUD+SUD), and (iv) any other SUD among BD patients with AUD. Relevant variables selected by the RFs were considered as independent variables in multiple logistic regressions to predict SUDs, adjusting for relevant covariates. AUD+SUD could be predicted in BD at an individual level with a sensitivity of 75% and a specificity of 75%. The presence of AUD+SUD was positively associated with having hypomania as the first affective episode (OR = 4.34 95% CI = 1.42–13.31), and the presence of hetero-aggressive behavior (OR = 3.15 95% CI = 1.48–6.74). Machine-learning models might be useful instruments to predict the risk of SUD in BD, but their efficacy is limited when considering socio-demographic or clinical factors alone.

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The biology of aggressive behavior in bipolar disorder: A systematic review

Cited by 16 publications

References 123 publications

Clinical correlates of seasonality in bipolar disorder: A specifier that needs specification?

Clinical correlates of seasonality in bipolar disorder: A specifier that needs specification?

Prevalence and correlates of aggressive behavior in psychiatric inpatient populations

Machine Learning Prediction of Comorbid Substance Use Disorders among People with Bipolar Disorder

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