Recent studies suggest an association between sympathies for violent protest and terrorism, and major depression, anxiety, post-traumatic stress disorder and psychiatric disorders in subgroups of radicalised people and in lone-actor terrorists.

The aim of this study is to identify and analyse all documented terrorist attacks in the Global Terrorism Database (GTD), where the motive for terrorism is questioned due to suspected mental health issues.

This study is based on a semi-quantitative, epidemiological analysis of all incidents from 1970 to the first half of 2021, as reported in the GTD. Incidents in which the act of terrorism was questionable because of alleged mental illness were included. Temporal factors, location, target type, attack and weapon type, perpetrator type and number of casualties were collated.

One hundred and two incidents in the period 1970–2020 and five incidents in 2021 were studied. The majority occurred in the period 2011–2020. The incidents resulted in a total of 99 fatal and 217 non-fatal injuries. Twenty-nine perpetrators died during the attacks.

The majority of the attacks occurred in the USA, followed by France and the West Bank and Gaza Strip. Armed assaults were the most frequently identified attack type (67%).

In North America, the incidence was as high as 8.2 and 3.4% of the total number of terrorist attacks in the periods 2001–2010 and 2021, respectively. Most of the perpetrators acted as lone actors. Five assailants were detained in a psychiatric facility after the judicial probe, 18 were convicted and 9 had not been sentenced.

The possible relation between terrorism and mental illness or addiction is a recent phenomenon in the GTD. The prototypical case consists of a lone actor suffering from an assumed mental illness committing an armed assault. Only a minority of perpetrators were unable to stand trial in this series.

Substance use has consistently been linked with cognitive impairments. However, most previous studies have focused on highly selective samples of individuals with chronic substance use disorders and have typically relied solely on self-reports. The associations between recreational use patterns of single or multiple substances and cognitive functioning in representative samples remain unclear.

We measured over 100 substances and their metabolites over the past 3 months in 850 young adults (48.6% female, Mage = 24.4) from a community-based cohort, using quantitative hair analysis. We assessed sustained attention, working memory, declarative memory, and a total cognitive performance index using the Cambridge Neuropsychological Test Automated Battery. We regressed cognition on hair substance concentrations, adjusting for sex, household socioeconomic status, migration background, education, gaming experience, and self-reported daily tobacco and alcohol use.

In their hair samples, 386 (45.5%) participants tested positive for at least one psychotropic substance other than alcohol and nicotine. Higher hair concentrations of Δ9-tetrahydrocannabinol (Cohen’s d = 0.40) and codeine (d = 0.22) were associated with lower sustained attention; higher concentrations of ketamine (d = 0.59) with worse declarative memory. Higher hair concentrations of cocaine and a higher polysubstance use severity index (PSUSI) were associated with both reduced attention (cocaine: d = 0.21; PSUSI: d = 0.30) and declarative memory (cocaine: d = 0.20; PSUSI: d = 0.29).

In this community sample of young adults, substance use was highly prevalent and associated with reduced cognitive performance, with small-to-moderate effect sizes. Cognitive consequences of recreational substance use may have been previously underestimated.

Cortical thickness reductions associated with chronic methamphetamine use exhibit a non-uniform spatial distribution across brain regions. A potential neurobiological mechanism underlying for this heterogeneous pattern may involve the structural and functional organization of cortical connectivity networks, which could mediate the propagation of neuroanatomical alterations. Here, we aimed to explore how brain network architecture constrains cortical thickness alterations and their clinical relevance.

The 3D-T1 images were acquired from 139 patients with methamphetamine use disorder (MUD) and 119 sex- and age-matched healthy controls. We first characterized distributed cortical thinning patterns in patients with MUD, then evaluated the relationships between regional atrophy and (1) multimodal nodal centrality measures (structural, morphological, and functional) and (2) atrophy profiles of structural connected neighbors. Individual network-weighted cortical abnormality maps were used to identify distinct MUD biotypes and related to clinical features through k-means clustering and partial least squares regression.

Cortical thinning patterns demonstrated significant associations with nodal centrality across all modalities, as well as cortical thinning of connected neighbors revealing a network-dependent atrophy architecture. Fronto-temporal regions emerged as critical epicenters, showing both high nodal centrality and strong correlations with connected neighbors’ thinning severity. We found that the individual differences in network-weighted cortical abnormality corresponded to clinical symptom variability, and distinguished two MUD biotypes associated with drug use.

Our findings suggest that cortical thinning in MUD is influenced by the brain connectome architecture, providing a mechanistic framework for understanding individual variability in addiction progression.

Genetic research on nicotine dependence has utilized multiple assessments that are in weak agreement.

We conducted a genome-wide association study (GWAS) of nicotine dependence defined using the Diagnostic and Statistical Manual of Mental Disorders (DSM-NicDep) in 61,861 individuals (47,884 of European ancestry [EUR], 10,231 of African ancestry, and 3,746 of East Asian ancestry) and compared the results to other nicotine-related phenotypes.

We replicated the well-known association at the CHRNA5 locus (lead single-nucleotide polymorphism [SNP]: rs147144681, p = 1.27E−11 in EUR; lead SNP = rs2036527, p = 6.49e−13 in cross-ancestry analysis). DSM-NicDep showed strong positive genetic correlations with cannabis use disorder, opioid use disorder, problematic alcohol use, lung cancer, material deprivation, and several psychiatric disorders, and negative correlations with respiratory function and educational attainment. A polygenic score of DSM-NicDep predicted DSM-5 tobacco use disorder criterion count and all 11 individual diagnostic criteria in the independent National Epidemiologic Survey on Alcohol and Related Conditions-III sample. In genomic structural equation models, DSM-NicDep loaded more strongly on a previously identified factor of general addiction liability than a “problematic tobacco use” factor (a combination of cigarettes per day and nicotine dependence defined by the Fagerström Test for Nicotine Dependence). Finally, DSM-NicDep showed a strong genetic correlation with a GWAS of tobacco use disorder as defined in electronic health records (EHRs).

Our results suggest that combining the wide availability of diagnostic EHR data with nuanced criterion-level analyses of DSM tobacco use disorder may produce new insights into the genetics of this disorder.