Numerous theories posit different core features to borderline personality disorder (BPD). Recent advances in network analysis provide a method of examining the relative centrality of BPD symptoms, as well as examine the replicability of findings across samples. Additionally, despite the increase in research supporting the validity of BPD in adolescents, clinicians are reluctant to diagnose BPD in adolescents. Establishing the replicability of the syndrome across adolescents and adults informs clinical practice and research. This study examined the stability of BPD symptom networks and centrality of symptoms across samples varying in age and clinical characteristics.

Cross-sectional analyses of BPD symptoms from semi-structured diagnostic interviews from the Collaborative Longitudinal Study of Personality Disorders (CLPS), the Methods to Improve Diagnostic Assessment and Service (MIDAS) study, and an adolescent clinical sample. Network attributes, including edge (partial association) strength and node (symptom) expected influence, were compared.

The three networks were largely similar and strongly correlated. Affective instability and identity disturbance emerged as relatively central symptoms across the three samples, and relationship difficulties across adult networks. Differences in network attributes were more evident between networks varying both in age and in BPD symptom severity level.

Findings highlight the relative importance of affective, identity, and relationship symptoms, consistent with several leading theories of BPD. The network structure of BPD symptoms appears generally replicable across multiple large samples including adolescents and adults, providing further support for the validity of the diagnosis across these developmental phases.

Transforming towards global sustainability requires a dramatic acceleration of social change. Hence, there is growing interest in finding ‘positive tipping points’ at which small interventions can trigger self-reinforcing feedbacks that accelerate systemic change. Examples have recently been seen in power generation and personal transport, but how can we identify positive tipping points that have yet to occur? We synthesise theory and examples to provide initial guidelines for creating enabling conditions, sensing when a system can be positively tipped, who can trigger it, and how they can trigger it. All of us can play a part in triggering positive tipping points.

Recent work on positive tipping points towards sustainability has focused on social-technological systems and the agency of policymakers to tip change, whilst earlier work identified social-ecological positive feedbacks triggered by diverse actors. We bring these together to consider positive tipping points across social-technological-ecological systems and the potential for multiple actors and interventions to trigger them. Established theory and examples provide several generic mechanisms for triggering tipping points. From these we identify specific enabling conditions, reinforcing feedbacks, actors and interventions that can contribute to triggering positive tipping points in the adoption of sustainable behaviours and technologies. Actions that can create enabling conditions for positive tipping include targeting smaller populations, altering social network structure, providing relevant information, reducing price, improving performance, desirability and accessibility, and coordinating complementary technologies. Actions that can trigger positive tipping include social, technological and ecological innovations, policy interventions, public investment, private investment, broadcasting public information, and behavioural nudges. Positive tipping points can help counter widespread feelings of disempowerment in the face of global challenges and help unlock ‘paralysis by complexity’. A key research agenda is to consider how different agents and interventions can most effectively work together to create system-wide positive tipping points whilst ensuring a just transformation.

We identify key actors and actions that can enable and trigger positive tipping points towards global sustainability.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Antidepressant prescribing is widespread. Nonetheless, response to antidepressants is variable. If it was possible to predict response to medication and thus tailor treatment accordingly, this would not only improve patient outcomes but may also have economic benefits.

To test the hypothesis that individuals with more severe depression would benefit more from noradrenaline reuptake inhibitors (NARIs) than selective serotonin reuptake inhibitors (SSRIs) compared with individuals with less severe depression.

Individuals recruited from UK primary care who met ICD-10 criteria for a depressive episode and scored 15 or more on the Beck Depression Inventory (BDI) were randomised to either an SSRI (citalopram 20mg daily) or a NARI (reboxetine 4mg twice daily). Randomisation was by means of a remote automated telephone system. The main outcome was depressive symptoms measured by the BDI total score 6 weeks after randomisation. (Trial registration: ISRCTN31345163.)

In total, 601 participants were randomised (citalopram: n = 298, reboxetine: n = 303). Ninety-one per cent were followed up at 6 weeks (citalopram: n = 274, reboxetine: n = 272). There was little evidence to support an interaction between treatment and severity of depression (interaction term: 0.02, 95% CI −0.59 to 0.62, P = 0.96). Adjustment for potential confounders (age, gender, employment status, history of depression, number of life events and social support) did not affect the findings (interaction term: 0.06, 95% CI −0.54 to 0.66, P = 0.85).

Treatment with NARIs does not confer any advantage over SSRI treatment for outcome in those with more severe depressive illness presenting in primary care.

Antidepressants exhibit a variety of pharmacological actions including inhibition of the serotonin and noradrenaline transporters. We wished to investigate whether genetic variation could be used to target or personalise treatment, in a comparison of selective serotonin reuptake inhibitors (SSRIs) with noradrenaline reuptake inhibitors (NARIs).

To test the hypothesis that patients homozygous for the long (insertion) polymorphism of the serotonin transporter (5-HTTLPR) have an increased response to SSRI antidepressants but not to NARI antidepressants.

In an individually randomised, parallel-group controlled trial, people meeting criteria for a depressive episode who were referred by their general practitioner were randomised to receive either citalopram (an SSRI) or reboxetine (an NARI). Randomisation was by means of a remote automated system accessed by telephone. The main outcome was depressive symptoms, measured by Beck Depression Inventory (BDI) total score 6 weeks after randomisation. The trial was registered with the International Standard Randomised Controlled Trials Number registry (ISRCTN31345163).

Altogether 298 participants were randomised to receive citalopram and 303 were randomised to reboxetine. At 6 weeks follow-up, complete data were available for 258 participants taking citalopram and 262 taking reboxetine. We found no evidence to support an influence of 5-HTTLPR on outcome following antidepressant treatment. The interaction term for BDI score at 6 weeks was 0.50 (95% CI −2.04 to 3.03, P = 0.70), which indicated that responses to the SSRI and NARI were similar irrespective of 5-HTTLPR genotype.

It is unlikely that the 5-HTTLPR polymorphism alone will be clinically useful in predicting response to antidepressants in people with depression.