There is limited, poorly characterized information about adverse events occurring during maintenance treatment of bipolar disorder. We aimed to determine adverse event rates during treatment with ...lithium, valproate, olanzapine, and quetiapine.
We conducted a propensity score adjusted cohort study using nationally representative United Kingdom electronic health records from January 1, 1995, until December 31, 2013. We included patients who had a diagnosis of bipolar disorder and were prescribed lithium (n = 2148), valproate (n = 1670), olanzapine (n = 1477), or quetiapine (n = 1376) as maintenance mood stabilizer treatment. Adverse outcomes were chronic kidney disease, thyroid disease, hypercalcemia, weight gain, hypertension, type 2 diabetes mellitus, cardiovascular disease, and hepatotoxicity. The propensity score included important demographic, physical health, and mental health predictors of drug treatment allocation. The median duration of drug treatment was 1.48 y (interquartile range 0.64-3.43). Compared to patients prescribed lithium, those taking valproate, olanzapine, and quetiapine had reduced rates of chronic kidney disease stage 3 or more severe, following adjustment for propensity score, age, and calendar year, and accounting for clustering by primary care practice (valproate hazard ratio HR 0.56; 95% confidence interval CI 0.45-0.69; p < 0.001, olanzapine HR 0.57; 95% CI 0.45-0.71; p < 0.001, quetiapine HR 0.62; 95% CI 0.47-0.80; p < 0.001). Hypothyroidism was reduced in those taking valproate (HR 0.60; 95% CI 0.40-0.89; p = 0.012) and olanzapine (HR 0.48; 95% CI 0.29-0.77; p = 0.003), compared to those taking lithium. Rates of new onset hyperthyroidism (valproate HR 0.24; 95% CI 0.09-0.61; p = 0.003, olanzapine HR 0.31; 95% CI 0.13-0.73; p = 0.007) and hypercalcemia (valproate HR 0.25; 95% CI 0.10-0.60; p = 0.002, olanzapine HR 0.32; 95% CI 0.14-0.76; p = 0.008, quetiapine HR 0.23; 95% CI 0.07-0.73; p = 0.013) were also reduced relative to lithium. However, rates of greater than 15% weight gain on valproate, olanzapine, and quetiapine were higher (valproate HR 1.62; 95% CI 1.31-2.01; p < 0.001, olanzapine HR 1.84; 95% CI 1.47-2.30; p < 0.001, quetiapine HR 1.67; 95% CI 1.24-2.20; p < 0.001) than in individuals prescribed lithium, as were rates of hypertension in the olanzapine treated group (HR 1.41, 95% CI 1.06-1.87; p = 0.017). We found no significant difference in rates of chronic kidney disease stage 4 or more severe, type 2 diabetes mellitus, cardiovascular disease, or hepatotoxicity. Despite estimates being robust following sensitivity analyses, limitations include the potential for residual confounding and ascertainment bias and an inability to examine dosage effects.
Lithium use is associated with more renal and endocrine adverse events but less weight gain than commonly used alternative mood stabilizers. Risks need to be offset with the effectiveness and anti-suicidal benefits of lithium and the potential metabolic side effects of alternative treatment options.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
People with severe mental illness (SMI) have higher rates of a range of physical health conditions, yet little is known regarding the clustering of physical health conditions in this population. We ...aimed to investigate the prevalence and clustering of chronic physical health conditions in people with SMI, compared to people without SMI.
We performed a cohort-nested accumulated prevalence study, using primary care data from the Clinical Practice Research Datalink (CPRD), which holds details of 39 million patients in the United Kingdom. We identified 68,783 adults with a primary care diagnosis of SMI (schizophrenia, bipolar disorder, or other psychoses) from 2000 to 2018, matched up to 1:4 to 274,684 patients without an SMI diagnosis, on age, sex, primary care practice, and year of registration at the practice. Patients had a median of 28.85 (IQR: 19.10 to 41.37) years of primary care observations. Patients with SMI had higher prevalence of smoking (27.65% versus 46.08%), obesity (24.91% versus 38.09%), alcohol misuse (3.66% versus 13.47%), and drug misuse (2.08% versus 12.84%) than comparators. We defined 24 physical health conditions derived from the Elixhauser and Charlson comorbidity indices and used logistic regression to investigate individual conditions and multimorbidity. We controlled for age, sex, region, and ethnicity and then additionally for health risk factors: smoking status, alcohol misuse, drug misuse, and body mass index (BMI). We defined multimorbidity clusters using multiple correspondence analysis (MCA) and K-means cluster analysis and described them based on the observed/expected ratio. Patients with SMI had higher odds of 19 of 24 conditions and a higher prevalence of multimorbidity (odds ratio (OR): 1.84; 95% confidence interval CI: 1.80 to 1.88, p < 0.001) compared to those without SMI, particularly in younger age groups (males aged 30 to 39: OR: 2.49; 95% CI: 2.27 to 2.73; p < 0.001; females aged 18 to 30: OR: 2.69; 95% CI: 2.36 to 3.07; p < 0.001). Adjusting for health risk factors reduced the OR of all conditions. We identified 7 multimorbidity clusters in those with SMI and 7 in those without SMI. A total of 4 clusters were common to those with and without SMI; while 1, heart disease, appeared as one cluster in those with SMI and 3 distinct clusters in comparators; and 2 small clusters were unique to the SMI cohort. Limitations to this study include missing data, which may have led to residual confounding, and an inability to investigate the temporal associations between SMI and physical health conditions.
In this study, we observed that physical health conditions cluster similarly in people with and without SMI, although patients with SMI had higher burden of multimorbidity, particularly in younger age groups. While interventions aimed at the general population may also be appropriate for those with SMI, there is a need for interventions aimed at better management of younger-age multimorbidity, and preventative measures focusing on diseases of younger age, and reduction of health risk factors.
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Particulate air pollution's physical health effects are well known, but associations between particulate matter (PM) exposure and mental illness have not yet been established. However, there is ...increasing interest in emerging evidence supporting a possible etiological link.
This systematic review aims to provide a comprehensive overview and synthesis of the epidemiological literature to date by investigating quantitative associations between PM and multiple adverse mental health outcomes (depression, anxiety, bipolar disorder, psychosis, or suicide).
We undertook a systematic review and meta-analysis. We searched Medline, PsycINFO, and EMBASE from January 1974 to September 2017 for English-language human observational studies reporting quantitative associations between exposure to PM
in aerodynamic diameter (ultrafine particles) and PM
and
in aerodynamic diameter (
and
, respectively) and the above psychiatric outcomes. We extracted data, appraised study quality using a published quality assessment tool, summarized methodological approaches, and conducted meta-analyses where appropriate.
Of 1,826 citations identified, 22 met our overall inclusion criteria, and we included 9 in our primary meta-analyses. In our meta-analysis of associations between long-term (
)
exposure and depression (
studies), the pooled odds ratio was 1.102 per
increase (95% CI: 1.023, 1.189;
). Two of the included studies investigating associations between long-term
exposure and anxiety also reported statistically significant positive associations, and we found a statistically significant association between short-term
exposure and suicide in meta-analysis at a 0-2 d cumulative exposure lag.
Our findings support the hypothesis of an association between long-term
exposure and depression, as well as supporting hypotheses of possible associations between long-term
exposure and anxiety and between short-term
exposure and suicide. The limited literature and methodological challenges in this field, including heterogeneous outcome definitions, exposure assessment, and residual confounding, suggest further high-quality studies are warranted to investigate potentially causal associations between air pollution and poor mental health. https://doi.org/10.1289/EHP4595.
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Bipolar disorder and schizophrenia are associated with increased mortality relative to the general population. There is an international emphasis on decreasing this excess mortality.
To determine ...whether the mortality gap between individuals with bipolar disorder and schizophrenia and the general population has decreased.
A nationally representative cohort study using primary care electronic health records from 2000 to 2014, comparing all patients diagnosed with bipolar disorder or schizophrenia and the general population. The primary outcome was all-cause mortality.
Individuals with bipolar disorder and schizophrenia had elevated mortality (adjusted hazard ratio (HR) = 1.79, 95% CI 1.67-1.88 and 2.08, 95% CI 1.98-2.19 respectively). Adjusted HRs for bipolar disorder increased by 0.14/year (95% CI 0.10-0.19) from 2006 to 2014. The adjusted HRs for schizophrenia increased gradually from 2004 to 2010 (0.11/year, 95% CI 0.04-0.17) and rapidly after 2010 (0.34/year, 95% CI 0.18-0.49).
The mortality gap between individuals with bipolar disorder and schizophrenia, and the general population is widening.
People with severe mental illness (SMI) are at higher risk of physical health conditions compared to the general population, however, the impact of specific underlying health conditions on the use of ...secondary care by people with SMI is unknown. We investigated hospital use in people managed in the community with SMI and five common physical long-term conditions: cardiovascular diseases, COPD, cancers, diabetes and liver disease. We performed a systematic review and meta-analysis (Prospero: CRD42020176251) using terms for SMI, physical health conditions and hospitalisation. We included observational studies in adults under the age of 75 with a diagnosis of SMI who were managed in the community and had one of the physical conditions of interest. The primary outcomes were hospital use for all causes, physical health causes and related to the physical condition under study. We performed random-effects meta-analyses, stratified by physical condition. We identified 5,129 studies, of which 50 were included: focusing on diabetes (n = 21), cardiovascular disease (n = 19), COPD (n = 4), cancer (n = 3), liver disease (n = 1), and multiple physical health conditions (n = 2). The pooled odds ratio (pOR) of any hospital use in patients with diabetes and SMI was 1.28 (95%CI:1.15-1.44) compared to patients with diabetes alone and pooled hazard ratio was 1.19 (95%CI:1.08-1.31). The risk of 30-day readmissions was raised in patients with SMI and diabetes (pOR: 1.18, 95%CI:1.08-1.29), SMI and cardiovascular disease (pOR: 1.27, 95%CI:1.06-1.53) and SMI and COPD (pOR:1.18, 95%CI: 1.14-1.22) compared to patients with those conditions but no SMI. People with SMI and five physical conditions are at higher risk of hospitalisation compared to people with that physical condition alone. Further research is warranted into the combined effects of SMI and physical conditions on longer-term hospital use to better target interventions aimed at reducing inappropriate hospital use and improving disease management and outcomes.
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Cancer-associated fibroblasts (CAFs) were presumed absent in glioblastoma given the lack of brain fibroblasts. Serial trypsinization of glioblastoma specimens yielded cells with CAF morphology and ...single-cell transcriptomic profiles based on their lack of copy number variations (CNVs) and elevated individual cell CAF probability scores derived from the expression of 9 CAF markers and absence of 5 markers from non-CAF stromal cells sharing features with CAFs. Cells without CNVs and with high CAF probability scores were identified in single-cell RNA-Seq of 12 patient glioblastomas. Pseudotime reconstruction revealed that immature CAFs evolved into subtypes, with mature CAFs expressing actin alpha 2, smooth muscle (ACTA2). Spatial transcriptomics from 16 patient glioblastomas confirmed CAF proximity to mesenchymal glioblastoma stem cells (GSCs), endothelial cells, and M2 macrophages. CAFs were chemotactically attracted to GSCs, and CAFs enriched GSCs. We created a resource of inferred crosstalk by mapping expression of receptors to their cognate ligands, identifying PDGF and TGF-β as mediators of GSC effects on CAFs and osteopontin and HGF as mediators of CAF-induced GSC enrichment. CAFs induced M2 macrophage polarization by producing the extra domain A (EDA) fibronectin variant that binds macrophage TLR4. Supplementing GSC-derived xenografts with CAFs enhanced in vivo tumor growth. These findings are among the first to identify glioblastoma CAFs and their GSC interactions, making them an intriguing target.
ADHD Pharmacotherapy and Mortality Richards-Belle, Alvin; Launders, Naomi; Hayes, Joseph F
JAMA : the journal of the American Medical Association,
07/2024, Volume:
332, Issue:
1
Journal Article
Identifying modifiable risk factors is essential to reduce the prevalence adolescent depression. Self-report data suggest that physical activity and sedentary behaviour might be associated with ...depressive symptoms in adolescents. We examined associations between depressive symptoms and objectively measured physical activity and sedentary behaviour in adolescents.
From a population-based cohort of adolescents whose mothers were invited to participate in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, we included participants with at least one accelerometer recording and a Clinical Interview Schedule-Revised (CIS-R) depression score at age 17·8 years (reported as age 18 years hereafter). Amounts of time spent in sedentary behaviour and physical activity (light or moderate-to-vigorous) were measured with accelerometers at around 12 years, 14 years, and 16 years of age. Total physical activity was also recorded as count per minute (CPM), with raw accelerometer counts averaged over 60 s epochs. Associations between the physical activity and sedentary behaviour variables and depression (CIS-R) scores at age 18 years were analysed with regression and group-based trajectory modelling.
4257 adolescents from the 14 901 enrolled in the ALSPAC study had a CIS-R depression score at age 18 years. Longitudinal analyses included 2486 participants at age 12 years, 1938 at age 14 years, and 1220 at age 16 years. Total follow-up time was 6 years. Total physical activity decreased between 12 years and 16 years of age, driven by decreasing durations of light activity (mean 325·66 min/day SD 58·09 at 12 years; 244·94 min/day 55·08 at 16 years) and increasing sedentary behaviour (430·99 min/day 65·80; 523·02 min/day 65·25). Higher depression scores at 18 years were associated with a 60 min/day increase in sedentary behaviour at 12 years (incidence rate ratio IRR 1·111 95% CI 1·051–1·176), 14 years (1·080 1·012–1·152), and 16 years of age (1·107 1·015–1·208). Depression scores at 18 years were lower for every additional 60 min/day of light activity at 12 years (0·904 0·850–0·961), 14 years (0·922 0·857–0·992), and 16 years of age (0·889 0·809–0·974). Group-based trajectory modelling across 12–16 years of age identified three latent subgroups of sedentary behaviour and activity levels. Depression scores were higher in those with persistently high (IRR 1·282 95% CI 1·061–1·548) and persistently average (1·249 1·078–1·446) sedentary behaviour compared with those with persistently low sedentary behaviour, and were lower in those with persistently high levels of light activity (0·804 0·652–0·990) compared with those with persistently low levels of light activity. Moderate-to-vigorous physical activity (per 15 min/day increase) at age 12 years (0·910 0·857–0·966) and total physical activity (per 100 CPM increase) at ages 12 years (0·941 0·910–0·972) and 14 years (0·965 0·932–0·999), were negatively associated with depressive symptoms.
Sedentary behaviour displaces light activity throughout adolescence, and is associated with a greater risk of depressive symptoms at 18 years of age. Increasing light activity and decreasing sedentary behaviour during adolescence could be an important target for public health interventions aimed at reducing the prevalence of depression.
Details of funding are provided in the Acknowledgments.
TERT promoter mutations reactivate telomerase, allowing for indefinite telomere maintenance and enabling cellular immortalization. These mutations specifically recruit the multimeric ETS factor GABP, ...which can form two functionally independent transcription factor species: a dimer or a tetramer. We show that genetic disruption of GABPβ1L (β1L), a tetramer-forming isoform of GABP that is dispensable for normal development, results in TERT silencing in a TERT promoter mutation-dependent manner. Reducing TERT expression by disrupting β1L culminates in telomere loss and cell death exclusively in TERT promoter mutant cells. Orthotopic xenografting of β1L-reduced, TERT promoter mutant glioblastoma cells rendered lower tumor burden and longer overall survival in mice. These results highlight the critical role of GABPβ1L in enabling immortality in TERT promoter mutant glioblastoma.
•The β1L tetramer-forming isoform of GABP activates the mutant TERT promoter•β1L disruption induces telomere loss and death only in TERT promoter mutant cells•Disruption of β1L reduces tumor growth and prolongs survival in xenografted mice•GABPβ1L is a potential therapeutic target for TERT promoter mutant glioblastoma
TERT promoter mutations generate a binding site for GABP and reactivate TERT expression. Mancini et al. show that GABPβ1L, among GABP subunits, is specifically required for the function of TERT promoter mutants, and disrupting GABPβ1L causes telomere loss and cell death exclusively in TERT promoter mutant cells.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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