General somatic health and lifestyle habits in individuals with obsessive- compulsive disorder: an international survey.

BACKGROUND: Obsessive-compulsive disorder (OCD) has been associated with a broad range of health-related issues. Unhealthy lifestyle habits such as physical inactivity, an unhealthy diet, smoking, and alcohol consumption are hypothesized to contribute to this association. However, the lifestyle habits of individuals with OCD have been scarcely investigated. In this international survey, we explored the physical health and lifestyle habits of adults with a self-reported diagnosis of OCD. METHODS: An online global survey available in seven languages was disseminated through interest organizations and social media between July 2021 and March 2022. The survey included questions relating to socio-demographic variables and clinical characteristics (including OCD symptom severity - as measured with the 12-item self-report scale Obsessive-Compulsive Inventory [OCI-12] - and psychotropic medication), physical health, and lifestyle habits. Frequencies and percentages, or means and standard deviations, as appropriate, were calculated. Subgroup analyses by OCD symptom severity, gender, and age group were performed. RESULTS: A total of 496 individuals with OCD completed the survey and were included in the analyses (mean age = 36.0 years, SD = 12.5, range 18-79; 78.8% women). Most participants were from Europe (n = 245, 49.4%) and North America (n = 187, 37.7%). OCD symptom severity scores were on the moderate range (OCI-12 mean score = 21.2, SD = 9.1). A majority (n = 354, 71.4%) reported having comorbid somatic health issues, mainly allergies, gastrointestinal conditions, and cardiometabolic conditions. Nearly half of the sample (n = 236, 47.6%) reported a body mass index ≥ 25, corresponding to at least overweight. A significant proportion of the participants reported low physical activity (n = 271, 55.0%), unhealthy dietary habits (n = 182, 36.7%), risk consumption of alcohol (n = 111, 22.3%), and non-restorative sleep (n = 268, 54.0%). Subgroup analyses showed overall similar results across groups, with some exceptions. CONCLUSIONS: In this sample, individuals with OCD self-reported a range of health-related issues and a number of unhealthy lifestyle behaviors, most prominently a lack of physical activity. Interventions aimed at modifying unhealthy lifestyles to prevent or improve health conditions beyond the psychiatric symptoms should be considered.

Introducing Braining-physical exercise as adjunctive therapy in psychiatric care: a retrospective cohort study of a new method.

BACKGROUND: Patients with severe mental disorders suffer from higher rates of poor somatic health and have shorter life expectancy than the average population. Physical activity can treat and prevent several diseases, e.g. cardiovascular and metabolic disorders as well as psychiatric symptoms. It is therefore of utmost importance to develop effective methods to integrate physical activity into psychiatric care. To meet this need, the physical activity intervention Braining was developed. This study aims to describe Braining, to assess the number of patients reached during the first years of pilot testing, to analyze clinical data in the group of patients participating in Braining 2017-2020 and to assess the intervention. METHODS: In this descriptive retrospective study we analyzed data from all patients participating in Braining training sessions ≥ 3 times (n = 239), the Braining Participants. Regular patients at the clinic served as a comparison. Furthermore, medical records were studied for a smaller cohort (n = 51), the Braining Pilot Cohort. Data was analyzed using Chi-square and Fisher's tests. RESULTS: During the introduction period of Braining, 580 patients attended an information meeting about Braining, or at least one training session. 239 patients participated in ≥ 3 training sessions, considered to be participants of Braining. These Braining Participants (n = 239), ages 19 to 82, males 23.4%, attended between 3 and 308 training sessions (median 9). The main diagnoses were affective and anxiety disorders. Number of diagnoses ranged from 0 to 10 (median = 2). For the subsample, the Braining Pilot Cohort (n = 51), participants attended between 3 and 208 training sessions (median = 20). Twelve percent were working full-time, and symptom severity of depression and general anxiety was moderate. Two thirds had ≥ 3 different classes of medication. Regarding metabolic morbidity, 28 had been diagnosed with hypertension, though blood lipids, blood glucose as well as blood pressure were within the normal range. Thirty-seven percent were prescribed Physical Activity on Prescription during 2017-2020. One severe adverse event was reported. CONCLUSIONS: The Braining intervention reached all age-groups and patients with a wide and representative diagnostic panorama, suggesting that Braining could be a promising and safe method for implementing physical activity in a psychiatric patient population.

Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden.

BACKGROUND: Lithium is the most effective treatment for bipolar disorder, resulting in strong suicide prevention effects. The therapeutic range of lithium, however, is narrow and treatment initiation requires individual titration to address inter-individual variability. We aimed to improve lithium dose prediction using clinical and genomic data. METHODS: We performed a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two clinical Swedish cohorts. Participants in cohort 1 were from specialised outpatient clinics at Huddinge Hospital, in Stockholm, Sweden, and participants in cohort 2 were identified using the Swedish National Quality Registry for Bipolar disorder (BipoläR). Patients who received a lithium dose corresponding to at least one tablet of lithium sulphate (6 mmol) per day and had clinically relevant plasma concentrations of lithium were included in the study. Data on age, sex, bodyweight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of tablets of lithium per day, serum lithium concentration, and medications affecting kidney function (C09 antihypertensives, C03 [except C03D] sodium-retaining diuretics, and non-steroidal anti-inflammatory drugs) were obtained retrospectively for several timepoints when possible from electronic health records, BipoläR, and the Swedish prescription registry. The median time between timepoints was 1·07 years for cohort 1 and 1·09 years for cohort 2. The primary outcome of interest was the natural logarithm of total body clearance for lithium (CLLi) associated with the clinical variables. The residual effects after accounting for age and sex, representing the individual-level effects (CLLi,age/sex), were used as the dependent variable in a GWAS. FINDINGS: 2357 patients who were administered lithium (1423 women [60·4%] and 934 men [39·6%]; mean age 53·6 years [range 17-89], mainly of European descent) were included and 5627 data points were obtained. Age (variance explained [R2]: R2cohort1=0·41 and R2cohort2=0·31; both p<0·0001), sex (R2cohort1=0·0063 [p=0·045] and R2cohort2=0·026 [p<0·0001]), eGFR (R2cohort1=0·38 and R2cohort2=0·20; both p<0·0001), comedication with diuretics (R2cohort1=0·0058 [p=0·014] and R2cohort2=0·0026 [p<0·0001]), and agents acting on the renin-aldosterone-angiotensin system (R2cohort1=0·028 and R2cohort2=0·015; both p<0·0001) were clinical predictors of CLLi. Notably, an association between CLLi and serum lithium was observed, with a lower CLLi being associated with higher serum lithium (R2cohort1=0·13 and R2cohort2=0·15; both p<0·0001). In a GWAS of CLLi,age/sex, one locus was associated with a change in CLLi (rs583503; ß=-0·053 [95% CI -0·071 to -0·034]; p<0·00000005). We also found enrichment of the associations with genes expressed in the medulla (p=0·0014, corrected FDR=0·04) and cortex of the kidney (p=0·0015, corrected FDR=0·04), as well as associations with polygenic risk scores for eGFR (p value threshold: 0·05, p=0·01), body-mass index (p value threshold: 0·05, p=0·00025), and blood urea nitrogen (p value threshold: 0·001, p=0·00043). The model based on six clinical predictors explained 61·4% of the variance in CLLi in cohort 1 and 49·8% in cohort 2. Adding genetic markers did not lead to major improvement of the models: within the subsample of genotyped individuals, the variance explained only increased from 59·32% to 59·36% in cohort 1 and from 49·21% to 50·03% in cohort 2 when including rs583503 and the four first principal components. INTERPRETATION: Our model predictors could be used clinically to better guide lithium dosage, shortening the time to reach therapeutic concentrations, thus improving care. Identification of the first genomic locus and PRS to be associated with CLLi introduces the opportunity of individualised medicine in lithium treatment. FUNDING: Stanley Medical Research Institute, Swedish Research Council, Swedish Foundation for Strategic Research, Swedish Brain Foundation, Swedish Research Council, Söderström-Königska Foundation, Bror Gadelius Minnesfond, Swedish Mental Health Fund, Karolinska Institutet and Hospital.

Prediction of lithium response using genomic data.

Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen's kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [- 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.

Lithium and the Interplay Between Telomeres and Mitochondria in Bipolar Disorder.

Bipolar disorder is a severe psychiatric disorder which affects more than 1% of the world's population and is a leading cause of disability among young people. For the past 50 years, lithium has been the drug of choice for maintenance treatment of bipolar disorder due to its potent ability to prevent both manic and depressive episodes as well as suicide. However, though lithium has been associated with a multitude of effects within different cellular pathways and biological systems, its specific mechanism of action in stabilizing mood remains largely elusive. Mitochondrial dysfunction and telomere shortening have been implicated in both the pathophysiology of bipolar disorder and as targets of lithium treatment. Interestingly, it has in recent years become clear that these phenomena are intimately linked, partly through reactive oxygen species signaling and the subcellular translocation and non-canonical actions of telomerase reverse transcriptase. In this review, we integrate the current understanding of mitochondrial dysfunction, oxidative stress and telomere shortening in bipolar disorder with documented effects of lithium. Moreover, we propose that lithium's mechanism of action is intimately connected with the interdependent regulation of mitochondrial bioenergetics and telomere maintenance.

AKT1 and genetic vulnerability to bipolar disorder.

AKT1 encodes a serine/threonine kinase that has as one of its best-known substrates glycogen synthase kinase-3 (GSK3), a primary target for lithium. AKT1 has been previously been implicated as a vulnerability gene for bipolar disorder (BD). We aimed to associate genetic variants in the AKT1 gene with subgroups of BD. BD patients from a Swedish cohort (N = 831) were phenotyped in regards to their psychotic episodes according to mood-congruence in depression and manias, and compared to controls (N = 1,496). All participants were genotyped for SNPs in AKT1 previously implicated to have a role: rs3730358, rs1130214 and rs3803300. None of the effects reported in earlier studies were statistically significant, including the association between rs3803300 and BD without any psychotic symptoms, rs3803300 and mood-congruent psychosis, rs3803300 and the combined groups, as well as the association between the haplotypes formed by rs3730358 and rs1130214 and risk for BD. In a Bayesian analysis, all Bayes' Factors using default priors supported the null hypothesis in the replication set by a factor of between 5 and 1300 times. Analysis of genome wide association data did not reveal any association between BD and the AKT1 region. We conclude AKT1 is less likely to be a vulnerability gene in BD.

Lithium treatment and cancer incidence in bipolar disorder.

OBJECTIVES: To investigate whether there is an increased risk of cancer associated with lithium treatment in patients with bipolar disorder compared to the general population. METHODS: A nationwide Swedish register study of incidence rate ratios (IRRs) of total cancer and site-specific cancer in the 50-84-year age range was carried out in patients with bipolar disorder (n = 5,442) with and without lithium treatment from July 2005 to December 2009 compared to the general population using linked information from The Swedish Cancer Register, The National Patient Register, and The Drug Prescription Register. RESULTS: The overall cancer risk was not increased in patients with bipolar disorder. There was no difference in risk of unspecified cancer, neither in patients with lithium treatment compared to the general population [IRR = 1.04, 95% confidence interval (CI): 0.89-1.23] nor in patients with bipolar disorder without lithium treatment compared to the general population (IRR = 1.03, 95% CI: 0.89-1.19). The cancer risk was significantly increased in patients with bipolar disorder without lithium treatment in the digestive organs (IRR = 1.47, 95% CI: 1.12-1.93), in the respiratory system and intrathoracic organs (IRR = 1.72, 95% CI: 1.11-2.66), and in the endocrine glands and related structures (IRR = 2.60, 95% CI: 1.24-5.47), but in patients with bipolar disorder with lithium treatment, there was no significantly increased cancer risk compared to the general population. CONCLUSIONS: Bipolar disorder was not associated with increased cancer incidence and neither was lithium treatment in these patients. Specifically, there was an increased risk of respiratory, gastrointestinal, and endocrine cancer in patients with bipolar disorder without lithium treatment.

hTERT genetic variation in depression.

BACKGROUND: Telomeres are protective DNA-protein complexes forming the chromosome ends. TL differs between tissues. Shorter telomere length (TL) in blood leukocytes (LTL) has been associated with major depression, and with previous exposure to childhood adversity. TL studies on non-invasively sampled salivary DNA are less common. Telomerase, with its catalytic subunit hTERT, counteracts telomere shortening. Reduced telomerase activity associates with depression-like behavior in mice. Recently, the minor allele of the hTERT polymorphism rs2736100 was associated with shorter LTL among primarily healthy individuals. We hypothesized that (i) TL in saliva DNA is shortened in adults with a history of depression, and that (ii) rs2736100 is implicated in depression and depressive episodes in bipolar disorder type 1 (BD1). METHODS: Individuals with a history of depression and those without (controls) were identified using self-reported questionnaires from a well-characterized population-based cohort. Clinical BD1 patients were diagnosed by specialized psychiatrists. Saliva TL was measured in age-matched depressed individuals and controls (n=662) using qRT-PCR. rs2736100 was genotyped in 436 depressed individuals, 1590 controls, and 368 BD1 patients. RESULTS: Saliva TL was shorter in depressed individuals compared to controls. The rs2736100 minor allele was associated with depression among those without experience of childhood adversity, and with number of depressive episodes in BD1 patients responding well to lithium. LIMITATION: Psychopathological symptoms were recorded at two time points only, 3 and 6 years prior to DNA sampling. CONCLUSIONS: This is the first report on hTERT genetic variation in mood disorder. It proposes that genetic variation in hTERT may influence the susceptibility to depression.

Mood Stabilizers and the Influence on Global Leukocyte DNA Methylation in Bipolar Disorder.

Little is known about the relationship between treatments for bipolar disorder (BD), their therapeutic responses and the DNA methylation status. We investigated whether global DNA methylation levels differ between healthy controls and bipolar patients under different treatments. Global DNA methylation was measured in leukocyte DNA from bipolar patients under lithium monotherapy (n = 29) or combination therapy (n = 32) and from healthy controls (n = 26). Lithium response was assessed using the Alda scale. Lithium in monotherapy was associated with hypomethylation (F = 4.63, p = 0.036). Lithium + valproate showed a hypermethylated pattern compared to lithium alone (F = 7.27, p = 0.011). Lithium response was not associated with DNA methylation levels. These data suggest that the choice of treatment in BD may lead to different levels of global DNA methylation. However, further research is needed to understand its clinical significance.