High Risk and Trajectories of Physical Illnesses before the Diagnosis of Bipolar Disorder

Association of lipids and inflammatory markers with left ventricular wall thickness in patients with bipolar disorder

BACKGROUND

Individuals with bipolar disorder (BD) face a high risk of heart failure and left ventricular (LV) dysfunction. Despite strong evidence that high LV relative wall thickness (RWT) is a risk marker for heart failure, few studies have evaluated LV RWT and aggravating factors in individuals with BD.

METHODS

We recruited 104 participants (52 patients with BD and 52 age- and sex-matched mentally healthy controls) to undergo echocardiographic imaging and biochemistry, high-sensitivity C-reactive protein (hs-CRP), and blood cell count measurements. LV RWT was estimated using the following equation: (2 × LV posterior wall end-diastolic thickness)/LV end-diastolic diameter. Clinical data were obtained through interviews and chart reviews.

RESULTS

The BD group exhibited a significantly greater LV RWT (Cohen's d = 0.53, p = 0.003) and a less favorable mitral valve E/A ratio (Cohen's d = 0.54, p = 0.023) and LV global longitudinal strain (Cohen's d = 0.57, p = 0.047) than did the control group. Multiple linear regression revealed that in the BD group, serum triglyceride levels (β = 0.466, p = 0.001), platelet-to-lymphocyte ratios (β = 0.324, p = 0.022), and hs-CRP levels (β = 0.289, p = 0.043) were all significantly and positively associated with LV RWT.

LIMITATIONS

This study applied a cross-sectional design, meaning that the direction of causation could not be inferred.

CONCLUSIONS

Patients with BD are at a risk of heart failure, as indicated by their relatively high LV RWT. Lipid levels and systemic inflammation may explain this unfavorable association.

Lurasidone and risk of metabolic syndrome: results from short and long-term studies in patients with bipolar depression

OBJECTIVE

The elevated prevalence of metabolic syndrome (MetS) in patients with depression has been associated with increased mortality. This post hoc analysis assessed the effect of treatment with lurasidone on risk of MetS in patients with bipolar depression.

METHODS

Data used in the current analyses consisted of 3 double-blind (DB), placebo-controlled, 6-week studies in adults with bipolar I depression (N = 1192), consisting of 1 monotherapy, and 2 adjunctive trials (lithium or valproate). Also analyzed was a 6-month open-label (OL) extension study (monotherapy, N = 316; adjunctive therapy, N = 497); and a 5-month, OL, stabilization phase followed by randomization to a 28-week DB, placebo-controlled, adjunctive therapy study with lurasidone (N = 490). MetS was defined based on NCEP ATP III criteria (2005 revision).

RESULTS

The proportion of patients with new-onset MetS was similar for lurasidone vs placebo in the short-term studies (monotherapy, 13.9% vs 15.3%; adjunctive therapy, 13.6% vs 11.0%); and remained stable during both the 6-month extension phase study (monotherapy, 15.2%; adjunctive therapy, 16.9%), and the 5-month stabilization study (adjunctive therapy, 12.2%). After 28 weeks of DB treatment (following 5-month treatment in the stabilization study), new onset MetS was observed at endpoint (OC) in 26.2% of the lurasidone group, and 30.8% of the placebo group.

CONCLUSIONS

This post hoc analysis found that both short and long-term treatment with lurasidone was associated with a relatively low risk for the development of MetS in patients with bipolar I disorder. These findings are consistent with similar analyses in patients with schizophrenia.

The temporal relationship between severe mental illness diagnosis and chronic physical comorbidity: a UK primary care cohort study of disease burden over 10 years

BACKGROUND

Despite increased rates of physical health problems in people with schizophrenia, bipolar disorder, and other psychotic illnesses, the temporal relationship between physical disease acquisition and diagnosis of a severe mental illness remains unclear. We aimed to determine the cumulative prevalence of 24 chronic physical conditions in people with severe mental illness from 5 years before to 5 years after their diagnosis.

METHODS

In this cohort study, we used the UK Clinical Practice Research Datalink (CPRD) to identify patients aged 18-100 years who were diagnosed with severe mental illness between Jan 1, 2000, and Dec 31, 2018. Each patient with severe mental illness was matched with up to four individuals in the CPRD without severe mental illness by sex, 5-year age band, primary care practice, and year of primary care practice registration. Individuals in the matched cohort were assigned an index date equal to the date of severe mental illness diagnosis in the patient with severe mental illness to whom they were matched. Our primary outcome was the cumulative prevalence of 24 physical health conditions, based on the Charlson and Elixhauser comorbidity indices, at 5 years, 3 years, and 1 year before and after severe mental illness diagnosis and at the time of diagnosis. We used logistic regression to compare people with severe mental illness with the matched cohort, adjusting for key variables such as age, sex, and ethnicity.

FINDINGS

We identified 68 789 patients diagnosed with a severe mental illness between Jan 1, 2000, and Dec 31, 2018, and we matched them to 274 827 patients without a severe mental illness diagnosis. In both cohorts taken together, the median age was 40·90 years (IQR 29·46-56·00), 175 138 (50·97%) people were male, and 168 478 (49·03%) were female. The majority of patients were of White ethnicity (59 867 [87·03%] patients with a severe mental illness and 244 566 [88·99%] people in the matched cohort). The most prevalent conditions at the time of diagnosis in people with severe mental illness were asthma (10 581 [15·38%] of 68 789 patients), hypertension (8696 [12·64%]), diabetes (4897 [7·12%]), neurological disease (3484 [5·06%]), and hypothyroidism (2871 [4·17%]). At diagnosis, people with schizophrenia had increased odds of five of 24 chronic physical conditions compared with matched controls, and nine of 24 conditions were diagnosed less frequently than in matched controls. Individuals with bipolar disorder and other psychoses had increased odds of 15 conditions at diagnosis. At 5 years after severe mental illness diagnosis, these numbers had increased to 13 conditions for schizophrenia, 19 for bipolar disorder, and 16 for other psychoses.

INTERPRETATION

Elevated odds of multiple conditions at the point of severe mental illness diagnosis suggest that early intervention on physical health parameters is necessary to reduce morbidity and premature mortality. Some physical conditions might be under-recorded in patients with schizophrenia relative to patients with other severe mental illness subtypes.

FUNDING

UK Office For Health Improvement and Disparities.

Incidence of and risk factors for alcohol dependence in bipolar disorder: A population-based cohort and nested case-control study

OBJECTIVES

Although alcohol dependence is highly prevalent in patients with bipolar disorder, the causal relationship is not yet well-established. This study estimated the incidence of alcohol dependence in a nationwide bipolar disorder cohort and examined risk factors for alcohol dependence.

METHODS

Patients aged 15-65 years with consistent bipolar disorder who had their first psychiatric admission between 1999 and 2012 (n = 21,791) were enrolled from the National Health Insurance Research Database in Taiwan. We calculated the adjusted incidence rate ratio of alcohol dependence in the bipolar cohort relative to the general population after stratification by age and sex. In the nested case-control study, we included patients with incident alcohol dependence as cases and four age- and sex-matched controls for each case to analyze health care utilization, comorbidities and concomitant medications between them.

RESULTS

We identified 1261 patients with bipolar disorder with incident alcohol dependence. Relative to the general population, the adjusted incidence rate ratio of alcohol dependence was 9.20 in the bipolar cohort. All adjusted incidence rate ratios were high across all age subgroups. Cases had higher psychiatric and nonpsychiatric health care utilization than did controls. Multivariate analysis revealed that cases tended to have cardiovascular disease, diabetes mellitus, chronic hepatic disease, pneumonia and delirium before alcohol dependence diagnosis. Cases had higher psychiatric comorbidities, namely drug-induced mental disorders, anxiety disorder, personality disorder, adjustment disorder and sleep disorder.

CONCLUSION

The bipolar cohort had a higher incidence of alcohol dependence. We identified specific groups with a high risk of alcohol dependence. Additional strategies for early detection, treatment and intervention for alcohol dependence should be developed.

Clustering of physical health multimorbidity in people with severe mental illness: An accumulated prevalence analysis of United Kingdom primary care data

BACKGROUND

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.

METHODS AND FINDINGS

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.

CONCLUSIONS

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.

Number of episodes and duration of illness associated with hypertension and 10-year cardiovascular risk in patients with bipolar disorder type I

Severe Mental Illnesses, including bipolar disorder (BD) and schizophrenia (SCZ), are burdened with an increased mortality and a significantly reduced life expectancy than general population, and cardiovascular diseases (CVD) are considered the most contributing conditions. The aim of the present study is to evaluate 10-year CV risk and the associated clinical characteristics in patients with SCZ, BD type I and II. Patients were consecutively recruited from two Italian psychiatric acute units. Single CV risk factors were assessed, and 10-year CV risk calculated by means of the CUORE Project 10-year CV risk algorithm, based on the combination of the following risk factors: age, systolic blood pressure, total and high-density lipoprotein cholesterol, diabetes, smoking habit, and hypertensive treatment. Three hundred patients were included. Patients with BD type I showed a higher prevalence of hypertension and 10-year CV risk score compared to the other groups. In subjects with BD type I, we found a significant correlation between duration of illness and number of mood episodes and both hypertension and 10-year CV risk score. Several preventive strategies should be provided to these vulnerable populations, such as correcting unhealthy lifestyles, prescribing medications at lower CV and metabolic risk, enhancing access to care.

Increased sympathetic tone is associated with illness burden in bipolar disorder

BACKGROUND

We recently described an association between reduced heart rate variability (HRV) and illness burden in bipolar disorder (BD) using a novel Illness Burden Index (IBI). We aimed to further characterize this association by using spectral analyses to assess whether the IBI is also associated with autonomic imbalance in BD patients.

METHODS

In this cross-sectional study, 53 participants with BD wore a device for 24 h to assess association between HRV spectral measures and the IBI or each of its components (age of onset, number and type of previous episode(s), duration of the most severe episode, history of suicide attempts or psychotic symptoms during episodes, co-morbid psychiatric disorders, and family history). We ran both unadjusted models and models controlling for age, sex, years of education, marital status, BMI, pharmacotherapy, and baseline functional cardiovascular capacity.

RESULTS

HRV low-frequency (LF) normalized values were almost twice as high as published in healthy controls. Higher IBI was associated with higher LF and lower High Frequency (HF) values, resulting in a higher LF/HF ratio, indicating an increased sympathetic tone. Four individual components of the IBI were similarly associated with measures of increased sympathetic tone: earlier age of onset, number of depressive episodes, co-morbid anxiety disorders, and family history of suicide. Adjusted and unadjusted models had similar results.

LIMITATIONS

Our models used mean LF and HF and do not consider their dynamic variations over 24 h or phase of the illness.

CONCLUSIONS

Burden of illness is associated with increased sympathetic tone in patients with BD, putting them at risk for arrythmias and sudden death.

Targeting Metabolic Dysfunction for the Treatment of Mood Disorders: Review of the Evidence

Major depressive disorder (MDD) and bipolar disorder (BD) are often chronic with many patients not responding to available treatments. As these mood disorders are frequently associated with metabolic dysfunction, there has been increased interest in novel treatments that would target metabolic pathways. The objectives of this scoping review were to synthesize evidence on the impact on mood symptoms of lipid lowering agents and anti-diabetics drugs, while also reviewing current knowledge on the association between mood disorders and dyslipidemia or hyperglycemia. We propose that metabolic dysfunction is prevalent in both MDD and BD and it may contribute to the development of these disorders through a variety of pathophysiological processes including inflammation, brain structural changes, hormonal alterations, neurotransmitter disruptions, alteration on brain cholesterol, central insulin resistance, and changes in gut microbiota. Current evidence is conflicting on the use of statins, polyunsaturated fatty acids, thiazolidinediones, glucagon-like peptide agonists, metformin, or insulin for the treatment of MDD and BD. Given the paucity of high-quality randomized controlled trials, additional studies are needed before any of these medications can be repurposed in routine clinical practice. Future trials need to enrich patient recruitment, include evaluations of mechanism of action, and explore differential effects on specific symptom domains such as anhedonia, suicidality, and cognition.