summary: Researchers have identified six predictors that may help determine the correct amount of lithium to treat a patient with bipolar disorder.
source: Karolinska Institute
Six predictors could help determine how much lithium is needed to treat patients with bipolar disorder, according to a large study led by researchers at Karolinska Institutet in Sweden.
The study published in the journal Lancet Psychiatryalso identifies genetic markers that appear to influence how quickly the body removes lithium from its system.
Our model can now be used to predict how much lithium a patient with bipolar disorder will need. This could reduce valuable time spent finding the right dose for each patient, potentially having a life-saving effect,” says Martin Schalling, MD, professor in the Department of Molecular Medicine and Surgery, Karolinska Institutet and first author of the study.
One of the most important treatments for patients with bipolar disorder is lithium, a condition that has been linked to an increased risk of suicide.
The chemical acts as a mood stabilizer and reduces episodes of depression and mania. The amount needed varies greatly between individuals and finding the right dose for each patient is key because too much can be toxic while too little is ineffective.
To reduce the risk of side effects, doctors tend to start treatment with lower doses that are increased over time, which means it can take months before the treatment has an effect.
To get around this, researchers have long sought to find a model that can predict dose response in individual patients.
Previous studies have identified markers such as age, gender, and kidney function as potential indicators of how quickly the body is removing lithium from its system (lithium filtering), which can be used to determine the amount needed on a daily basis. However, most studies were limited to small sample sizes.
In the current study, researchers examined the electronic health records and registration data of a total of 2,357 patients with bipolar disorder, which may represent the largest sample size for this type of study to date. Both men and women between the ages of 17 and 89, mostly of European descent, were included.
The study found associations between lithium clearance rate, age, gender, kidney function (measured as eGFR), blood lithium concentrations, and medications containing diuretics and substances that target the renin-angiotensin-aldosterone system (RAAS), which can be used to treat high blood pressure and other conditions.
Our findings suggest that older patients, women, patients with impaired renal function, and those taking certain medications require lower lithium doses. Interestingly, we also discovered that the amount of lithium taken and the concentrations of lithium in the blood did not appear to be completely proportional, which is somewhat inconsistent with current thinking.
says first author Vincent Melcher, a postdoctoral researcher in the Department of Molecular Medicine and Surgery, Karolinska Institutet, and resident in psychiatry at the Medical University of Vienna.
The study also found associations between less lithium removal and a single genetic locus on chromosome 11 and could also show that genetic variants affecting BMI and kidney function are linked to lithium removal.
Although the addition of genetic markers only slightly improved the predictive ability of the model, the researchers say it opens an opportunity for personalized medicine in the treatment of lithium in the future.
“Next, we will test our model in a clinical trial to see if it can reduce the time taken to find the right amount of lithium for each patient,” says Martin Schalling.
“If the result is positive, we will develop a digital application that psychiatrists can use in the future to help assess the dose of lithium for patients with bipolar disorder.”
About this research on psychopharmacology news
original search: Access closed.
“Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a genome-wide cohort study in SwedenWritten by Martin Schalling et al. Lancet Psychiatry
Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a genome-wide cohort study in Sweden
Lithium is the most effective treatment for bipolar disorder, resulting in powerful suicide prevention effects. However, the therapeutic range for lithium is narrow and initiation of therapy requires individual titration to address interindividual variability. We aimed to improve lithium dose prediction using clinical and genomic data.
We conducted a population pharmacokinetic study followed by a genome-wide association study (GWAS), including two Swedish clinical groups. Participants were in the first group of specialist outpatient clinics at Hudinge Hospital, Stockholm, Sweden, and participants in the second group were identified using the Swedish National Quality Registry for Bipolar Disorder (BipoläR). Patients who received a dose of lithium corresponding to at least 1 tablet of lithium sulfate (6 mmol) daily and who had clinically relevant plasma concentrations of lithium were included in the study.
Data on age, gender, body weight, height, creatinine concentration, estimated glomerular filtration rate (eGFR), lithium preparation, number of lithium tablets per day, serum lithium concentration, drugs affecting renal function (C09 Antihypertensives, C03 [except C03D] Sodium-containing diuretics, NSAIDs were retrospectively obtained for several time points when possible from electronic health records, BipoläR, and the Swedish Prescription Registry.
The median time between time points was 1 07 years for group 1 and 1 09 years for group 2. The primary outcome of attention was the natural logarithm of total body lithium clearance (CL).for me) associated with clinical variables.
Residual effects after accounting for age and gender, which represent effects at the individual level (CLLi, age/gender), as a dependent variable in GWAS.
2357 patients were given lithium (1,423 women [60·4%] and 934 men [39·6%]; Average age 53 6 years [range 17–89], mainly of European origin) and 5,627 data points were obtained. Age (Explain Variation [R2]: s21 . cohort= 0 41 and s22 . cohort= 0; 31; both p < 0 0001), gender (s21 . cohort= 0 0063 [p=0·045] And s22 . cohort= 0 026 [p<0·0001]), eGFR (s21 . cohort= 0 38 and s22 . cohort= 0 20; both p < 0 0001), comedication with diuretics (s21 . cohort= 0 0058 [p=0·014] And s22 . cohort= 0 0026 [p<0·0001]), factors that act on the renin, aldosterone and angiotensin system (s21 . cohort= 0 028 and s22 . cohort= 0 015; Both p < 0 0001) were clinical predictors of CLfor me.
It is noteworthy that there is an association between CLfor me The presence of lithium in the blood was observed with a decrease in CLfor me It is associated with elevated levels of lithium in the blood.s21 . cohort= 0 13 and s22 . cohort= 0; 15th ; Both are p < 0 0001). In the GWAS of CLLi, age/genderone locus was associated with a change in CLfor me (rs583503; β = –0; 053 [95% CI –0·071 to –0·034]; p < 0 00000005).
We also found enrichment for associations with genes expressed in the medulla (p = 0 0014, corrected FDR = 0 04) and renal cortex (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), BMI (p-value threshold: 0 05, p = 0 00025), 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 CLfor me In cohort 1 and 49 8% in group placebo.
Adding genetic markers did not lead to significant improvements in the models: in the subsample of genotyped individuals, the explained variance only increased from 59 32% to 59 36% in group 1 and from 49 21% to 50 03% in group placebo when including rs583503 and the first four major components.
Our model predictors can be used clinically to better guide the lithium dose, shorten the time to reach therapeutic concentrations, and thus improve care. Identification of the first genetic locus and PRS associated with CLfor me Offers an individual medicine opportunity in lithium therapy.
The Stanley Institute for Medical Research, the Swedish Research Council, the Swedish Foundation for Strategic Research, the Swedish Brain Foundation, the Swedish Research Council, the Söderström Konigska Foundation, the Brewer Gadelius Mänesfond, the Swedish Mental Health Fund, Karolinska Institute and Hospital.