Arachidonic acid (AA), a component of membrane phospholipids, is released by phospholipase A2 (PLA2) activation. Neuroinflammation, which is considered to contribute to AD, can increase PLA2 activity and AA turnover in brain phospholipids; this process has been imaged in unanesthetized rats (Lee, JNeurochem, 91, 936, 2004). To image neuroinflammation in AD patients. Regional brain AA incorporation coefficients (K*) were measured with {1–11C}AA and positron emission tomography (PET) (Giovacchini, JCBFMetab, 22, 1453, 2002) in 8 moderately-severely demented AD patients and 7 age-matched controls; regional cerebral blood flow (rCBF) was measured with 15O-water. PET images were corrected for partial voluming from MRI scans. Data were normalized to a global mean, which was independently determined. SPM2 was used to test for group differences. Results are at p< 0.001. Compared to controls, rCBF reductions of ~21% were in temporal (BA 37, 20 and 22) and 20–40% in parietal (BA 39 and 7) association cortex bilaterally of AD patients. AD patients had increased normalized K* for AA of ~15% in temporal association cortex bilaterally (BA 21 and 22), ~12% in the right parietal lobule (BA 39), and 10–14% bilaterally in orbitofrontal cortex (BA 11 and 47). Between group differences were greater with absolute K* and rCBF values. Compared to controls, AD patients had 35% decreased mean global CBF and 23% increased global K*. AA incorporation is increased in AD compared with control brainn, globally and regional in brain areas demonstrating inflammatory neuropathology on postmortem; rCBF redudctions in these areas are consistent with prior evidence of reduced neuronal activity. As animals studies indicate that K* increases represent neuroinflammation involving increased PLA2 activity and AA turnover (Rosenberger, JNeurochem, 88, 1168, 2004), our findings suggest that neuroinflammation can be imaged in vivo in AD patients. PET imaging of AA incorporation might be used as a surrogate marker of AD neuroinflammation, for early diagnosis and evaluation of disease progression.
Bipolar disorder is a serious and common psychiatric disorder characterized by manic and depressive mood switches and a relapsing and remitting course. The cornerstone of clinical management is stabilization and prophylaxis using mood-stabilizing medications to reduce both manic and depressive symptoms. Lithium remains the gold standard of treatment with the strongest data for both efficacy and suicide prevention. However, many patients do not respond to this medication, and clinically there is a great need for tools to aid the clinician in selecting the correct treatment. Large genome wide association studies (GWAS) investigating retrospectively the effect of lithium response are in the pipeline; however, few large prospective studies on genetic predictors to of lithium response have yet been conducted. The purpose of this project is to identify genes that are associated with lithium response in a large prospective cohort of bipolar patients and to better understand the mechanism of action of lithium and the variation in the genome that influences clinical response. This study is an 11-site prospective non-randomized open trial of lithium designed to ascertain a cohort of 700 subjects with bipolar I disorder who experience protocol-defined relapse prevention as a result of treatment with lithium monotherapy. All patients will be diagnosed using the Diagnostic Interview for Genetic Studies (DIGS) and will then enter a 2-year follow-up period on lithium monotherapy if and when they exhibit a score of 1 (normal, not ill), 2 (minimally ill) or 3 (mildly ill) on the Clinical Global Impressions of Severity Scale for Bipolar Disorder (CGI-S-BP Overall Bipolar Illness) for 4 of the 5 preceding weeks. Lithium will be titrated as clinically appropriate, not to exceed serum levels of 1.2 mEq/L. The sample will be evaluated longitudinally using a wide range of clinical scales, cognitive assessments and laboratory tests. On relapse, patients will be discontinued or crossed-over to treatment with valproic acid (VPA) or treatment as usual (TAU). Relapse is defined as a DSM-IV manic, major depressive or mixed episode or if the treating physician decides a change in medication is clinically necessary. The sample will be genotyped for GWAS. The outcome for lithium response will be analyzed as a time to event, where the event is defined as clinical relapse, using a Cox Proportional Hazards model. Positive single nucleotide polymorphisms (SNPs) from past genetic retrospective studies of lithium response, the Consortium on Lithium Genetics (ConLiGen), will be tested in this prospective study sample; a meta-analysis of these samples will then be performed. Finally, neurons will be derived from pluripotent stem cells from lithium responders and non-responders and tested in vivo for response to lithium by gene expression studies. SNPs in genes identified in these cellular studies will also be tested for association to response. Lithium is an extraordinarily important therapeutic drug in the clinical management of patients suffering from bipolar disorder. However, a significant proportion of patients, 30–40 %, fail to respond, and there is currently no method to identify the good lithium responders before initiation of treatment. Converging evidence suggests that genetic factors play a strong role in the variation of response to lithium, but only a few genes have been tested and the samples have largely been retrospective or quite small. The current study will collect an entirely unique sample of 700 patients with bipolar disorder to be stabilized on lithium monotherapy and followed for up to 2 years. This study will produce useful information to improve the understanding of the mechanism of action of lithium and will add to the development of a method to predict individual response to lithium, thereby accelerating recovery and reducing suffering and cost. ClinicalTrials.gov Identifier: NCT01272531 Registered: January 6, 2011
In rat brain, dopaminergic D 2 -like but not D 1 -like receptors can be coupled to phospholipase A 2 (PLA 2 ) activation, to release the second messenger, arachidonic acid (AA, 20:4n-6), from membrane phospholipids. In this study, we hypothesized that D-amphetamine, a dopamine-releasing agent, could initiate such AA signaling. The incorporation coefficient, k ∗ (brain radioactivity/integrated plasma radioactivity) for AA, a marker of the signal, was determined in 62 brain regions of unanesthetized rats that were administered i.p. saline, D-amphetamine (2.5 or 0.5 mg/kg i.p.), or the D 2 -like receptor antagonist raclopride (6 mg/kg, i.v.) before saline or 2.5 mg/kg D-amphetamine. After injecting [1- 14 C]AA intravenously, k ∗ was measured by quantitative autoradiography. Compared to saline-treated controls, D-amphetamine 2.5 mg/kg i.p. increased k ∗ significantly in 27 brain areas rich in D 2 -like receptors. Significant increases were evident in neocortical, extrapyramidal, and limbic regions. Pretreatment with raclopride blocked the increments, but raclopride alone did not alter baseline values of k ∗ . In independent experiments, D-amphetamine 0.5 mg/kg i.p. increased k ∗ significantly in only seven regions, including the nucleus accumbens and layer IV neocortical regions. These results indicate that D-amphetamine can indirectly activate brain PLA 2 in the unanesthetized rat, and that activation is initiated entirely at D 2 -like receptors. D-Amphetamine's low-dose effects are consistent with other evidence that the nucleus accumbens, considered a reward center, is particularly sensitive to the drug.
Abstract Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N=2,367) and replicated in the combined PsyCourse (N=89) and BipoLife (N=102) studies. The associations of Li+PGS and lithium treatment response — defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������
Abstract Background Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.
Incorporation coefficients ( K* ) of arachidonic acid (AA) in the brain are increased in a rat model of neuroinflammation, as are other markers of AA metabolism. Data also indicate that neuroinflammation contributes to Alzheimer's disease (AD). On the basis of these observations, K* for AA was hypothesized to be elevated in patients with AD. Methods: A total of 8 patients with AD with an average (±SD) Mini-Mental State Examination score of 14.7 ± 8.4 (mean age, 71.7 ± 11.2 y) and 9 controls with a normal Mini-Mental State Examination score (mean age, 68.7 ± 5.6 y) were studied. Each subject received a 15O-water PET scan of regional cerebral blood flow, followed after 15 min by a 1-11C-AA scan of regional K* for AA. Results: In the patients with AD, compared with control subjects, global gray matter K* for AA (corrected or uncorrected for the partial-volume error [PVE]) was significantly elevated, whereas only PVE-uncorrected global cerebral blood flow was reduced significantly ( P < 0.05). A false-discovery-rate procedure indicated that PVE-corrected K* for AA was increased in 78 of 90 identified hemispheric gray matter regions. PVE-corrected regional cerebral blood flow, although decreased in 12 regions at P < 0.01 by an unpaired t test, did not survive the false-discovery-rate procedure. The surviving K* increments were widespread in the neocortex but were absent in caudate, pallidum, and thalamic regions. Conclusion: These preliminary results show that K* for AA is widely elevated in the AD brain, particularly in regions reported to have high densities of senile (neuritic) plaques with activated microglia. To the extent that the elevations represent upregulated AA metabolism associated with neuroinflammation, PET with 1-11C-AA could be used to examine neuroinflammation in patients with AD and other brain diseases.
Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.
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