1. |
- Blokland, G. A. M., et al.
(author)
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Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders
- 2022
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In: Biological Psychiatry. - : Elsevier BV. - 0006-3223 .- 1873-2402. ; 91:1, s. 102-117
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Journal article (peer-reviewed)abstract
- Background: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. Methods: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. Results: Across disorders, genome-wide significant single nucleotide polymorphism–by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10−8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10−6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10−7; rs73033497, p = 8.8 × 10−7; rs7914279, p = 6.4 × 10−7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10−7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10−7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10−7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). Conclusions: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels. © 2021 Society of Biological Psychiatry
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2. |
- Mullins, N., et al.
(author)
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Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology
- 2021
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In: Nature Genetics. - : Springer Science and Business Media LLC. - 1061-4036 .- 1546-1718. ; 53, s. 817-829
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Journal article (peer-reviewed)abstract
- Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies. Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.
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3. |
- Le Clerc, S., et al.
(author)
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HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders
- 2021
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1
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Journal article (peer-reviewed)abstract
- Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 x 10(-3); FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.
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4. |
- Amare, A. T., et al.
(author)
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Association of polygenic score for major depression with response to lithium in patients with bipolar disorder
- 2021
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In: Molecular Psychiatry. - : Springer Science and Business Media LLC. - 1359-4184 .- 1476-5578. ; 26, s. 2457-2470
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Journal article (peer-reviewed)abstract
- Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi(+)Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.
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5. |
- Cearns, M., et al.
(author)
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- 2022
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In: British Journal of Psychiatry. - : Royal College of Psychiatrists. - 0007-1250 .- 1472-1465. ; 220:4, s. 219-228
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Journal article (peer-reviewed)abstract
- Background Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. Aims To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. Method This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi(+)Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. Results The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. Conclusions Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
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8. |
- Schubert, K. O., et al.
(author)
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Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients
- 2021
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In: Translational Psychiatry. - : Springer Science and Business Media LLC. - 2158-3188. ; 11:1
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Journal article (peer-reviewed)abstract
- Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi(+)Gen; ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.
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14. |
- Martinsson, I, et al.
(author)
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Aβ/APP-induced hyperexcitability and dysregulation of homeostatic synaptic plasticity in models of Alzheimer’s disease
- 2022
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Other publication (other academic/artistic)abstract
- The proper function of the nervous system is dependent on the appropriate timing of neuronal firing. Synapses continually undergo rapid activity-dependent modifications that require feedback mechanisms to maintain network activity within a window in which communication is energy efficient and meaningful. Homeostatic synaptic plasticity (HSP) and homeostatic intrinsic plasticity (HIP) are such negative feedback mechanisms. Accumulating evidence implicates that Alzheimer’s disease (AD)-related amyloid precursor protein (APP) and its cleavage product amyloid-beta (Aβ) play a role in the regulation of neuronal network activity, and in particular HSP. AD features impaired neuronal activity with regional early hyper-activity and Aβ-dependent hyperexcitability has also been demonstrated in AD transgenic mice. We demonstrate similar hyper-activity in AD transgenic neurons in culture that have elevated levels of both human APP and Aβ. To examine the individual roles of APP and Aβ in promoting hyperexcitability we used an APP construct that does not generate Aβ, or elevated Aβ levels independently of APP. Increasing either APP or Aβ in wild type (WT) neurons leads to increased frequency and amplitude of calcium transients. Since HSP/HIP mechanisms normally maintain a setpoint of activity, we examined whether homeostatic synaptic/intrinsic plasticity was altered in AD transgenic neurons. Using methods known to induce HSP/HIP, we demonstrate that APP protein levels are regulated by chronic modulation of activity and show that AD transgenic neurons have an impaired response to global changes in activity. Further, AD transgenic compared to WT neurons failed to adjust the length of their axon initial segments (AIS), an adaptation known to alter excitability. Thus, we present evidence that both APP and Aβ influence neuronal activity and that mechanisms of HSP/HIP are disrupted in neuronal models of AD.Competing Interest StatementThe authors have declared no competing interest.
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- Millischer, V., et al.
(author)
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Improving lithium dose prediction using population pharmacokinetics and pharmacogenomics: a cohort genome-wide association study in Sweden
- 2022
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In: Lancet Psychiatry. - 2215-0374. ; 9:6, s. 447-457
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Journal article (peer-reviewed)abstract
- 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 (BipolaR). 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, BipolaR, 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 [R-2]: R-cohort1(2)=0.41 and R-cohort2(2)=0.31; both p<0.0001), sex (R-cohort1(2)=0.0063 [p=0.045] and R-cohort2(2)=0.026 [p<0.0001]), eGFR (R-cohort1(2)=0.38 and R-cohort2(2)=0.0; both p<0.0001), comedication with diuretics (R-cohort1(2)=0.0058 [p=0.014] and R-cohort2(2)=0.0026 [p<0.0001]), and agents acting on the renin-aldosterone-angiotensin system (R-cohort1(2)=0.028 and R-cohort2(2)=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 (R-cohort1(2)=0.13 and R-cohort2(2)=0.15; both p<0.0001). In a GWAS of CLLi,age/sex, one locus was associated with a change in CLLi (rs583503; beta=-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. Copyright (C) 2022 Elsevier Ltd. All rights reserved.
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17. |
- Ou, Anna H., et al.
(author)
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Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study
- 2024
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In: TRANSLATIONAL PSYCHIATRY. - 2158-3188. ; 14:1
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Journal article (peer-reviewed)abstract
- Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.
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18. |
- Schunk, Stefan J., et al.
(author)
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Genetically determined NLRP3 inflammasome activation associates with systemic inflammation and cardiovascular mortality
- 2021
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In: European Heart Journal. - : Oxford University Press. - 0195-668X .- 1522-9645. ; 42:18, s. 1742-1756
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Journal article (peer-reviewed)abstract
- AimsInflammation plays an important role in cardiovascular disease (CVD) development. The NOD-like receptor protein-3 (NLRP3) inflammasome contributes to the development of atherosclerosis in animal models. Components of the NLRP3 inflammasome pathway such as interleukin-1β can therapeutically be targeted. Associations of genetically determined inflammasome-mediated systemic inflammation with CVD and mortality in humans are unknown.Methods and resultsWe explored the association of genetic NLRP3 variants with prevalent CVD and cardiovascular mortality in 538 167 subjects on the individual participant level in an explorative gene-centric approach without performing multiple testing. Functional relevance of single-nucleotide polymorphisms on NLRP3 inflammasome activation has been evaluated in monocyte-enriched peripheral blood mononuclear cells (PBMCs). Genetic analyses identified the highly prevalent (minor allele frequency 39.9%) intronic NLRP3 variant rs10754555 to affect NLRP3 gene expression. rs10754555 carriers showed significantly higher C-reactive protein and serum amyloid A plasma levels. Carriers of the G allele showed higher NLRP3 inflammasome activation in isolated human PBMCs. In carriers of the rs10754555 variant, the prevalence of coronary artery disease was significantly higher as compared to non-carriers with a significant interaction between rs10754555 and age. Importantly, rs10754555 carriers had significantly higher risk for cardiovascular mortality during follow-up. Inflammasome inducers (e.g. urate, triglycerides, apolipoprotein C3) modulated the association between rs10754555 and mortality.ConclusionThe NLRP3 intronic variant rs10754555 is associated with increased systemic inflammation, inflammasome activation, prevalent coronary artery disease, and mortality. This study provides evidence for a substantial role of genetically driven systemic inflammation in CVD and highlights the NLRP3 inflammasome as a therapeutic target.
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19. |
- Stone, W, et al.
(author)
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Prediction of lithium response using genomic data
- 2021
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In: Scientific reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11:1, s. 1155-
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Journal article (peer-reviewed)abstract
- 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.
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21. |
- Amare, Azmeraw, et al.
(author)
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Association of Polygenic Score and the involvement of Cholinergic and Glutamatergic Pathways with Lithium Treatment Response in Patients with Bipolar Disorder.
- 2023
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In: Research square. - : Research Square Platform LLC.
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Journal article (peer-reviewed)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<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.
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22. |
- Amare, Azmeraw T, et al.
(author)
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Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.
- 2023
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In: Molecular psychiatry. - 1476-5578. ; 28, s. 5251-5261
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Journal article (peer-reviewed)abstract
- Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental healthdisorder 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=2367) 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<0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P=9.8×10-12, R2=1.9%) and continuous (P=6.4×10-9, R2=2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P=3.9×10-4, R2=0.9%), but not for the continuous outcome (P=0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.
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- Bokhari, Abdulmalik, et al.
(author)
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Novel human-derived EML4-ALK fusion cell lines identify ribonucleotide reductase RRM2 as a target of activated ALK in NSCLC
- 2022
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In: Lung Cancer. - : Elsevier BV. - 0169-5002. ; 171, s. 103-114
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Journal article (peer-reviewed)abstract
- Introduction: Echinoderm microtubule-associated protein-like 4 (EML4)-Anaplastic Lymphoma Kinase (ALK) rearrangements occur in 3% to 7% of lung adenocarcinomas and are targets for treatment with tyrosine kinase inhibitors (TKIs). Here we have developed three novel EML4-ALK-positive patient–derived Non-Small-Cell-Lung-Cancer (NSCLC) cancer cell lines, CUTO8 (variant 1), CUTO9 (variant 1) and CUTO29 (variant 3) and included a fourth ALK-positive cell line YU1077 (variant 3) to study ALK-positive signaling and responses. Variants 1 and 3 are the most common EML4-ALK variants expressed in ALK-positive NSCLC, and currently cell lines representing these EML4-ALK variants are limited. Materials and methods: Resazurin assay was performed to evaluate cell viability. Protein levels were determined using western blotting. RNA sequencing was performed in all four cell lines to identify differentially expressed genes. Whole-genome sequencing was performed to determine the presence of EML4-ALK fusion and ALK tyrosine kinase inhibitor resistance mutations. Results: In this study, we have confirmed expression of the corresponding ALK fusion protein and assessed their sensitivity to a range of ALK tyrosine kinase inhibitors. These patient derived cell lines exhibit differential sensitivity to lorlatinib, brigatinib and alectinib, with EML4-ALK variant 3 containing cell lines exhibiting increased sensitivity to lorlatinib and brigatinib as compared to alectinib. These cell lines were further characterized by whole genome sequencing and RNA-seq analysis that identified the ribonucleotide reductase regulatory subunit 2 (RRM2) as a downstream and potential therapeutic target in ALK-positive NSCLC. Conclusion: We provide a characterization of four novel EML4-ALK-positive NSCLC cell lines, highlighting genomic heterogeneity and differential responses to ALK TKI treatment. The RNA-Seq characterization of ALK-positive NSCLC CUTO8, CUTO9, CUTO29 and YU1077 cell lines reported here, has been compiled in an interactive ShinyApp resource for public data exploration (https://ccgg.ugent.be/shiny/nsclc_rrm2_2022/).
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