Make lithium great again – Precisely!
| Autor: | Frank Bellivier, Bruno Etain, Allan H. Young, Jan Scott, David A. Cousins |
|---|---|
| Přispěvatelé: | Hôpitaux Universitaire Saint-Louis, Lariboisière, Fernand-Widal, Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), King‘s College London, Newcastle University [Newcastle], Newcastle Upon Tyne Hospitals NHS Foundation Trust, Etain, Bruno |
| Jazyk: | angličtina |
| Předmět: |
Sleep latency
recurrent suicide attempt childhood maltreatment non-coding RNA Meta-regression Comorbidity Clinical markers GWAS genetics Dual diagnosis validation Multi-omics response Energy MESH: Risk burnout substance use disorder Vaccination Laterality Catatonia Genomics Quality Diagnostic delay machine learning Mood stabilisers Suicidal behavior depression treatment-resistant depression Epigenetics levels of analysis Cognitive function addiction dimensions Longitudinal study age at onset post-traumatic MESH: Sex Characteristics medicine.medical_specialty Data set Methylation MESH: Sulfurtransferases Clusters 03 medical and health sciences PSQI Bipolar I disorder LITHIUM USE Functioning Misperception of sleep Transcriptomics Genotype-by-sex interaction MESH: Humans variability patient experience Modifiers transferability biomarkers MESH: Adult MESH: Retrospective Studies Precision medicine Psychosis Pharmacodynamics antecedents major depression MESH: Female Cohorts Youth patient satisfaction Seasonal variation Response variability Practice guidelines Trajectories activity rhythms Argument quality of care Suicide attempt pain Sequence of onset bipolar disorder Psychiatry Maintenance treatment MESH: Suicidal Ideation outcome studies MESH: Depression Postpartum Alda scale Clinical Practice Phenotype biological rhythms Tolerability radiomics biomarker affective symptoms circadian genes medicine.drug mood recurrence Validity of diagnosis DSM-5 health care workers severe mental illness medicine Bipolar disorders morningness Unsupervised machine learning Neurokinetics Sleep duration business.industry illness trajectories COVID-19 Delirium clinical cohort meta-analysis Treatment chronotype Bipolar Systematic review eveningness Delayed early intervention Sleep chronobiology Prediction chronic kidney disease qualitative research actigraphy Lithium (medication) MS-HRM CKD-chronic kidney disease 0302 clinical medicine Cognition circadian gene MESH: Bipolar Disorder Confusion Children DNA methylation MESH: Middle Aged High risk Metabolic syndrome health services research 3. Good health Adolescence Psychiatry and Mental health Transporters Sunlight Infectious diseases light CRP Personality MESH: Cross-Sectional Studies Polygenicity Memory MESH: Sleep Initiation and Maintenance Disorders Polygenic score Sex differences Circadian rhythms mediation Intensive care medicine resilience Medication adherence Biological Psychiatry Pleiotropy Lifestyle Metabolic abnormalities 030227 psychiatry clinical severity 030217 neurology & neurosurgery Sleep efficiency clock gene Neurodevelopment [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health impulsiveness Subtype Alcohol use disorder Cocaine Recurrence MESH: Risk Factors Mood stabilizers magnetic resonance imaging rest Handedness Blood-brain barrier sanitary crisis nephrotoxicity Circadian Cohort Sleep quality animal models side effects serious suicide attempt Mania lithium antidepressants Solar insolation Domains Mood disorders Language disorders MESH: Suicide Attempted patient-reported experience measures lithium response Genetic correlation Genome-wide association study prevalence Family history early life stress Major depressive disorder Follow-up studies comorbidities ICD-11 kidney microcysts Obesity MESH: Patient Acuity First episode Clinical trajectory suicide Plexus choroid childhood trauma outbreak Predictors Hierarchical agglomerative clustering MESH: Quantitative Trait Loci Evidence map MESH: France antipsychotics physical abuse [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health Longitudinal Schizophrenia gene expression expert centres polarity at onset Course business depressive disorders bipolar affective disorders |
| Zdroj: | Bipolar Disorders Bipolar Disorders, Wiley, 2021, 23 (2), pp.209-210. ⟨10.1111/bdi.13023⟩ |
| ISSN: | 1399-5618 1398-5647 |
| DOI: | 10.1111/bdi.13023 |
| Popis: | Background Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest–activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR). Methods Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR). Results Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06). Conclusions To our knowledge, this is the largest actigraphy study of rest–activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups. 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. |
| Databáze: | OpenAIRE |
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