ArticleScientific reports2021
Prediction of lithium response using genomic data.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Optimizing Treatment Strategies in the Bipolar Disorder Spectrum With Classical AI Approaches: Systematic Review of Performance, Bias, and Clinical Applicability.JMIR mental health · 2026Pooled it
- Moving toward precision and personalized treatment strategies in psychiatry.The international journal of neuropsychopharmacology · 2025Review
- New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview.Pharmacological reviews · 2024Review
- Pharmacogenomics and response to lithium in bipolar disorder.Pharmacogenomics · 2024Review
- A review of model evaluation metrics for machine learning in genetics and genomics.Frontiers in bioinformatics · 2024Review
- Lithium rescues dendritic abnormalities in Ank3 deficiency models through the synergic effects of GSK3β and cyclic AMP signaling pathways.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2023Article
- Candidate biomarkers in psychiatric disorders: state of the field.World psychiatry : official journal of the World Psychiatric Association (WPA) · 2023Article
- Recommendations, guidelines, and best practice for the use of human induced pluripotent stem cells for neuropharmacological studies of neuropsychiatric disorders.Neuroscience applied · 2023Review
- Barriers to genetic testing in clinical psychiatry and ways to overcome them: from clinicians' attitudes to sociocultural differences between patients across the globe.Translational psychiatry · 2022Review
- A Comparison of Different Approaches to Clinical Phenotyping of Lithium Response: A Proof of Principle Study Employing Genetic Variants of Three Candidate Circadian Genes.Pharmaceuticals (Basel, Switzerland) · 2021Article
- Pharmacogenomics of Lithium Response in Bipolar Disorder.Pharmaceuticals (Basel, Switzerland) · 2021Review
Corrections and comments
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Authors and funding
53 authors.
Funding
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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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.