ReviewMetabolism: clinical and experimental2013
Personalized medicine in major depressive disorder -- opportunities and pitfalls.
Review in Metabolism: clinical and experimental, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.
- Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping.Molecular psychiatry · 2019Pooled it
- Exploring venlafaxine pharmacokinetic variability with a phenotyping approach, a multicentric french-swiss study (MARVEL study).BMC pharmacology & toxicology · 2017Trial
- Concerns about unintended negative consequences of informing the public about multifactorial risks may be premature for young adult smokers.British journal of health psychology · 2014Trial
- Review
- Prognostic Significance of Blood-Based Baseline Biomarkers in Treatment-Resistant Depression: A Literature Review of Available Studies on Treatment Response.Brain sciences · 2022Review
- Toward a New Model of Understanding, Preventing, and Treating Adolescent Depression Focusing on Exhaustion and Stress.Frontiers in psychiatry · 2020Article
- Depressive disorders: Treatment failures and poor prognosis over the last 50 years.Pharmacology research & perspectives · 2019Review
- Biomarker-based subtyping of depression and anxiety disorders using Latent Class Analysis. A NESDA study.Psychological medicine · 2019Article
- Prophylactic ketamine alters nucleotide and neurotransmitter metabolism in brain and plasma following stress.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2018Article
- Hippocampal metabolic differences implicate distinctions between physical and psychological stress in four rat models of depression.Translational psychiatry · 2018Article
- Optimization of Antidepressant use with Pharmacogenetic Strategies.Current genomics · 2017Article
- Pharmacogenomics and Global Precision Medicine in the Context of Adverse Drug Reactions: Top 10 Opportunities and Challenges for the Next Decade.Omics : a journal of integrative biology · 2016Review
- Amygdala response to explicit sad face stimuli at baseline predicts antidepressant treatment response to scopolamine in major depressive disorder.Psychiatry research. Neuroimaging · 2016Article
- Genome-wide linkage on chromosome 10q26 for a dimensional scale of major depression.Journal of affective disorders · 2016Article
- Association of Periodontitis and Subsequent Depression: A Nationwide Population-Based Study.Medicine · 2015Observational
- Agomelatine: an agent against anhedonia and abulia?Journal of neural transmission (Vienna, Austria : 1996) · 2015Review
- Rodent models of depression: neurotrophic and neuroinflammatory biomarkers.BioMed research international · 2014Review
- Hands-on workshops as an effective means of learning advanced technologies including genomics, proteomics and bioinformatics.Genomics, proteomics & bioinformatics · 2013Article
- Biomarkers in pediatric depression.Depression and anxiety · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
The sequencing of the human genome in the early days of this millennium was greeted with great fanfare as this accomplishment was expected to revolutionize medicine and result in individualized treatments based on the genetic make-up of the patient. The ultimate promise of personalized medicine would be fulfilled with the identification of disease biomarkers that would be widely available for use in diagnosis and treatment. Progress, however, has been slow in providing disease biomarkers or approved diagnostic tests. This is true for major depressive disorder (MDD), despite its prevalence in the general population and the widespread acceptance of its biological basis. Studies using strategies like genome-wide association and candidate gene analyses have identified a number of possible biomarkers of MDD, including serum levels of neurotrophic factors, inflammatory cytokines and HPA axis hormones, but none have proven sufficiently powerful for clinical use. The lack of biologically based tests available for use in identifying patients with MDD is a significant impediment to personalized and more effective treatment, because it means diagnosis continues to be driven by subjective symptoms. While genetic studies of MDD have not yet led to diagnostic and treatment biomarkers, progress in determining the role of the genome in drug metabolism heralds the first effort in personalized prescribing for the antidepressants. The FDA suggested and approved genotyping tests for common variants of drug metabolism genes, such as the cytochrome p450s. By using these tests a physician can select an appropriate antidepressant for a given patient, as differences in clearance, half-life, and peak blood concentrations are controlled by genetic variability in drug metabolism. Personalization in drug choice can be achieved because these tests: (1) identify responders and non-responders; (2) provide alerts to possible adverse drug events; and (3) help optimize dose. Improved ways of diagnosing and prescribing effective treatments for MDD are needed, as the available methods are inadequate and symptom based. In the foreseeable future, further interrogation of the genome may serve as the basis for development of new personalized medicine strategies for diagnosis and treatment of MDD.
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What OpenQuestion holds
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.