| Title |
Suicidal Ideation during Antidepressant Treatment
|
|---|---|
| Published in |
CNS Drugs, August 2012
|
| DOI | 10.2165/11589420-000000000-00000 |
| Pubmed ID | |
| Authors |
Nader Perroud |
| Abstract |
Suicidal thoughts during antidepressant treatment have recently been the focus of several candidate gene and genome-wide association studies. Although the clinical risk factors for such events are well known, unfortunately they do not help to predict who will have a suicidal event during antidepressant treatment and who will not. Pharmacogenomic studies have therefore attempted to use genetic variants to predict individual susceptibility to treatment-related suicidal ideation. In this perspective, several genetic predictors have been highlighted, the majority of which relate to common mechanisms of antidepressant action: genes involved in the neurotrophic and synaptic plasticity systems (CREB1, and BDNF and its receptor NTRK2), noradrenergic system (ADRA2A), glutamatergic system (GRIA3, GRIK2 and GDA), inflammatory and hypothalamic-pituitary-adrenal (HPA) axis systems (IL28RA and FKBP5) and in other brain functions (PAPLN, APOO, KCNIP4 and ELP3). Although some of these genes may be of interest in predicting antidepressant-induced suicidal ideation, they still need to be validated in better phenotypically designed samples. Several methodological factors are indeed responsible for the problems involved in implicating these findings in the causation of a clinically relevant phenotype. These include discrepancies between studies in defining phenotypes, with several different thresholds used to establish significant suicidal ideation; the use of scales not truly designed to measure suicidal ideation; and the paucity of true suicidal events (suicide attempts and/or completion) in pharmacogenomic studies. In conclusion, pharmacogenomic studies are far from fulfilling their promise. There is a need for future pharmacogenetic studies targeting events that are clinically significant in order to find associated variants that will help clinicians to improve their treatment strategies. While awaiting these genetic predictors, clinicians need to bear in mind that all studies in this field support a beneficial effect of antidepressants on suicidal ideation. This should therefore encourage them to prescribe antidepressant medication even in patients with suicidal ideation. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 54 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 2% |
| United States | 1 | 2% |
| Unknown | 52 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 9 | 17% |
| Student > Bachelor | 7 | 13% |
| Student > Master | 6 | 11% |
| Researcher | 5 | 9% |
| Professor > Associate Professor | 4 | 7% |
| Other | 8 | 15% |
| Unknown | 15 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 26% |
| Psychology | 6 | 11% |
| Neuroscience | 5 | 9% |
| Agricultural and Biological Sciences | 3 | 6% |
| Nursing and Health Professions | 2 | 4% |
| Other | 7 | 13% |
| Unknown | 17 | 31% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 02 January 2012.
All research outputs
#16,580,157
of 25,374,647 outputs
Outputs from CNS Drugs
#1,133
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#120,164
of 187,950 outputs
Outputs of similar age from CNS Drugs
#494
of 541 outputs
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