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Depression or major depressive disorder (MDD) is a multifactorial psychiatric condition. Individuals with depression often find themselves in a persistently low mood, anhedonia (inability to feel pleasure), cognitive disturbances, and other symptoms that impair daily functioning.
Read our popular deep-dive on the Genetics of Depression
According to epidemiological data a lifetime prevalence of depression is approaching 15-20 % worldwide. Primary cause arises from complex interactions of genetics, neurochemical imbalance, dysregulated stress-axis activity, and environmental stress factors.
Brain research shows that depression is linked to fewer mood-related neurotransmitters, disrupted glutamate activity, a smaller hippocampus, and poor communication between brain areas that control emotion and thinking. Converging evidence also highlights inflammatory processes and neurotrophic deficits, particularly decreased brain-derived neurotrophic factor (BDNF) expression, as contributors to disease onset and progression.
Antidepressants help correct chemical imbalances in the brain that are linked to depression. Most work by increasing the levels of mood-related neurotransmitters such as serotonin, norepinephrine, or dopamine. By restoring these signals, the drugs can lift mood, improve sleep and appetite, and reduce anxiety. They usually take a few weeks to reach full effect and should be used under a doctor’s guidance.
Antidepressant prescribing still relies heavily on trial-and-error. Around one-third of patients achieve remission with the first drug they receive, while many experience delayed benefit or troublesome side-effects. Pharmacogenomics, the study of how genetic variation influences drug response, offers a path out of this uncertainty. Over the past decade, and especially since 2023, large-scale studies and guideline updates have clarified which genes are involved, how strongly they affect efficacy and tolerability, and when testing should guide routine care.
Serotonin-reuptake inhibitors (SSRIs)
SSRIs are a common class of antidepressant medicines that raise the level of serotonin. Serotonin is a chemical that helps regulate mood, and SSRIs act by blocking its re-absorption (reuptake) into the brain’s nerve cells after it is released. With more serotonin remaining active in the synapse (the space between two nerve cells), communication between neurons improves, which over several weeks can lift mood, reduce anxiety, and ease other depressive symptoms.
Drugs such as fluoxetine, sertraline, and escitalopram belong to this group and are generally favored because they are effective, easy to dose, and safer than older antidepressants. However, they can still cause side effects like nausea, headache, or sleep changes and should be taken under medical supervision.
Core Genes: CYP2D6 and CYP2C19
CYP2D6 and CYP2C19 are genes that encode specific liver-based cytochrome P450 enzymes critical for drug metabolism. Most SSRIs are metabolised by cytochrome P450 enzymes.
Alleles that reduce or stop the activity of CYP2D6 or CYP2C19 slow the serotonin clearance, leading to higher plasma levels, whereas increased-function alleles accelerate clearance and can lead to sub-therapeutic exposure.
- CYP2D6 (chromosome 22q13) produces the CYP2D6 mono-oxygenase, which oxidizes roughly 20–25 % of all prescribed drugs, including many antidepressants (e.g., paroxetine, venlafaxine). It is highly polymorphic: more than 150 star-allele gene variants have been catalogued that can stop, reduce, normalise, or increase enzyme activity, giving rise to poor, intermediate, normal, or ultra-rapid metaboliser phenotypes.
- CYP2C19 (chromosome 10q24) encodes CYP2C19, an enzyme that metabolises selective serotonin-reuptake inhibitors (escitalopram, sertraline). Like CYP2D6, the gene is highly variable, with common loss-of-function alleles (*2, *3) and a gain-of-function allele (*17) that respectively slow or speed drug clearance.
Because these variants can markedly alter plasma drug levels, clinical pharmacogenomic guidelines (e.g., CPIC, DPWG) recommend genotype-guided dosing or drug selection for medications that are substantially cleared by either enzyme to improve efficacy and reduce adverse effects.
In April 2023 the Clinical Pharmacogenetics Implementation Consortium (CPIC) updated its guideline, expanding the genotypes covered and providing concrete dose or drug-switch recommendations for 18 antidepressants. For example, for the SSRI escitalopram, CPIC recommends a 50% dose reduction or an alternative agent in CYP2C19 poor metabolisers, and avoiding paroxetine in CYP2D6 poor metabolisers altogether.
Clinical impact is now supported by meta-analysis: patients whose treatment was guided by a multi-gene panel, including CYP2D6 and CYP2C19, were 41-78 % more likely to achieve remission than those treated as usual. Importantly, the benefit was confined to randomised controlled trials, underscoring the need for rigorous implementation rather than opportunistic testing.
Transporters, Receptors and Downstream signalling
Drug concentration at the synapse is only half the story; neuronal response is equally shaped by the receptor and transporter genes.
SLC6A4 Gene
SLC6A4 (solute carrier family 6 member 4) is the gene that encodes the serotonin transporter (often abbreviated SERT or 5-HTT), a membrane protein responsible for pumping serotonin back into presynaptic neurons after it has been released into the synaptic cleft. SLC6A4 gene is highly polymorphic. The best-studied variant is the serotonin-transporter-linked polymorphic region 5-HTTLPR located at the gene’s promoter, which exists mainly as long (L) and short (S) alleles; the S allele reduces transcription, leading to fewer transporters and altered serotonin tone.
Variants in SLC6A4, notably the L and S promoter repeat alleles, influence transcription and thus transporter density. Some, but not all studies link the L allele to greater SSRI response, while the S allele heightens the risk of gastrointestinal side-effects.
A 2020 review of 49 studies found that people with major depression who carry the L form of the 5-HTTLPR variant in the SLC6A4 gene respond better to SSRI antidepressants than those with two S copies, but this benefit was clear only in Caucasian patients and did not appear in Asian groups or in studies using mixed drug classes.
CPIC now classifies the S/S genotype as “possible reduced benefit” but does not yet mandate a dose change.
Recent scientific updates
A study published in May of this year (2025) of 302 European patients with depression or anxiety who failed previous SSRI treatment found that certain genetic combinations in the serotonin system were much more common than in the general population. Patients carrying at least one G allele of the HTR1A rs6295 variant together with the short/short (SS) form of the SLC6A4 promoter variant 5-HTTLPR had the highest over-representation among those with failed treatment—about 74 % above expectations—suggesting this pairing greatly increases the risk of SSRI non-response and associated disability. The findings indicate that genotyping both the serotonin transporter (SLC6A4) and its autoreceptor (HTR1A) could help predict treatment failure and guide more effective antidepressant choices.
HTR2A and Other Genes
Serotonin-2A receptor (HTR2A) polymorphisms, particularly rs7997012, and BDNF Val66Met (rs6265) have been repeatedly associated with differential remission rates, although effect sizes are modest. A 2024 genome-wide association study (GWAS) in an Indian cohort added weight by identifying HTR2A and other synaptic signalling loci among the top hits for inadequate treatment response.
Moreover, downstream stress-axis genes such as FKBP5, which regulates glucocorticoid receptor sensitivity, may explain why some patients develop early adverse reactions or emotional blunting. Evidence here is still emerging, and no prescribing guideline incorporates these variants yet.
Ancestry
Most pharmacogenomic evidence has historically been derived from European populations, but allele frequencies can diverge widely among others.
For instance, the CYP2C19*17 ultra-rapid allele is common in Northern Europeans yet rare in East Asians, whereas CYP2C19 loss-of-function alleles *2 and *3 occur in up to 20 % of Han Chinese. The 2024 Indian GWAS illustrates how locally generated data can uncover novel loci and improve predictive accuracy for the millions of patients in South Asia.
Beyond efficacy: genetics of adverse effects and withdrawal
Genes that influence transporter affinity or membrane pumps such as ABCB1 (P-glycoprotein) modulate central nervous system exposure and have been linked to sedation and weight gain. Meanwhile, emerging evidence suggests genetic predisposition to a difficult withdrawal: a 2024 meta-analysis noted that 43 % of long-term users experience discontinuation symptoms, with risk rising in CYP2D6 poor metabolisers who accumulate active drugs. Personalised tapering schedules based on metabolic genotype may therefore reduce withdrawal burden.
Clinical implementation: where testing is recommended today
International guidelines converge on three practical principles:
- Test before first prescription when using drugs for which genotype-based dose recommendations are clear (e.g., tricyclics, paroxetine, escitalopram, sertraline).
- Consider testing after inadequate response or intolerable side-effects to guide the next choice.
- Interpret results in context—age, comorbidities, and drug interactions can mimic genetic slow metabolism.
Health-system pilot studies show that pre-emptive panels integrated into electronic medical records are cost-effective, reducinghospitalisations from adverse reactions within two years of deployment. Some private insurances in the United States and several European countries now reimburse panel testing when guideline criteria are met.
Limitations and future directions of genetic testing
- Genetic effect sizes are moderate. Genetics sets the range of likely outcomes, but environment, adherence, and placebo effects still contribute heavily.
- Rare variants remain underexplored. Whole-genome sequencing is starting to reveal private mutations in CYP genes that conventional panels miss.
- Multi-omics approaches beckon. Transcriptomic and metabolomic signatures measured at baseline may complement static DNA data, capturing dynamic state factors such as inflammation.
- Ethical considerations. Testing can stigmatise or raise privacy concerns; informed consent and clear communication are essential.
The next frontier is adaptive prescribing algorithms that combine individual genotypes, Polygenic Risk Scores (PRS) , real-time mood rating and wearable-derived sleep data to adjust treatment weeks earlier than what is possible in today’s practice.
Conclusion
Genetic insights are already refining antidepressant therapy, moving psychiatry toward the precision enjoyed in oncology and cardiology. Testing for CYP2D6 and CYP2C19 variants has immediate, guideline-backed utility, while accumulating evidence on transporter variants and advanced PRS models promise progressively finer tailoring. Widespread implementation will require equitable sequencing across ancestries, clinician education, and integration with clinical decision support. Yet the trajectory is clear: as our understanding of the genetic response to antidepressants deepens, the era of “fail first, switch later” is giving way to informed, patient-specific care—offering faster relief and fewer harms for millions living with depression.
Reference
- https://pmc.ncbi.nlm.nih.gov/articles/PMC5640125/
- https://cpicpgx.org/guidelines/cpic-guideline-for-ssri-and-snri-antidepressants/
- https://www.frontiersin.org/journals/psychiatry/articles/10.3389/fpsyt.2024.1276410/
- https://www.sciencedirect.com/science/article/abs/pii/S0165032720305188
- https://www.nature.com/articles/s41397-025-00370-5
- https://www.medrxiv.org/content/10.1101/2024.11.25.24317869v1.full-text