Epigenome-wide DNA methylation in unipolar depression: predictive biomarker of antidepressant treatment response?
Open accessAbstract
Background: Despite the well-documented efficacy of antidepressant agents for the treatment of major depressive disorder (MDD), initial treatment nonresponse rates are high. Recent years have seen an increase in research into predictive biomarkers toward improving diagnosis and individualized treatment. Among those, epigenetic mechanisms such as DNA methylation constitute promising candidate markers in predicting antidepressant treatment response in MDD. The present study sought to address epigenome-wide DNA methylation as a predictor of antidepressant treatment response in the largest sample to date of patients with MDD. Methods: Epigenome-wide DNA methylation was analyzed using the Infinium MethylationEPIC BeadChip in peripheral blood of n = 230 Caucasian patients with MDD receiving 6-week antidepressant treatment in a naturalistic in-patient setting as well as in a subsample of n = 107 patients primarily receiving continuous treatment with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors. Treatment response was assessed by means of the Hamilton Depression Scale. Results: No genome-wide significant hits were observed. Suggestive (P < 1E-5) epigenome-wide evidence was discerned for altered DNA methylation at 6 CpG sites (LOC102724467, LOC100506023, RSPO2, SAG, IL16, PRKCI) to predict response to naturalistic antidepressant treatment. In patients treated with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors, differential DNA methylation at 11 CpGs, for example, mapping to the TIMP2, VDAC1, or SORL1 genes, was suggestively associated with treatment response. Conclusions: The present results provide preliminary evidence for altered DNA methylation patterns to be associated with antidepressant treatment response in MDD. Provided significant replication in independent and larger samples, the present findings might in the future aid in clinical decision-making toward more individualized and thus more efficacious treatments of MDD.
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Written from the paper’s full text.
TL;DR
In the largest sample to date of patients with major depressive disorder, epigenome-wide DNA methylation in peripheral blood yielded no genome-wide significant predictors of 6-week antidepressant treatment response, but suggestive associations emerged at 6 CpGs in the overall naturalistic sample (n = 230) and 11 CpGs in an SSRI/SNRI subsample (n = 107). The authors conclude these preliminary findings require replication before any clinical use.
Key findings
- In n = 230 naturalistically treated MDD patients, no genome-wide significant hits were observed; suggestive evidence (P < 1E-5) was found for altered DNA methylation at 6 CpG sites mapping to LOC102724467, LOC100506023, RSPO2, SAG, IL16, and PRKCI.
- In the n = 107 subsample treated primarily and continuously with SSRIs or SNRIs, differential DNA methylation at 11 CpGs was suggestively associated with treatment response, including CpGs mapping to TIMP2, VDAC1, and SORL1; the strongest listed signals were cg26967050 (MIR9-3HG; coefficient 221.84, P = 3.2E-07) and cg03308985 (DGCR6L; coefficient 569.22, P = 3.49E-07).
- The identified hits did not overlap with CpGs associated with antidepressant treatment response in previous EWAS, nor with genes from genome-wide association meta-analyses of antidepressant response/treatment-resistant depression.
- Genomic inflation was lambda = 1.06 for the whole sample and 0.97 for the SSRI/SNRI subsample; one suggestive CpG (cg04099436) was omitted because it was flagged for cross-reactivity.
Methods
- Naturalistic inpatient cohort recruited at the University of Muenster, Germany (2004–2011): n = 236 MDD patients initially, with DNA methylation and complete clinical data available for n = 230 in the overall treatment-prediction analysis and n = 107 in the SSRI/SNRI subsample; inclusion required DSM-IV MDD, European ancestry, and antidepressant treatment for at least 6 consecutive weeks.
- Epigenome-wide DNA methylation was measured in EDTA blood at admission using the Infinium MethylationEPIC BeadChip (~865,000 sites), processed with a modified CPACOR pipeline; treatment response was defined as change in HAM-D score from week 1 to week 6.
- Linear regression used DNA methylation β-values as predictors, adjusted for the first 5 principal components of control probes, HAM-D score at admission, age, sex, and DNA methylation at cg05575921 in AHRR as a smoking proxy; significance threshold was P < 5.77E-8 (Bonferroni for 865,859 CpGs), with P < 1E-5 considered suggestive.
Limitations
- The paper states that DNA methylation was measured in peripheral blood, precluding direct conclusions about central processes; validation is needed using postmortem brain, animal models, or in silico tools, which do not cover all EPIC CpGs or all relevant brain regions.
- The naturalistic design used varying drug classes and dosages, allowed drug initiation/discontinuation and co-medication, and cannot exclude co-medication or drug effects as confounders; smoking information was unavailable, though AHRR cg05575921 methylation was used as a proxy.
- The authors state the sample size is still moderate and may be underpowered for small effects, warranting replication in larger samples; evident from the text, the findings are only suggestive with no genome-wide significant hits, and the sample was restricted to European ancestry, limiting generalizability.
Model-written summary. Check it against the paper before relying on it.
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Claims the paper makes
0 of 42 cited sources checked · 0 supported · 0 flagged
- Findingown data
In the overall sample of MDD patients, no genome-wide significant hits were observed for DNA methylation predicting antidepressant treatment response.
“In the overall sample of MDD patients, no genome-wide significant hits were observed.”
Quote in the paperSubstantial claim - Findingown data
In the subsample of MDD patients primarily and continuously treated with SSRIs or SNRIs, differential DNA methylation at 11 CpGs was suggestively associated with treatment response.
“In patients primarily and continuously treated with SSRIs or SNRIs, differential DNA methylation at 11 CpGs was suggestively associated with treatment response”
Quote in the paperSubstantial claim - Findingown data
The 6 CpG sites suggestively predicting response to naturalistic antidepressant treatment map to the LOC102724467, LOC100506023, RSPO2, SAG, IL16, and PRKCI genes.
“These CpGs map to genes affiliated with the long noncoding RNA (lncRNA) class (LOC102724467, LOC100506023) or coding for the R-Spondin 2 (RSPO2), S-Antigen Visual Arrestin (SAG), Interleukin 16 (IL16), and Protein Kinase C Iota (PRKCI) genes”
Quote in the paperSubstantial claim - Findingown data
Suggestive (P < 1E-5) epigenome-wide evidence was discerned for altered DNA methylation at 6 CpG sites to predict response to naturalistic antidepressant treatment in the overall sample of MDD patients.
“Suggestive (P < 1E-5) epigenome-wide evidence was discerned for altered DNA methylation at 6 CpG sites (LOC102724467, LOC100506023, RSPO2, SAG, IL16, PRKCI) to predict response to naturalistic antidepressant treatment.”
Quote in the paperSubstantial claim - Findingown data
The 11 CpGs suggestively associated with treatment response in the SSRI/SNRI subsample map to genes including TIMP2, VDAC1, and SORL1.
“mapping for instance to the Tissue Metalloproteinase 2 (TIMP2), Voltage Dependent Anion Channel 1 (VDAC1), or Sortilin Related Receptor (SORL1) genes”
Quote in the paperNot a substantial claim
- Findingown data
The presently identified hits did not overlap with CpGs associated with antidepressant treatment response in previous EWAS.
“The presently identified hits did not overlap with CpGs associated with antidepressant treatment response in previous EWAS (cf. Takeuchi et al., 2017; Ju et al., 2019; Martinez-Pinteno et al., 2021; Engelmann et al., 2022).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites Takeuchi et al., 2017 source
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- cites Ju et al., 2019
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- cites Martinez-Pinteno et al., 2021
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- Findingcitation
There was no overlap between presently identified suggestive associations and findings from a methylome study in electroconvulsive therapy.
“there was no overlap with findings from a methylome study in electroconvulsive therapy (Sirignano et al., 2021).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Sirignano et al., 2021 source
Not checked in the free run.
- Findingown data
Cross-referencing of presently identified hits with the 10 CpGs reported to be associated with antidepressant use in a recent EWAS did not reveal any overlap.
“However, cross-referencing of the presently identified hits suggestively predicting antidepressant treatment response with the 10 CpGs reported to be associated with antidepressant use in a recent EWAS (Barbu et al., 2022) did not reveal any overlap.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Barbu et al., 2022 source
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- Findingown data
Results compared with genome-wide association meta-analyses did not yield any overlap with the genes identified in the present study.
“Additionally, results were compared with those from genome-wide association meta-analyses (Fabbri et al., 2019; Li et al., 2020), which did not yield any overlap with the genes identified in the present study.”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Fabbri et al., 2019 source
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- cites Li et al., 2020
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- Premisecitation
Only 4 pilot studies have investigated genome-wide DNA methylation patterns for their potential as predictors of response to pharmacological antidepressant treatment.
“Thus far, only 4 pilot studies have investigated genome-wide DNA methylation patterns for their potential as predictors of response to pharmacological antidepressant treatment”
Quote in the paperSubstantial claim0 of 3 sources checked- cites Takeuchi et al. (2017) source
Not checked in the free run.
- cites Ju et al., 2019
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- cites Martinez-Pinteno et al., 2021
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- Premisereasoning
The present study is the largest sample to date of MDD patients treated in a naturalistic setting for epigenome-wide DNA methylation analysis of antidepressant treatment response.
“in the largest sample to date of MDD patients treated in a naturalistic setting”
Quote in the paperNot a substantial claim - Interpretationown data
Present results provide preliminary suggestive evidence for novel epigenetic candidates to possibly be associated with antidepressant treatment response in MDD in a naturalistic in-patient treatment setting.
“Taken together, the present results provide preliminary suggestive evidence for novel epigenetic candidates to possibly be associated with antidepressant treatment response in MDD in a naturalistic in-patient treatment setting.”
Quote in the paperSubstantial claim- Rests on an assumption: MIR9-3HG, LOC341056, and B3GALNT2 have not been reported to be related to a mental disorder phenotype before.
- Study design and conductcitation
Correction for methylation at cg05575921 within AHRR as an established proxy for smoking status was applied in the presently described treatment prediction analyses to account for the potentially confounding effect of nicotine smoking.
“However, correction for methylation at cg05575921 within the aryl hydrocarbon receptor (AHR) repressor gene (AHRR) as an established proxy for smoking status (cf. Zeilinger et al., 2013) was applied in the presently described treatment prediction analyses to account for the potentially confounding effect of nicotine smoking.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Zeilinger et al., 2013 source
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- Study design and conductreasoning
Co-medication cannot be excluded as a potential confounding source on the present results.
“Still, co-medication cannot be excluded as a potential confounding source on the present results.”
Quote in the paperNot a substantial claim - Interpretationown data
Peripheral blood determination precludes direct conclusions regarding central processes.
“Epigenome-wide DNA methylation was determined in peripheral blood samples, thus precluding direct conclusions regarding central processes.”
Quote in the paperSubstantial claim - Interpretationcitation
Presently identified suggestive associations may be specific to pharmacological treatment.
“The presently identified suggestive associations may also be specific to pharmacological treatment as there was no overlap with findings from a methylome study in electroconvulsive therapy (Sirignano et al., 2021).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Sirignano et al., 2021 source
Not checked in the free run.
- Study design and conductnone given
All patients included in the present study received serotonergic antidepressants as their primary medication.
“While all patients included in the present study received serotonergic antidepressants as their primary medication”
Quote in the paperNot a substantial claim
- Classified as probably not a substantial claim. 30
- May combine two claims. 12
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationDGCR6L has been shown to interact with the gamma-aminobutyric acid GABA-B1 receptor subunit and to be related to anxiety in children with chromosome 22q11.2 deletion syndrome as well as to schizophrenia.
“the DiGeorge critical region 6 and its duplication (DGCR6L) have been shown to interact with the gamma-aminobutyric acid GABA-B1 receptor subunit (Zunner et al., 2010) and to be related to anxiety in children with chromosome 22q11.2 deletion syndrome (Das Chakraborty et al., 2012) as well as to schizophrenia (Liu et al., 2002).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductown dataNone of the CpGs overlapped with single nucleotide polymorphisms (distance to SNP ≤5 base pairs and European ancestry-based minor allele frequency ≥0.01).
“None of the CpGs overlapped with single nucleotide polymorphisms (distance to single nucleotide polymorphism ≤5 base pairs and European ancestry–based minor allele frequency ≥0.01).”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenThe lncRNA gene LOC102724467 has not previously been linked to mental disorder phenotypes.
“The lncRNA gene LOC102724467 has not previously been linked to mental disorder phenotypes.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationInterleukin 16 protein levels have been reported to be altered in serum samples of MDD patients and to be associated with symptom severity in schizophrenia.
“interleukin 16 protein levels have been reported to be altered in a molecular profiling study on serum samples of MDD patients (Stelzhammer et al., 2014) and to be associated with symptom severity in schizophrenia (Schwarz et al., 2012).”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe lncRNA class gene LOC100506023 originally associated by proximity with CpG cg11091478 was subsequently annotated as lnc-TNFSF4-3.
“The lncRNA class gene LOC100506023 originally associated by proximity with CpG cg11091478 was subsequently annotated as lnc-TNFSF4-3 (Volders et al., 2019).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Volders et al., 2019 source
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PremisecitationThe EED gene codes for a core component of the polycomb-repressive complex 2, which has been linked to neurodevelopmental abnormalities, intellectual disability, and neurodegeneration, and microglial EED has been suggested to play a pivotal role in normal synaptic and cognitive functions.
“The embryonic ectoderm development gene (EED) codes for a core component of the polycomb-repressive complex 2, which has been linked to neurodevelopmental abnormalities, intellectual disability, and neurodegeneration, and microglial EED has been suggested to play a pivotal role in normal synaptic and cognitive functions (Wang et al., 2022).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Wang et al., 2022 source
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Classified as probably not a substantial claim.
PremisecitationInitial treatment nonresponse rates in MDD are reported to be as high as 60%.
“initial treatment nonresponse rates in MDD are reported to be as high as 60% (Fava, 2003).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fava, 2003 source
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Study design and conductcitationOne suggestive CpG (cg04099436) was flagged for cross-reactivity and thus omitted from the results.
“One of the suggestive CpGs (cg04099436) was flagged for cross-reactivity (cf. Lehne et al., 2015; Pidsley et al., 2016) and thus omitted from the results.”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationR-Spondin 2 has been implied in the development of midbrain dopaminergic neurons and has been linked to fear extinction processes in the amygdala.
“R-Spondin 2 has been implied in the development of midbrain dopaminergic neurons (Gyllborg et al., 2018) and has been linked to fear extinction processes in the amygdala (McCullough et al., 2016).”
Quote in the paperNot a substantial claim0 of 2 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationThe TNFSF4 gene has been observed to be downregulated in MDD patients in a genome-wide gene expression analysis.
“This TNF Superfamily Member 4 (TNFSF4) gene has been observed to be downregulated in MDD patients in a genome-wide gene expression analysis (Woo et al., 2018).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Woo et al., 2018 source
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PremisecitationPRKCI has been implied in immunosuppression, and genetic variation in the PRKCI gene has been found to be associated with bipolar disorder and autism.
“The Protein Kinase C Iota has been implied in immunosuppression (Sarkar et al., 2017), and genetic variation in the PRKCI gene has been found to be associated with bipolar disorder (Iwamoto et al., 2011) and autism (Shen et al., 2011).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationPRDX6 has been linked to depressive and anxiety-like behavior in mice as well as to paroxetine, escitalopram, and sertraline administration in rats.
“PRDX6 has been linked to depressive (Gu et al., 2022) and anxiety-like (Pairojana et al., 2022) behavior in mice as well as to paroxetine (McHugh et al., 2010), escitalopram, and sertraline (Bisgaard et al., 2012) administration in rats.”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationInterleukin 16 has been shown to reduce neuronal excitability and synaptic activity.
“The pro-inflammatory cytokine interleukin 16 has been shown to reduce neuronal excitability and synaptic activity (Hridi et al., 2019).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Hridi et al., 2019 source
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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Study design and conductown dataThe genomic inflation factor lambda was 1.06 for the whole sample and 0.97 for the SSRI/SNRI subsample.
“Lambda was 1.06 for the whole sample and 0.97 for the SSRI/SNRI subsample.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductreasoningThe threshold for statistical significance was set at P < 5.77E-8, corresponding to a Bonferroni correction for the 865,859 evaluated CpG sites.
“The threshold for statistical significance was set at P < 5.77E-8, corresponding to a Bonferroni correction for the 865 859 evaluated CpG sites (0.05/865 859).”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductcitationAssociations at a significance level of P < 1E-5 were considered suggestive.
“Associations at a significance level of P < 1E-5 were considered suggestive (Lander and Kruglyak, 1995).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Lander and Kruglyak, 1995
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Interpretationown dataThe presently identified hits add to the available literature on potential biomarkers of MDD and its treatment response.
“While these presently identified hits add to the available literature on potential biomarkers of MDD and its treatment response”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenEpigenetic research into treatment response is still in its infancy and not yet ready for translation into clinical practice.
“While epigenetic research into treatment response is still in its infancy and not yet ready for translation into clinical practice”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
PremisecitationMAO inhibitors or valproic acid are known to affect DNA methylation.
“both of which are known to affect DNA methylation (for review see Boks et al., 2012).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Boks et al., 2012 source
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PremisecitationAltered methylation of the ZNF69 gene has been suggested to play a role in neurogenesis and brain development in Down syndrome.
“Altered methylation of the Zinc Finger Protein 69 (ZNF69) gene has been suggested to play a role in neurogenesis and brain development in Down syndrome (Laan et al., 2020).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Laan et al., 2020 source
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May combine two claims.
Study design and conductreasoningThe sample size is overall still moderate and may be underpowered to detect small effect sizes.
“the sample size is overall still moderate and may be underpowered to detect small effect sizes”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
PremisecitationA genetic polymorphism in the TIMP2 gene was found to be associated with depression, and increased TIMP-2 mRNA levels have been observed in patients with depression.
“A genetic polymorphism in the TIMP2 gene coding for the tissue metalloproteinase 2 modulating inflammation was found to be associated with depression (Bobińska et al., 2016b), and increased TIMP-2 mRNA levels have been observed in patients with depression (Bobińska et al., 2016a).”
Quote in the paperNot a substantial claim0 of 2 sources checked- cites Bobińska et al., 2016b
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- cites Bobińska et al., 2016a
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PremisereasoningPrevious EWAS sample sizes were very small and differed in sample composition and statistical approaches, limiting comparability.
“However, previous sample sizes were very small and differed both in sample composition (e.g., age, ethnicity) and statistical approaches, thus limiting comparability.”
Quote in the paperSubstantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningDrug effects themselves may represent a confounding variable.
“Along those lines, drug effects themselves may represent a confounding variable.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Study design and conductnone givenEpigenome-wide DNA methylation was determined in peripheral blood samples.
“Epigenome-wide DNA methylation was determined in peripheral blood samples”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationVDAC1 has been shown to be downregulated in rats resilient to chronic social isolation stress.
“The Voltage Dependent Anion Channel 1 (VDAC1) has been shown to be downregulated in rats resilient to chronic social isolation stress (Perić et al., 2021)”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites Perić et al., 2021 source
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Study design and conductnone givenInformation on smoking was not available for the present sample.
“information on smoking was not available for the present sample.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductnone givenDrug initiation or discontinuation during the observation period was allowed.
“Additionally, drug initiation or discontinuation during the observation period was allowed”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningDosages were not held constant over the course of treatment.
“dosages were not held constant over the course of treatment”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
Study design and conductreasoningVarying drug classes of differing dosage were used in the present study.
“given the naturalistic study design, varying drug classes of differing dosage were used”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
PremisecitationSmoking status has been reported to affect global DNA methylation levels.
“While smoking status has been reported to affect global DNA methylation levels (Gao et al., 2015)”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Gao et al., 2015 source
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Study design and conductnone givenCo-medication with other pharmacological agents was permitted, with the exception of MAO inhibitors or valproic acid.
“co-medication with other pharmacological agents (e.g., mood stabilizers, antipsychotics) was permitted, with the exception of MAO inhibitors or valproic acid”
Quote in the paperNot a substantial claim
The paper relies on this without support.
MIR9-3HG, LOC341056, and B3GALNT2 have not been reported to be related to a mental disorder phenotype before.
“The MIR9-3 Host Gene (MIR9-3HG), the lncRNA class-associated LOC341056 gene, and the Beta-1,3-N-Acetylgalactosaminyltransferase 2 (B3GALNT2) have not been reported to be related to a mental disorder phenotype before.”
The paper relies on this without support.
The present sample is the largest sample investigated for this research question.
“While the present size constitutes the largest sample investigated in this regard”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Large-scale epigenome-wide association studies have identified specific CpG loci, such as RSPO2, IL16, and PRKCI, that correlate with treatment outcomes following SSRI or SNRI therapy.
“large-scale epigenome-wide association studies have identified specific CpG loci, such as RSPO2, IL16, and PRKCI, that correlate with treatment outcomes following SSRI or SNRI therapy”
From Histone modifications and depression: epigenetic mechanisms, therapeutic targets, and translational outlook (2026) · cites this paper as Schiele et al., 2024
The Results identify CpG sites mapping to RSPO2, IL16, and PRKCI as suggestively associated with response in the overall, naturalistically treated MDD sample. They report a separate SSRI/SNRI subgroup analysis with different example genes. No genome-wide significant hits were observed, so the claim overstates both the treatment specificity and the strength of the findings. (LLM, conf=0.90)
Experimental — accuracy not yet measured
Cites
Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results
Lander, E. S., & Kruglyak, L. (1995) · Nature Genetics · doi:10.1038/ng1195-241 · Cited by 5,196 · see citing works
DNA methylation arrays as surrogate measures of cell mixture distribution
Houseman, E. A., Accomando, W. P., Koestler, D. C., Christensen, B. C., Marsit, C. J., Nelson, H. H., Wiencke, J. K., & Kelsey, K. T. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-86 · Cited by 3,175 · see citing works
Genomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162 · see citing works
Pidsley, R., Zotenko, E., Peters, T. J., Lawrence, M. G., Risbridger, G. P., Molloy, P., Van Djik, S., Muhlhausler, B., Stirzaker, C., & Clark, S. J. (2016) · Genome biology · doi:10.1186/s13059-016-1066-1 · Cited by 1,480 · see citing works
Diagnosis and definition of treatment-resistant depression
Fava, M. (2003) · Biological Psychiatry · doi:10.1016/s0006-3223(03)00231-2 · Cited by 1,380 · see citing works
Frankish, A., Diekhans, M., Jungreis, I., Lagarde, J., Loveland, J. E., Mudge, J. M., Sisu, C., Wright, J. C., Armstrong, J., Barnes, I., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa1087 · Cited by 1,334 · see citing works
Preprocessing, normalization and integration of the Illumina HumanMethylationEPIC array with minfi
Fortin, J.-P., Triche, T. J., & Hansen, K. D. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw691 · Cited by 867 · see citing works
Tobacco smoking leads to extensive genome-wide changes in DNA methylation
Zeilinger, S., Kühnel, B., Klopp, N., Baurecht, H., Kleinschmidt, A., Gieger, C., Weidinger, S., Lattka, E., Adamski, J., Peters, A., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0063812 · Cited by 824 · see citing works
LNCipedia 5: towards a reference set of human long non-coding RNAs
Volders, P.-J., Anckaert, J., Verheggen, K., Nuytens, J., Martens, L., Mestdagh, P., & Vandesompele, J. (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1031 · Cited by 547 · see citing works
Braun, P. R., Han, S., Hing, B., Nagahama, Y., Gaul, L. N., Heinzman, J. T., Grossbach, A. J., Close, L., Dlouhy, B. J., Howard, M. A., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0376-y · Cited by 467 · see citing works
Hannon, E., Lunnon, K., Schalkwyk, L., & Mill, J. (2015) · Epigenetics · doi:10.1080/15592294.2015.1100786 · Cited by 455 · see citing works
Candidate biomarkers in psychiatric disorders: state of the field
Abi‐Dargham, A., Moeller, S. J., Ali, F., DeLorenzo, C., Domschke, K., Horga, G., Jutla, A., Kotov, R., Paulus, M. P., Rubio, J. M., et al. (2023) · World Psychiatry · doi:10.1002/wps.21078 · Cited by 390 · see citing works
Self-citationGao, X., Jia, M., Zhang, Y., Breitling, L. P., & Brenner, H. (2015) · Clinical Epigenetics · doi:10.1186/s13148-015-0148-3 · Cited by 386 · see citing works
Lehne, B., Drong, A. W., Loh, M., Zhang, W., Scott, W. R., Tan, S.-T., Afzal, U., Scott, J., Jarvelin, M.-R., Elliott, P., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0600-x · Cited by 380 · see citing works
Epigenetic basis of mental illness
Nestler, E. J., Peña, C. J., Kundakovic, M., Mitchell, A., & Akbarian, S. (2016) · The Neuroscientist · doi:10.1177/1073858415608147 · Cited by 342 · see citing works
Liu, H., Heath, S. C., Sobin, C., Roos, J. L., Galke, B. L., Blundell, M. L., Lenane, M., Robertson, B., Wijsman, E. M., Rapoport, J. L., et al. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.042700699 · Cited by 323 · see citing works
Lehne, B. C., Drong, A., Loh, M. C. S., Zhang, W., Scott, W. R., Tan, S.-T., Afzal, U., Schulz, R., Scott, J., Järvelin, M., et al. (2016) · Genome biology · doi:10.1186/s13059-016-0934-z · Cited by 284 · see citing works
Epigenetic Mechanisms of Depression and Antidepressant Action
Vialou, V., Feng, J., Robison, A. J., & Nestler, E. J. (2013) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-010611-134540 · Cited by 277 · see citing works
Moore, R. C., Depp, C. A., Wetherell, J. L., & Lenze, E. J. (2016) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2016.01.011 · Cited by 274 · see citing works
BECon: a tool for interpreting DNA methylation findings from blood in the context of brain
Edgar, R. D., Jones, M. J., Meaney, M. J., Turecki, G., & Kobor, M. S. (2017) · Translational Psychiatry · doi:10.1038/tp.2017.171 · Cited by 261 · see citing works
Serotonin transporter gene hypomethylation predicts impaired antidepressant treatment response
Domschke, K., Tidow, N., Schwarte, K., Deckert, J., Lesch, K., Arolt, V., Zwanzger, P., & Baune, B. T. (2014) · The International Journal of Neuropsychopharmacology · doi:10.1017/s146114571400039x · Cited by 179 · see citing works
Self-citationEpigenetic alterations in depression and antidepressant treatment
Menke, A., & Binder, E. B. (2014) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2014.16.3/amenke · Cited by 161 · see citing works
Schiele, M. A., Gottschalk, M. G., & Domschke, K. (2020) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101830 · Cited by 156 · see citing works
Self-citationA review of DNA methylation in depression
Chen, D., Meng, L., Pei, F., Zheng, Y., & Leng, J. (2017) · Journal of Clinical Neuroscience · doi:10.1016/j.jocn.2017.05.022 · Cited by 154 · see citing works
Verduijn, J., Verhoeven, J. E., Milaneschi, Y., Schoevers, R. A., van Hemert, A. M., Beekman, A. T. F., & Penninx, B. W. J. H. (2017) · BMC Medicine · doi:10.1186/s12916-017-0972-8 · Cited by 122 · see citing works
Blood biomarkers and treatment response in major depression
Mora, C., Zonca, V., Riva, M. A., & Cattaneo, A. (2018) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2018.1470927 · Cited by 107 · see citing works
Proteomic changes in serum of first onset, antidepressant drug-naïve major depression patients
Stelzhammer, V., Haenisch, F., Chan, M. K., Cooper, J. D., Steiner, J., Steeb, H., Martins-de-Souza, D., Rahmoune, H., Guest, P. C., & Bahn, S. (2014) · The International Journal of Neuropsychopharmacology · doi:10.1017/s1461145714000819 · Cited by 105 · see citing works
PRKCI promotes immune suppression in ovarian cancer
Sarkar, S., Bristow, C. A., Dey, P., Rai, K., Perets, R., Ramirez-Cardenas, A., Malasi, S., Huang-Hobbs, E., Haemmerle, M., Wu, S. Y., et al. (2017) · Genes & Development · doi:10.1101/gad.296640.117 · Cited by 93 · see citing works
Schwarz, E., Guest, P. C., Steiner, J., Bogerts, B., & Bahn, S. (2012) · Translational Psychiatry · doi:10.1038/tp.2012.3 · Cited by 91 · see citing works
Current status and future prospects for epigenetic psychopharmacology
Boks, M. P., de Jong, N. M., Kas, M. J. H., Vinkers, C. H., Fernandes, C., Kahn, R. S., Mill, J., & Ophoff, R. A. (2012) · Epigenetics · doi:10.4161/epi.7.1.18688 · Cited by 89 · see citing works
The Relationship between DNA Methylation and Antidepressant Medications: A Systematic Review
Webb, L. M., Phillips, K. E., Ho, M. C., Veldic, M., & Blacker, C. J. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21030826 · Cited by 84 · see citing works
Epigenetics, Depression and Antidepressant Treatment
Menke, A., Klengel, T., & Binder, E. B. (2012) · Current Pharmaceutical Design · doi:10.2174/138161212803523590 · Cited by 78 · see citing works
Schuebel, K., Gitik, M., Domschke, K., & Goldman, D. (2016) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyw058 · Cited by 75 · see citing works
Self-citationGenome-wide association studies of antidepressant class response and treatment-resistant depression
Li, Q. S., Tian, C., Hinds, D. A., Agee, M., Alipanahi, B., Auton, A., Bell, R. K., Bryc, K., Elson, S. L., Fontanillas, P., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-01035-6 · Cited by 70 · see citing works
Fabbri, C., Kasper, S., Kautzky, A., Bartova, L., Dold, M., Zohar, J., Souery, D., Montgomery, S., Albani, D., Raimondi, I., et al. (2019) · British Journal of Psychiatry · doi:10.1192/bjp.2018.256 · Cited by 61 · see citing works
Ju, C., Fiori, L. M., Belzeaux-R, R., Théroux, J., Chen, G. G., Aouabed, Z., Blier, P., Farzan, F., Frey, B. N., Giacobbe, P., et al. (2018) · Translational Psychiatry · doi:10.1038/s41398-019-0589-0 · Cited by 56 · see citing works
Role of MMP-2, MMP-7, MMP-9 and TIMP-2 in the development of recurrent depressive disorder
Bobińska, K., Szemraj, J., Czarny, P. L., & Gałecki, P. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.03.068 · Cited by 53 · see citing works
Pharmacoepigenetics of depression: no major influence of MAO-A DNA methylation on treatment response
Domschke, K., Tidow, N., Schwarte, K., Ziegler, C., Lesch, K., Deckert, J., Arolt, V., Zwanzger, P., & Baune, B. T. (2014) · Journal of Neural Transmission · doi:10.1007/s00702-014-1227-x · Cited by 52 · see citing works
Self-citationMcCullough, K. M., Choi, D., Guo, J., Zimmerman, K., Walton, J., Rainnie, D. G., & Ressler, K. J. (2016) · Nature Communications · doi:10.1038/ncomms13149 · Cited by 51 · see citing works
Schiele, M. A., Zwanzger, P., Schwarte, K., Arolt, V., Baune, B. T., & Domschke, K. (2020) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyaa081 · Cited by 50 · see citing works
Self-citationThe DNA methylome in panic disorder: A case-control and longitudinal psychotherapy-epigenetic study
Ziegler, C., Grundner-Culemann, F., Schiele, M. A., Schlosser, P., Kollert, L., Mahr, M., Gajewska, A., Lesch, K.-P., Deckert, J., Köttgen, A., et al. (2019) · Translational Psychiatry · doi:10.1038/s41398-019-0648-6 · Cited by 47 · see citing works
Barbu, M. C., Huider, F., Campbell, A., Amador, C., Adams, M. J., Lynall, M.-E., Howard, D. M., Walker, R. M., Morris, S. W., Van Dongen, J., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-021-01412-7 · Cited by 43 · see citing works
Woo, H. I., Lim, S.-W., Myung, W., Kim, D. K., & Lee, S.-Y. (2018) · Experimental & Molecular Medicine · doi:10.1038/s12276-018-0123-0 · Cited by 42 · see citing works
Expression and Activity of Metalloproteinases in Depression
Bobińska, K., Szemraj, J., Czarny, P. L., & Gałecki, P. (2016) · Medical Science Monitor · doi:10.12659/msm.895978 · Cited by 39 · see citing works
Laan, L., Klar, J., Sobol, M., Hoeber, J., Shahsavani, M., Kele, M., Fatima, A., Zakaria, M., Annerén, G., Falk, A., et al. (2020) · Clinical Epigenetics · doi:10.1186/s13148-019-0803-1 · Cited by 33 · see citing works
Methylome-wide change associated with response to electroconvulsive therapy in depressed patients
Sirignano, L., Frank, J., Kranaster, L., Witt, S. H., Streit, F., Zillich, L., Sartorius, A., Rietschel, M., & Foo, J. C. (2021) · Translational Psychiatry · doi:10.1038/s41398-021-01474-9 · Cited by 32 · see citing works
Loss of microglial EED impairs synapse density, learning, and memory
Wang, Y.-Y., Deng, Y.-S., Dai, S.-K., Mi, T.-W., Li, R.-Y., Liu, P.-P., Liu, C., He, B.-D., He, X.-C., Du, H.-Z., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01576-w · Cited by 32 · see citing works
Epigenome-wide DNA methylation in obsessive-compulsive disorder
Schiele, M. A., Lipovsek, J., Schlosser, P., Soutschek, M., Schratt, G. M., Zaudig, M., Berberich, G., Köttgen, A., & Domschke, K. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01996-w · Cited by 31 · see citing works
Self-citationChakraborty, D., Bernal, A. J., Schoch, K., Howard, T. D., Ip, E. H., Hooper, S. R., Keshavan, M. S., Jirtle, R. L., & Shashi, V (2012) · Translational Psychiatry · doi:10.1038/tp.2012.31 · Cited by 30 · see citing works
Engelmann, J., Zillich, L., Frank, J., Wagner, S., Cetin, M., Herzog, D. P., Müller, M. B., Tadic, A., Foo, J. C., Sirignano, L., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02032-7 · Cited by 29 · see citing works
Genome-wide copy-number variation study of psychosis in Alzheimer’s disease
Zheng, X., Demirci, F. Y., Barmada, M. M., Richardson, G. A., López, O. L., Sweet, R. A., Kamboh, M. I., & Feingold, E. (2015) · Translational Psychiatry · doi:10.1038/tp.2015.64 · Cited by 28 · see citing works
Gyllborg, D., Ahmed, M., Toledo, E. M., Theofilopoulos, S., Yang, S., ffrench-Constant, C., & Arenas, E. (2018) · Stem Cell Reports · doi:10.1016/j.stemcr.2018.07.014 · Cited by 28 · see citing works
Bisgaard, C. F., Bak, S. Y., Christensen, T. T., Jensen, O. N., Enghild, J. J., & Wiborg, O. (2012) · Journal of Psychopharmacology · doi:10.1177/0269881112460110 · Cited by 27 · see citing works
Changes of TSPO-mediated mitophagy signaling pathway in learned helplessness mice
Li, D., Zheng, J., Wang, M., Feng, L., Ren, Z., Liu, Y., Yang, N., & Zuo, P. (2016) · Psychiatry Research · doi:10.1016/j.psychres.2016.02.068 · Cited by 27 · see citing works
Therapeutic response to paroxetine in major depressive disorder predicted by DNA Methylation
Takeuchi, N., Nonen, S., Kato, M., Wakeno, M., Takekita, Y., Kinoshita, T., & Kugawa, F. (2017) · Neuropsychobiology · doi:10.1159/000480512 · Cited by 26 · see citing works
Proteomic analysis of rat hippocampus exposed to the antidepressant paroxetine
McHugh, P., Rogers, G., Glubb, D., Joyce, P., & Kennedy, M. (2010) · Journal of Psychopharmacology · doi:10.1177/0269881109102786 · Cited by 25 · see citing works
Translating depression biomarkers for improved targeted therapies
Bredt, D. S., Furey, M. L., Chen, G., Lovenberg, T., Drevets, W. C., & Manji, H. K. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.09.013 · Cited by 20 · see citing works
Hridi, S. U., Franssen, A. J. P. M., Jiang, H.-R., & Bushell, T. J. (2019) · Molecular and Cellular Neuroscience · doi:10.1016/j.mcn.2019.01.002 · Cited by 20 · see citing works
S-antigen in non ocular tissues
Faure, J.-P., & Mirshahi, M. (1990) · Current Eye Research · doi:10.3109/02713689008999437 · Cited by 18 · see citing works
Shen, C., Zhao, X.-L., Ju, W., Zou, X.-B., Huo, L.-R., Yan, W., Zou, J.-H., Yan, G.-D., Jenkins, E. C., Brown, W. T., et al. (2011) · Journal of Molecular Neuroscience · doi:10.1007/s12031-010-9463-5 · Cited by 18 · see citing works
Perić, I., Costina, V., Gass, P., Findeisen, P., & Filipović, D. (2021) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2020.11.013 · Cited by 18 · see citing works
Iwamoto, K., Ueda, J., Bundo, M., Kojima, T., & Kato, T. (2011) · Neuroscience Research · doi:10.1016/j.neures.2011.02.012 · Cited by 14 · see citing works
DNA Methylation of Fluoxetine Response in Child and Adolescence: Preliminary Results
Martínez-Pinteño, A., Rodríguez, N., Blázquez, A., Plana, M. T., Varela, E., Gassó, P., Lafuente, A., Lázaro, L., & Mas, S. (2021) · Pharmacogenomics and Personalized Medicine · doi:10.2147/pgpm.s289480 · Cited by 12 · see citing works
GABAB receptor subunit 1 binds to proteins affected in 22q11 deletion syndrome
Zunner, D., Deschermeier, C., & Kornau, H.-C. (2010) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2009.12.120 · Cited by 11 · see citing works
Gu, S. M., Yu, E., Kim, Y., Yoon, S. S., Lee, D., Hong, J. T., & Yun, J. (2022) · Biomolecules & Therapeutics · doi:10.4062/biomolther.2021.169 · Cited by 8 · see citing works
S antigen specific effector T cell activation detected by cytokine flow cytometry
Morgan, J. P. (2002) · British Journal of Ophthalmology · doi:10.1136/bjo.86.5.517 · Cited by 6 · see citing works
Exploring the sortilin related receptor, SorLA, in depression
Buttenschøn, H. N., Elfving, B., Nielsen, M., Skeldal, S., Ollendorff, M. K., Mors, O. N., & Glerup, S. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2018.02.050 · Cited by 5 · see citing works
Behavioral and synaptic phenotypes of female Prdx6(-/-) Mice
Pairojana, T., Phasuk, S., Suresh, P., & Liu, I. Y. (2022) · Antioxidants · doi:10.3390/antiox11061201 · Cited by 5 · see citing works
Flagged first, then by citations
Research works printed but not linked: 1
- GBD Mental Disorders Collaborators, 2019, (, Lancet Psychiatry, 9, 137
Cited by
Sorted by citations
Lv, L.-Z., Wang, Z.-D., Ren, J.-J., Li, L.-H., Liu, X.-B., Li, J.-L., Zhu, H., Jiang, B., Han, Y.-P., Zhou, X.-M., et al. (2026) · Frontiers in Genetics · doi:10.3389/fgene.2025.1722453 · Cited by 7 · see citing works
- Authors
- Schiele, M. A., Crespo Salvador, O., Lipovsek, J., Schwarte, K., Schlosser, P., Zwanzger, P., Arolt, V., Baune, B. T., Köttgen, A., & Domschke, K.
- Affiliations
- University of Freiburg (DE)
- Department of Psychiatry and Psychotherapy, Medical Center – University of Freiburg, Faculty of Medicine, University of Freiburg , Freiburg ,
- University of Münster (DE)
- Johns Hopkins University (US)
- Inn-Salzach-Klinikum (DE)
- The University of Melbourne (AU)
- Corresponding author
- Domschke, Katharina
- Venue
- International Journal of Neuropsychopharmacology
- Publisher
- Oxford University Press (OUP)
- Published
- 2024-10-05
- Volume
- 27
- Issue
- 11
- ISSN
- 1461-1457 (ISSN-L)
- 1469-5111
- PMC
- PMC11558245
- OpenAlex
- W4403154823
- Cited by
- 13
- References
- 69
- Citations by year
- 2026: 8 · 2025: 5
- FWCI
- 3.69
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- The International Journal of Neuropsychopharmacology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UWA Profiles and Research Repository (UWA) (submittedVersion, cc-by)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Funders
- Dr. Robert Pfleger Stiftung
- German Research Foundation (530592017, SCHL 2292/3–1)
- Germany’s Excellence Strategy (390939984)
- Medical Epigenetics (192904750—CRC 992)
- Topics
- Health Sciences › Medicine › Pharmacology › Treatment of Major Depression
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- DNA methylation, major depressive disorder, antidepressant response, predictive biomarkers, epigenetics, serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, CpG sites, personalized treatment, peripheral blood
- MeSH terms
- Epigenome, Adult, Antidepressive Agents, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, Male, Middle Aged, Biomarkers, Treatment Outcome, Selective Serotonin Reuptake Inhibitors, CpG Islands, DNA Methylation, Epigenesis, Genetic
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-10.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-10.
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