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Record W3131673246 · doi:10.1038/s41398-021-01248-3

Genome-wide analysis suggests the importance of vascular processes and neuroinflammation in late-life antidepressant response

2021· article· en· W3131673246 on OpenAlexaff
Victoria Marshe, Małgorzata Maciukiewicz, Anne-Christin Hauschild, Farhana Islam, Qin Li, Arun K. Tiwari, Etienne Sibille, Daniel M. Blumberger, Jordan F. Karp, Alastair J. Flint, Gustavo Turecki, Raymond W. Lam, Roumen Milev, Benício N. Frey, Susan Rotzinger, Jane A. Foster, Sidney H. Kennedy, James L. Kennedy, Benoit H. Mulsant, Charles F. Reynolds, Eric J. Lenze, Daniel J. Müller

Bibliographic record

VenueTranslational Psychiatry · 2021
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsSt. Michael's HospitalMcMaster UniversityQueen's UniversitySt. Joseph’s Healthcare HamiltonUniversity of British ColumbiaMcGill UniversityDouglas Mental Health University InstituteUniversity Health NetworkUniversity of TorontoVancouver Coastal HealthCentre for Addiction and Mental Health
Fundersnot available
KeywordsNeuroinflammationAntidepressantSchizophrenia (object-oriented programming)PsychologyNeurosciencePsychiatryMedicineInternal medicineHippocampusInflammation

Abstract

fetched live from OpenAlex

Abstract Antidepressant outcomes in older adults with depression is poor, possibly because of comorbidities such as cerebrovascular disease. Therefore, we leveraged multiple genome-wide approaches to understand the genetic architecture of antidepressant response. Our sample included 307 older adults (≥60 years) with current major depression, treated with venlafaxine extended-release for 12 weeks. A standard genome-wide association study (GWAS) was conducted for post-treatment remission status, followed by in silico biological characterization of associated genes, as well as polygenic risk scoring for depression, neurodegenerative and cerebrovascular disease. The top-associated variants for remission status and percentage symptom improvement were PIEZO1 rs12597726 ( OR = 0.33 [0.21, 0.51], p = 1.42 × 10 −6 ) and intergenic rs6916777 ( Beta = 14.03 [8.47, 19.59], p = 1.25 × 10 −6 ), respectively. Pathway analysis revealed significant contributions from genes involved in the ubiquitin-proteasome system, which regulates intracellular protein degradation with has implications for inflammation, as well as atherosclerotic cardiovascular disease ( n = 25 of 190 genes, p = 8.03 × 10 −6 , FDR-corrected p = 0.01). Given the polygenicity of complex outcomes such as antidepressant response, we also explored 11 polygenic risk scores associated with risk for Alzheimer’s disease and stroke. Of the 11 scores, risk for cardioembolic stroke was the second-best predictor of non-remission, after being male (Accuracy = 0.70 [0.59, 0.79], Sensitivity = 0.72, Specificity = 0.67; p = 2.45 × 10 −4 ). Although our findings did not reach genome-wide significance, they point to previously-implicated mechanisms and provide support for the roles of vascular and inflammatory pathways in LLD. Overall, significant enrichment of genes involved in protein degradation pathways that may be impaired, as well as the predictive capacity of risk for cardioembolic stroke, support a link between late-life depression remission and risk for vascular dysfunction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.360

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.256
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations44
Published2021
Admission routes1
Has abstractyes

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