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Clinical associations with treatment resistance in depression: An electronic health record study.
Coombes, Brandon J; Sanchez-Ruiz, Jorge A; Fennessy, Brian; Pazdernik, Vanessa K; Adekkanattu, Prakash; Nuñez, Nicolas A; Lepow, Lauren; Melhuish Beaupre, Lindsay M; Ryu, Euijung; Talati, Ardesheer; Mann, J John; Weissman, Myrna M; Olfson, Mark; Pathak, Jyotishman; Charney, Alexander W; Biernacka, Joanna M.
Afiliação
  • Coombes BJ; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA. Electronic address: coombes.brandon@mayo.edu.
  • Sanchez-Ruiz JA; Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
  • Fennessy B; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Pazdernik VK; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
  • Adekkanattu P; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA; Clinical and Translational Science Center, Weill Cornell Medicine, New York, NY, USA.
  • Nuñez NA; Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA.
  • Lepow L; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Melhuish Beaupre LM; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
  • Ryu E; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA.
  • Talati A; Department of Psychiatry, Vagelos College of Physicians and Surgeons Columbia University & NY State Psychiatric Institute, New York, NY, USA.
  • Mann JJ; Department of Psychiatry, Vagelos College of Physicians and Surgeons Columbia University & NY State Psychiatric Institute, New York, NY, USA.
  • Weissman MM; Department of Psychiatry, Vagelos College of Physicians and Surgeons Columbia University & NY State Psychiatric Institute, New York, NY, USA.
  • Olfson M; Department of Psychiatry, Vagelos College of Physicians and Surgeons Columbia University & NY State Psychiatric Institute, New York, NY, USA.
  • Pathak J; Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA; Department of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
  • Charney AW; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Mount Sinai Clinical Intelligence Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Biernacka JM; Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA; Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA. Electronic address: biernacka.joanna@mayo.edu.
Psychiatry Res ; 342: 116203, 2024 Sep 16.
Article em En | MEDLINE | ID: mdl-39321638
ABSTRACT
Treatment resistance is common in major depressive disorder (MDD), yet clinical risk factors are not well understood. Using a discovery-replication design, we conducted phenome-wide association studies (PheWASs) of MDD treatment resistance in two electronic health record (EHR)-linked biobanks. The PheWAS included participants with an MDD diagnosis in the EHR and at least one antidepressant (AD) prescription. Participant lifetime diagnoses were mapped to phecodes. PheWASs were conducted for three treatment resistance outcomes based on AD prescription data number of unique ADs prescribed, ≥1 and ≥2 CE switches. Of the 180 phecodes significantly associated with these outcomes in the discovery cohort (n = 12,558), 71 replicated (n = 8,206). In addition to identifying known clinical factors for treatment resistance in MDD, the total unique AD prescriptions was associated with additional clinical variables including irritable bowel syndrome, gastroesophageal reflux disease, symptomatic menopause, and spondylosis. We calculated polygenic risk of specific-associated conditions and tested their association with AD outcomes revealing that genetic risk for many of these conditions is also associated with the total unique AD prescriptions. The number of unique ADs prescribed, which is easily assessed in EHRs, provides a more nuanced measure of treatment resistance, and may facilitate future research and clinical application in this area.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Psychiatry Res Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: Psychiatry Res Ano de publicação: 2024 Tipo de documento: Article