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Menopausal hormone therapy and the female brain: Leveraging neuroimaging and prescription registry data from the UK Biobank cohort.

Claudia Barth | Liisa A M Galea | Emily G Jacobs | Bonnie H Lee | Lars T Westlye | Ann-Marie G de Lange
eLife | 2025

Menopausal hormone therapy (MHT) is generally thought to be neuroprotective, yet results have been inconsistent. Here, we present a comprehensive study of MHT use and brain characteristics in females from the UK Biobank.

Pubmed ID: 40439116

Research resources used in this publication

None found

Additional research tools detected in this publication

Antibodies used in this publication

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Associated grants

  • Agency: European Research Council, International
    Id: 10.3030/802998
  • Agency: Norges Forskningsråd,
    Id: 298646
  • Agency: NIH HHS, United States
    Id: AG063843
  • Agency: CIHR, Canada
    Id: PJT-173554
  • Agency: Norges Forskningsråd,
    Id: 249795
  • Agency: Norges Forskningsråd,
    Id: 223273
  • Agency: NIA NIH HHS, United States
    Id: R01 AG063843
  • Agency: Helse Sør-Øst RHF,
    Id: 2018076
  • Agency: Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung,
    Id: PZ00P3_193658
  • Agency: Norges Forskningsråd,
    Id: 300768
  • Agency: Helse Sør-Øst RHF,
    Id: 2022103
  • Agency: Helse Sør-Øst RHF,
    Id: 2023037
  • Agency: Helse Sør-Øst RHF,
    Id: 2019101
  • Agency: Norges Forskningsråd,
    Id: 273345

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This is a list of tools and resources that we have found mentioned in this publication.


scikit-learn (tool)

RRID:SCR_002577

scikit-learn: machine learning in Python

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UK Biobank (tool)

RRID:SCR_012815

Biobank provides data collected at Assessment Center and via online questionnaires on participants aged 40-69 years recruited throughout United Kingdom and provides summary information to improve prevention, diagnosis and treatment of serious and life threatening illnesses.

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XGBoost (tool)

RRID:SCR_021361

Open source software tool as library for implementation of gradient boosting with various machine learning algorithms.Optimized distributed gradient boosting library designed to be highly efficient, flexible and portable.Supports regression, classification, ranking and user defined objectives.

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