Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
  1. Home
  2. Search

Refine search

Refine search

Access:
Content type:
Publication date:
Apply   From and To filters
Subject: Show more
Journals Show more
Publishers: Show more
Societies Show more
Series: Show more
Collections: Show more

Actions for selected content:

Select all | Deselect all
  • View selected items
  • Export citations
  • Download PDF (zip)
  • Save to Kindle
  • Save to Dropbox
  • Save to Google Drive

Save Search

You can save your searches here and later view and run them again in "My saved searches".

Please provide a title, maximum of 40 characters.
Cancel
×

5 results

  • Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report)

  • Iryna O. Fedko, Jouke-Jan Hottenga, Quinta Helmer, Hamdi Mbarek, Floris Huider, Najaf Amin, Joline W. Beulens, Marijke A. Bremmer, Petra J. Elders, Tessel E. Galesloot, Lambertus A. Kiemeney, Hanna M. van Loo, H. Susan J. Picavet, Femke Rutters, Ashley van der Spek, Anne M. van de Wiel, Cornelia van Duijn, Eco J. C. de Geus, Edith J. M. Feskens, Catharina A. Hartman, Albertine J. Oldehinkel, Jan H. Smit, W. M. Monique Verschuren, Brenda W. J. H. Penninx, Dorret I. Boomsma, Mariska Bot
  • Journal:
    Psychological Medicine / Volume 51 / Issue 8 / June 2021
    Published online by Cambridge University Press:
    27 February 2020, pp. 1345-1354
    Print publication:
    June 2021
    • Article
      • You have access
      • Open access
    • PDF
    • HTML
    • Export citation
  • Background

    Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression.

    Methods

    Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS).

    Results

    Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15–1.32, R2 = 1.47%).

    Conclusions

    By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.

  • 19 - Prion diseases

  • from Part II - Neurological diseases
  • Albert Hofman, Erasmus Universiteit Rotterdam, Richard Mayeux, Columbia University, New York
  • Book:
    Investigating Neurological Disease
    Published online:
    29 September 2009
    Print publication:
    30 August 2001, pp 259-269

  • Summary

    This chapter discusses the etiology, diagnosis, occurrence, and prognosis of human prion disorders. It emphasizes on the Creutzfeldt-Jakob disease (CJD), the most common and complex prion disorder in humans. Prion diseases may be transmitted from man to man. The classical example is kuru, in which the disease has been transmitted through cannibalistic rituals. New developments may be anticipated with regard to the use of magnetic resonance imaging (MRI) in the diagnosis of CJD. For all prion disorders, DNA diagnostics may be used to support the diagnosis. Several dominant mutations in the prion protein (PRNP) gene are known to lead to CJD. The most common prion disease, CJD, is reported worldwide with a mortality of around one death per million persons. Within months after diagnosis of CJD, there is a progressive deterioration of the clinical condition to akinetic mutism.

  • 3 - Gene–environment interaction in neurologic disorders

  • from Part I - Quantitative methods in clinical neurology
  • Albert Hofman, Erasmus Universiteit Rotterdam, Richard Mayeux, Columbia University, New York
  • Book:
    Investigating Neurological Disease
    Published online:
    29 September 2009
    Print publication:
    30 August 2001, pp 21-25

  • Summary

    This chapter discusses the basic concept of gene environment interaction including the definition and principal mechanisms. It describes the evidence for gene-environment interaction. From the perspective of a neurogenetic disorder, gene-environment interaction implies that the risk of disease associated with mutations or common genetic variations (that is, polymorphisms) in genes is altered by a nongenetic risk factor. Modifiable age-dependent environmental factors are likely to influence the risk and onset of disease. Genetic factors play an important role in the etiology of various neurodegenerative disorders such as Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS) and Parkinson's disease. It is becoming increasingly clear that a great number of common neurodegenerative disorders result from an interplay of genetic and environmental risk factors. The clinical and public health implications of genetic factors in terms of disease prevention and care are not straightforward if risks associated with these genetic factors are not properly quantified.