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. 2020 Feb 27;51(8):1-10.
doi: 10.1017/S0033291720000100. Online ahead of print.

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

Iryna O Fedko  1 , Jouke-Jan Hottenga  1 , Quinta Helmer  1 , Hamdi Mbarek  1 , Floris Huider  1 , Najaf Amin  2 , Joline W Beulens  3   4   5 , Marijke A Bremmer  6 , Petra J Elders  4   7 , Tessel E Galesloot  8 , Lambertus A Kiemeney  8 , Hanna M van Loo  9 , H Susan J Picavet  10 , Femke Rutters  3   4 , Ashley van der Spek  2 , Anne M van de Wiel  11 , Cornelia van Duijn  2 , Eco J C de Geus  1   12 , Edith J M Feskens  11 , Catharina A Hartman  13 , Albertine J Oldehinkel  13 , Jan H Smit  14 , W M Monique Verschuren  5   10 , Brenda W J H Penninx  12   14 , Dorret I Boomsma  1   12 , Mariska Bot  12   14
Affiliations

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

Iryna O Fedko et al. Psychol Med. .

Abstract

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.

Keywords: LIDAS; Lifetime Depression Assessment Self-report; major depressive disorder; online assessment tool; prevalence.

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Conflict of interest statement

Brenda W.J.H. Penninx: received research funding (not related to the BIONIC project) from Janssen Research and Boehringer Ingelheim.

Figures

Fig. 1.
Fig. 1.
Pooled estimates of (a) current MDD and (b) lifetime MDD prevalence as measured with LIDAS.
Fig. 2.
Fig. 2.
Pooled estimates of current (a) and (b) lifetime MDD prevalence as measured with LIDAS per subgroup (sex, age, education, smoking, physical activity, and obesity). Q, Cochran's Q; df, degrees of freedom; p, p value from the subgroup analysis of (a) current and (b) lifetime MDD; y.o., years old; t.p.w., times per week.
Fig. 3.
Fig. 3.
Proportion of lifetime MDD cases in NTR plotted against deciles of PRS profiles distribution. For each group of individuals falling into ith decile of PRS distribution, the proportion of cases was calculated. This plot shows the relationship between the increasing value of PRS profile and the increased number of MDD cases. The line plotted through the points is a linear regression line with shaded area around it depicting the 95% confidence interval.
See this image and copyright information in PMC

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