Evidence map›Paper›PMID 30002671›Full record

ArticleFrontiers in genetics2018

Sample Size for Successful Genome-Wide Association Study of Major Depressive Disorder.

Jo Nishino, Hidenori Ochi, Yuta Kochi, Tatsuhiko Tsunoda, Shigeyuki Matsui

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In one paragraph

Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed, 3 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

20 citing papers in PubMed, 3 syntheses or guidelines pooled it.

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  11. Analysis of the Associations Between the Human Fecal Microbiome and Bone Density, Structure, and Strength: The Osteoporotic Fractures in Men (MrOS) Cohort.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2022
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Jo NishinoDepartment of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Hidenori OchiCREST, JST, Tokyo, Japan.
Yuta KochiCREST, JST, Tokyo, Japan.
Tatsuhiko TsunodaDepartment of Medical Science Mathematics, Medical Research Institute, Tokyo Medical and Dental University, Tokyo, Japan.
Shigeyuki MatsuiCREST, JST, Tokyo, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Major depressive disorder (MDD) is a complex, heritable psychiatric disorder. Advanced statistical genetics for genome-wide association studies (GWASs) have suggested that the heritability of MDD is largely explained by common single nucleotide polymorphisms (SNPs). However, until recently, there has been little success in identifying MDD-associated SNPs. Here, based on an empirical Bayes estimation of a semi-parametric hierarchical mixture model using summary statistics from GWASs, we show that MDD has a distinctive polygenic architecture consisting of a relatively small number of risk variants (~17%), e.g., compared to schizophrenia (~42%). In addition, these risk variants were estimated to have very small effects (genotypic odds ratio ≤ 1.04 under the additive model). Based on the estimated architecture, the required sample size for detecting significant SNPs in a future GWAS was predicted to be exceptionally large. It is noteworthy that the number of genome-wide significant MDD-associated SNPs would rapidly increase when collecting 50,000 or more MDD-cases (and the same number of controls); it can reach as much as 100 SNPs out of nearly independent (linkage disequilibrium pruned) 100,000 SNPs for ~120,000 MDD-cases.

Indexed as

effect-size distributiongenome-wide association studies (GWAS)genome-wide significancemajor depressive disordersample sizesemi-parametric hierarchical mixture model (SP-HMM)

Identifiers

PMID30002671
PMCPMC6032046

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.