Evidence map›Paper›PMID 39649954›Full record

ArticleCurrent genetic medicine reports2019

Benefits and Challenges of Rare Genetic Variation in Alzheimer's Disease.

Detelina Grozeva, Salha Saad, Georgina E Menzies, Rebecca Sims

Abstract read
In one paragraph

Article in Current genetic medicine reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. Review
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

4 authors.

Detelina GrozevaDivision of Psychological Medicine and Clinical Neuroscience, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK.
Salha SaadDivision of Psychological Medicine and Clinical Neuroscience, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK.
Georgina E MenziesUK Dementia Research Institute at Cardiff, School of Medicine, Cardiff University, Cardiff, UK.
Rebecca SimsDivision of Psychological Medicine and Clinical Neuroscience, MRC Centre for Neuropsychiatric Genetics and Genomics, School of Medicine, Cardiff University, Cardiff, UK.

Funding

Medical Research Council MR/N029402/1Medical Research Council MR/P007651/1
6 · The paper itself

Abstract

Purpose of Review: It is well established that sporadic Alzheimer's disease (AD) is polygenic with common and rare genetic variation alongside environmental factors contributing to disease. Here, we review our current understanding of the genetic architecture of disease, paying specific attention to rare susceptibility variants, and explore some of the limitations in rare variant detection and analysis. Recent Findings: Rare variation has been shown to robustly associate with disease. These include potentially damaging and loss of function mutations that are easily modelled in silico, in vitro and in vivo, and represent potentially druggable targets. A number of risk genes, including Summary: We are at the beginning of our journey of rare variant detection in AD. Whole exome sequencing has been the predominant technology of choice. While fruitful, this has introduced a number of challenges with regard to data integration. Ultimately the future of disease-associated rare variant identification lies in whole genome sequencing projects that will allow the testing of the full range of genomic variation.

Indexed as

Alzheimer’s diseaseGeneticsRare variantsSusceptibility

Identifiers

PMID39649954
PMCPMC7617023

What OpenQuestion holds

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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.