Evidence map›Paper›PMID 23205178›Full record

ArticleInternational journal of molecular epidemiology and genetics2012

Next generation sequencing of CLU, PICALM and CR1: pitfalls and potential solutions.

Jenny Lord, James Turton, Christopher Medway, Hui Shi, Kristelle Brown, James Lowe, David Mann, Stuart Pickering-Brown, Noor Kalsheker, Peter Passmore and 2 more

Open access · greenAbstract read
In one paragraph

Article in International journal of molecular epidemiology and genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.0field-weighted citation impact, top 22% of its field
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

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

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

12 authors at 1 institution in 1 country.

Jenny LordHuman Genetics, School of Molecular Medical Sciences, Queens Medical Centre, University of Nottingham Nottingham, UK.
James Turton
Christopher Medway
Hui Shi
Kristelle Brown
James Lowe
David Mann
Stuart Pickering-Brown
Noor Kalsheker
Peter Passmore
Kevin Morgan
Alzheimer’s Research UK(ARUK) Consortium
University of Nottingham · GB

Funding

Medical Research Council G0701441
6 · The paper itself

Abstract

CLU, PICALM and CR1 were identified as genetic risk factors for late onset Alzheimer's disease (AD) in two large genome wide association studies (GWAS) published in 2009, but the variants that convey this alteration in disease risk, and how the genes relate to AD pathology is yet to be discovered. A next generation sequencing (NGS) project was conducted targeting CLU, CR1 and PICALM, in 96 AD samples (8 pools of 12), in an attempt to discover rare variants within these AD associated genes. Inclusion of repetitive regions in the design of the SureSelect capture lead to significant issues in alignment of the data, leading to poor specificity and a lower than expected depth of coverage. A strong positive correlation (0.964, p<0.001) was seen between NGS and 1000 genome project frequency estimates. Of the ~170 "novel" variants detected in the genes, seven SNPs, all of which were present in multiple sample pools, were selected for validation by Sanger sequencing. Two SNPs were successfully validated by this method, and shown to be genuine variants, while five failed validation. These spurious SNP calls occurred as a result of the presence of small indels and mononucleotide repeats, indicating such features should be regarded with caution, and validation via an independent method is important for NGS variant calls.

Indexed as

Alzheimer’s diseaseCLUCR1genesNext generation sequencingPICALM

Identifiers

PMID23205178
PMCPMC3508540
OpenAlexW1782907294

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.