Evidence map›Paper›PMID 39741260›Full record

ArticleBMC genomics2024

Nanopore sequencing as a novel method of characterising anorexia nervosa risk loci.

Natasha Berthold, Silvana Gaudieri, Sean Hood, Monika Tschochner, Allison L Miller, Jennifer Jordan, Laura M Thornton, Cynthia M Bulik, Patrick Anthony Akkari, Martin A Kennedy

Abstract read
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 2 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

3 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
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

10 authors.

Natasha BertholdUniversity of Western Australia, Crawley, WA, Australia. natasha.berthold@research.uwa.edu.au.
Silvana GaudieriUniversity of Western Australia, Crawley, WA, Australia.
Sean HoodUniversity of Western Australia, Crawley, WA, Australia.
Monika TschochnerUniversity of Notre Dame Australia, Fremantle, WA, Australia.
Allison L MillerPathology and Biomedical Science Department, University of Otago Christchurch, Christchurch, New Zealand.
Jennifer JordanDepartment of Psychological Medicine, University of Otago Christchurch, Christchurch, New Zealand.
Laura M ThorntonDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA.
Cynthia M BulikDepartment of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA.
Patrick Anthony Akkari *University of Western Australia, Crawley, WA, Australia.
Martin A Kennedy *Pathology and Biomedical Science Department, University of Otago Christchurch, Christchurch, New Zealand.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAnorexia nervosa (AN) is a polygenic, severe metabopsychiatric disorder with poorly understood aetiology. Eight significant loci have been identified by genome-wide association studies (GWAS) and single nucleotide polymorphism (SNP)-based heritability was estimated to be ~ 11-17, yet causal variants remain elusive. It is therefore important to define the full spectrum of genetic variants in the wider regions surrounding these significantly associated loci. The hypothesis we evaluate here is that unrecognised or relatively unexplored variants in these regions exist and are promising targets for future functional analyses. To test this hypothesis, we implemented a novel approach with targeted nanopore sequencing (Oxford Nanopore Technologies) for 200 kb regions centred on each of the eight AN-associated loci in 10 AN case samples. Our bioinformatics pipeline entailed base-calling and alignment with Dorado and minimap2 software, followed by variant calling with four separate tools, Sniffles2, Clair3, Straglr, and NanoVar. We then leveraged publicly available databases to characterise these loci in putative functional context and prioritise a subset of potentially relevant variants.

resultsTargeted nanopore sequencing effectively enriched the target regions (average coverage 14.64x). To test our hypothesis, we curated a list of 20 prioritised variants in non-coding regions, poorly represented in the current human reference genome but that may have functional consequences in AN pathology. Notably, we identified a polymorphic SINE-VNTR-Alu like sub-family D element (SVA-D), intergenic with IP6K2 and PRKAR2A, and a poly-T short tandem repeat (STR) in the 3'UTR of FOXP1.

conclusionsOur results highlight the potential of targeted nanopore sequencing for characterising poorly resolved or complex variation, which may be initially obscured in risk-associated regions detected by GWAS. Some of the variants identified in this way, such as the polymorphic SVA-D and poly-T STR, could contribute to mechanisms of phenotypic risk, through regulation of several neighbouring genes implicated in AN biology, and affect post-transcriptional processing of FOXP1, respectively. This exploratory investigation was not powered to detect functional effects, however, the variants we observed using this method are poorly represented in the current human reference genome and accompanying databases, and further examination of these may provide new opportunities for improved understanding of genetic risk mechanisms of AN.

Indexed as

Anorexia NervosaGenetic Predisposition to DiseaseNanopore SequencingPolymorphism, Single NucleotideComputational BiologyFemaleGenetic LociGenome-Wide Association StudyHumansAdaptive samplingAnorexia nervosa risk lociEating disordersLong-read sequencingNanopore sequencingPsychiatric geneticsStructural variantsTargeted sequencingTransposable elements

Identifiers

PMID39741260
PMCPMC11687000

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.