Evidence map›Paper›PMID 22739340›Full record

ReviewEuropean journal of human genetics : EJHG2013

RNA-Seq and human complex diseases: recent accomplishments and future perspectives.

Valerio Costa, Marianna Aprile, Roberta Esposito, Alfredo Ciccodicola

Open access · bronzeAbstract readReview
In one paragraph

Review in European journal of human genetics : EJHG, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 116 papers.

0numbers the graph read from it
0cells of the map it votes in
116citing papers in PubMed
7.9field-weighted citation impact, top 2% 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

116 citing papers in PubMed, 279 citations in OpenAlex.

  1. Hybrid Encoding and Adaptive Guidance for Enhanced Single-Cell Multi-omics Clustering.Interdisciplinary sciences, computational life sciences · 2026
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  13. ntEmbd: Deep learning embedding for nucleotide sequences.bioRxiv : the preprint server for biology · 2024
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56 more citing papers are in PubMed but not listed here.

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 at 1 institution in 1 country.

Valerio CostaConsiglio Nazionale delle Ricerche, Institute of Genetics and Biophysics A. Buzzati-Traverso, Naples, Italy. valerio.costa@igb.cnr.it
Marianna Aprile
Roberta Esposito
Alfredo Ciccodicola
Institute of Genetics and Biophysics · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The availability of the human genome sequence has allowed identification of disease-causing mutations in many Mendelian disorders, and detection of significant associations of nucleotide polymorphisms to complex diseases and traits. Despite these progresses, finding the causative variations for most of the common diseases remains a complex task. Several studies have shown gene expression analyses provide a quite unbiased way to investigate complex traits and common disorders' pathogenesis. Therefore, whole-transcriptome analysis is increasingly acquiring a key role in the knowledge of mechanisms responsible for complex diseases. Hybridization- and tag-based technologies have elucidated the involvement of multiple genes and pathways in pathological conditions, providing insights into the expression of thousand of coding and noncoding RNAs, such as microRNAs. However, the introduction of Next-Generation Sequencing, particularly of RNA-Seq, has overcome some drawbacks of previously used technologies. Identifying, in a single experiment, potentially novel genes/exons and splice isoforms, RNA editing, fusion transcripts and allele-specific expression are some of its advantages. RNA-Seq has been fruitfully applied to study cancer and host-pathogens interactions, and it is taking first steps for studying neurodegenerative diseases (ND) as well as neuropsychiatric diseases. In addition, it is emerging as a very powerful tool to study quantitative trait loci associated with gene expression in complex diseases. This paper provides an overview on gene expression profiling of complex diseases, with emphasis on RNA-Seq, its advantages over conventional technologies for studying cancer and ND, and for linking nucleotide variations to gene expression changes, also discussing its limitations.

Indexed as

Gene Expression ProfilingGenetic Diseases, InbornHigh-Throughput Nucleotide SequencingQuantitative Trait, HeritableExonsGenome, HumanHumansOligonucleotide Array Sequence AnalysisRNATranscriptomeRNA

Identifiers

PMID22739340
PMCPMC3548270
OpenAlexW2066617774

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.