Review Article | Published:

Paediatric genomics: diagnosing rare disease in children

Nature Reviews Genetics volume 19, pages 253268 (2018) | Download Citation

  • An Erratum to this article was published on 19 February 2018

This article has been updated

Abstract

The majority of rare diseases affect children, most of whom have an underlying genetic cause for their condition. However, making a molecular diagnosis with current technologies and knowledge is often still a challenge. Paediatric genomics is an immature but rapidly evolving field that tackles this issue by incorporating next-generation sequencing technologies, especially whole-exome sequencing and whole-genome sequencing, into research and clinical workflows. This complex multidisciplinary approach, coupled with the increasing availability of population genetic variation data, has already resulted in an increased discovery rate of causative genes and in improved diagnosis of rare paediatric disease. Importantly, for affected families, a better understanding of the genetic basis of rare disease translates to more accurate prognosis, management, surveillance and genetic advice; stimulates research into new therapies; and enables provision of better support.

Key points

  • Genomic technologies have had a greater impact on paediatrics than on many other fields of medicine, and this discipline is leading the way in the implementation of clinical genomics.

  • Appropriate use of whole-exome sequencing (WES) or whole-genome sequencing (WGS) has the potential to curtail the diagnostic process for patients with rare and ultra-rare paediatric disorders, often avoiding the need for invasive and expensive investigations.

  • Although WES and WGS have enormous diagnostic power, data interpretation remains very challenging because of a high incidence of novel and ultra-rare benign variants, incomplete knowledge, false assignment of variant pathogenicity and even false association of genes with disease in the literature.

  • An accurate genetic diagnosis benefits a child by enabling a better understanding of their prognosis, more personalized treatment and tailored management and surveillance. A precise genetic diagnosis also enables accurate genetic advice for individuals and their relatives with increased reproductive choice and improved access to information and support from patient support groups, education, health and social care.

  • WES and WGS require considerable computational resources to process, analyse and store the vast data sets generated by these technologies. For clinicians, the issue of data storage and access is linked to the question of whether their duty of care is limited to finding a diagnosis for the child's immediate problems or whether it extends beyond the scope of the initial investigation.

  • In the future, stratified therapy for rare paediatric disease based on the specific genetic diagnosis is likely to be possible, and effective and affordable therapies are likely to become available through drug repurposing and innovation.

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Change history

  • 19 February 2018

    In Figure 2a of the above article, the resolution of microarrays was originally stated to be 50–100 Mb. The actual resolution is 50–100 kb. In addition, the key for Figure 2b referred to 30,000 coding variants instead of 20,000. These errors have been corrected online. Nature Reviews Genetics apologizes for these errors.

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Acknowledgements

The authors are all members of the management team of the Deciphering Developmental Disorders (DDD) Study, which undertakes independent research commissioned by the Health Innovation Challenge Fund [grant number HICF-1009-003], a parallel funding partnership between the Wellcome Trust and the Department of Health, and the Wellcome Trust Sanger Institute [grant number WT098051]. The views expressed in this publication are those of the authors and not necessarily those of the Wellcome Trust or the Department of Health. The study has UK Research Ethics Committee approval (10/H0305/83, granted by the Cambridge South REC, and GEN/284/12 granted by the Republic of Ireland REC). The research team acknowledges the support of the National Institute for Health Research, through the Comprehensive Clinical Research Network. This study makes use of DECIPHER, which is funded by the Wellcome Trust. H.V.F. is supported by The Wellcome Trust award 200990/Z/16/Z 'Designing, developing and delivering integrated foundations for genomic medicine'.

Author information

Affiliations

  1. University of Exeter Medical School, Institute of Biomedical and Clinical Science, Royal Devon and Exeter Hospital, Barrack Road, Exeter EX2 5DW, UK.

    • Caroline F. Wright
  2. Medical Research Council Human Genetics Unit, The Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh EH4 2XU, UK.

    • David R. FitzPatrick
  3. Cambridge University Hospitals National Health Service Foundation Trust, Cambridge Biomedical Campus, Hills Road, Cambridge CB2 0QQ, UK.

    • Helen V. Firth
  4. Wellcome Trust Sanger Institute, Wellcome Genome Campus, Cambridge, Hinxton CB10 1SA, UK.

    • Helen V. Firth

Authors

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Contributions

C.F.W. and H.V.F. drafted and revised the manuscript. D.R.F. provided editorial input, designed some of the figures and contributed to the ideas and discussions on which the article is based.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Helen V. Firth.

Glossary

Developmental disorders

Diseases with their genesis in embryonic life or early fetal brain development.

Structural variants

Blocks of DNA >1 kb that differ relative to the reference genome or general population, including inversions, balanced translocations and copy number variants (for example, deletions and duplications).

Mosaicism

The presence of two or more populations of cells with different genotypes in an individual who has developed from a single fertilized egg.

Penetrance

The proportion of individuals with a particular genotype who show features of the condition (however mildly). If some individuals with the genotype never show any features, the condition is said to have incomplete (or reduced) penetrance. If features develop with age, the condition is said to have age-dependent penetrance.

Expressivity

The phenotypic variability and severity that a given genotype shows in individuals penetrant for the condition.

Locus heterogeneity

When variants in a number of different genes independently cause the same phenotype.

Allelic heterogeneity

When different mutations at the same locus cause the same phenotype.

Monoallelic

Describes a mutation that affects only one copy of a gene. Autosomal dominant, de novo dominant or X-linked disorders are caused by a monoallelic pathogenic variant.

Biallelic variants

Mutations that affect both copies of a gene. Autosomal recessive disorders are caused by pathogenic biallelic variants.

Whole-exome sequencing

(WES). Next-generation sequencing of the entire protein-coding portion of the genome. In humans, the total length of coding and splicing regions is estimated to be ~35 Mb and comprises ~20,000 genes (1–2% of the genome).

Whole-genome sequencing

(WGS). Next-generation sequencing of the entire genome, which, in humans, is typically ~3,000 Mb.

Single-gene tests

Approaches that enable detailed analysis of a single gene. In addition to sequence analysis, they usually also include an assessment of dosage in order to detect exon-level deletions and duplications, which are often difficult to detect with current approaches to whole-exome sequencing and whole-genome sequencing.

Cytogenetic tests

Genome-wide tests that analyse the number and structure of chromosomes, including copy number variants, but do not provide information about the DNA sequence.

Karyotype

The chromosomal complement of a cell. Large-scale chromosomal imbalances can be detected using karyotyping approaches, such as imaging Giemsa-banded chromosomes with light microscopy.

Copy number variants

(CNVs). Structural variants that involve either a deletion or a duplication of a section of DNA relative to the reference genome.

Single nucleotide variants

(SNVs). Differences within a population, or between an individual and a reference genome, that affect a single base pair of DNA.

Gene panels

Subsets of genes (usually linked to a particular phenotype) that are incorporated into a laboratory-based gene capture kit or that form the basis of computer-based virtual gene panels, which are applied to a subset of variant data from a clinical exome or a whole-exome sequencing and/or whole-genome sequencing assay.

Minor allele frequencies

(MAFs). Measurements of how often the less common allele occurs at a given polymorphic locus.

Human Phenotype Ontology

(HPO). A standardized vocabulary of phenotypic abnormalities encountered in human disease. Each term in the HPO describes a phenotypic abnormality, such as atrial septal defect. The HPO currently contains ~11,000 terms.

Causative genotypes

Genotypes in which a single locus is perturbed and that have a high positive predictive value for a restricted pattern of morphological, biochemical or physiological features of clinical significance.

Blended phenotype

A mixed phenotype that results from causal variants in two or more genes. The phenotypes may either be distinct, with discrete (composite) manifestations, or overlapping, with similar phenotypic manifestations that are impossible to disentangle.

Genetic risk scores

Quantitative measures of genetic predisposition to a trait that are calculated from data for multiple (usually low-risk) genetic variants, which are usually obtained from genome-wide association studies.

Pleiotropy

The phenomenon whereby variants in a single gene may cause multiple phenotypic expressions or disorders.

Transcriptomics

A global approach for looking at gene expression patterns. This can involve measurements of thousands of genes simultaneously with microarrays or measurements of small numbers of genes that are facilitated by global sequence information from expressed sequence tag or genome-sequencing projects.

Epigenomics

A global approach for looking at the complete collection of epigenetic marks, such as DNA methylation and histone modifications, and other molecules that can transmit epigenetic information, such as non-coding RNAs, that exist in a cell at any given point in time.

Metabolomics

A global approach using quantitative analytical methods to look at the entire metabolic content of a cell or organism at a given time.

Proteomics

A global approach for looking at the complete collection of proteins in a cell or tissue at a given time.

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DOI

https://doi.org/10.1038/nrg.2017.116

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