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Prognosis in autoimmune and infectious disease: new insights from genetics.

Lee JC, Smith KG - Clin Transl Immunology (2014)

Bottom Line: A well-recognised feature of autoimmune and infectious diseases is that their clinical course and eventual outcome can vary substantially between affected individuals.This variability in disease prognosis critically determines patient well-being, and yet is relatively poorly understood and largely understudied-with many investigators opting instead to study what causes disease development in the first place.Here, we highlight the previously under-appreciated role that genetics has in determining prognosis in autoimmune and infectious disease, and the common role that FOXO3 has been shown to have as a modulator of inflammatory responses, and thereby of outcome, across several distinct diseases.

View Article: PubMed Central - PubMed

Affiliation: Cambridge Institute for Medical Research, Cambridge Biomedical Campus , Cambridge, UK ; Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus , Cambridge, UK.

ABSTRACT
A well-recognised feature of autoimmune and infectious diseases is that their clinical course and eventual outcome can vary substantially between affected individuals. This variability in disease prognosis critically determines patient well-being, and yet is relatively poorly understood and largely understudied-with many investigators opting instead to study what causes disease development in the first place. Better understanding of what determines prognosis could provide unique insights into disease biology, potentially revealing new therapeutic targets, and will also be essential if prognosis-based 'personalised medicine' is ever to become a reality. Here, we highlight the previously under-appreciated role that genetics has in determining prognosis in autoimmune and infectious disease, and the common role that FOXO3 has been shown to have as a modulator of inflammatory responses, and thereby of outcome, across several distinct diseases.

No MeSH data available.


Related in: MedlinePlus

Comparison of patients with contrasting phenotypes within a GWAS cohort can leverage new insights into other aspects of disease biology. Standard GWAS analysis compares the allele frequency at single-nucleotide polymorphisms located throughout the genome between cases and controls, and thus facilitates the hypothesis-free discovery of genes that predispose to specific diseases. However, this approach will fail to account for important heterogeneity within the disease cohort. By exploiting allied phenotypic data, it is possible to examine the genetic contribution to such aspects of disease biology (including prognosis) by comparing the genetic profiles of patients with contrasting clinical phenotypes—a so-called ‘within-cases' analysis.
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fig1: Comparison of patients with contrasting phenotypes within a GWAS cohort can leverage new insights into other aspects of disease biology. Standard GWAS analysis compares the allele frequency at single-nucleotide polymorphisms located throughout the genome between cases and controls, and thus facilitates the hypothesis-free discovery of genes that predispose to specific diseases. However, this approach will fail to account for important heterogeneity within the disease cohort. By exploiting allied phenotypic data, it is possible to examine the genetic contribution to such aspects of disease biology (including prognosis) by comparing the genetic profiles of patients with contrasting clinical phenotypes—a so-called ‘within-cases' analysis.

Mentions: Whether genetic variation might play a role in determining disease prognosis was largely unknown, for while disease susceptibility loci may not influence prognosis, this does not preclude the existence of other genetic variants that do. Indeed, given that GWAS identifies disease susceptibility loci through comparison of unstratified cases and controls, it would not be expected to reveal genetic variants that specifically associated with the outcome. This is because although the cases may share a common diagnosis, their clinical outcomes will be heterogeneous, such that a true prognostic variant may only be more common in a small subgroup of patients (for example, those with aggressive disease) and will also be reciprocally less common in another subgroup (for example, those with mild disease). We therefore hypothesised that to assess whether genetic variation influences disease course, a ‘within-cases' analysis would be necessary, in which the genetic profiles of patients with contrasting courses of disease could be directly compared (Figure 1). Here, we discuss our application of this approach to Crohn's disease (CD), a chronic and disabling form of inflammatory bowel disease, and the insights that a candidate gene study, recently published in Cell,6 have yielded both into the role of genetics in prognosis and also into the critical function of FOXO3 in regulating inflammation and thereby determining the outcome of autoimmune and infectious diseases.


Prognosis in autoimmune and infectious disease: new insights from genetics.

Lee JC, Smith KG - Clin Transl Immunology (2014)

Comparison of patients with contrasting phenotypes within a GWAS cohort can leverage new insights into other aspects of disease biology. Standard GWAS analysis compares the allele frequency at single-nucleotide polymorphisms located throughout the genome between cases and controls, and thus facilitates the hypothesis-free discovery of genes that predispose to specific diseases. However, this approach will fail to account for important heterogeneity within the disease cohort. By exploiting allied phenotypic data, it is possible to examine the genetic contribution to such aspects of disease biology (including prognosis) by comparing the genetic profiles of patients with contrasting clinical phenotypes—a so-called ‘within-cases' analysis.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4232069&req=5

fig1: Comparison of patients with contrasting phenotypes within a GWAS cohort can leverage new insights into other aspects of disease biology. Standard GWAS analysis compares the allele frequency at single-nucleotide polymorphisms located throughout the genome between cases and controls, and thus facilitates the hypothesis-free discovery of genes that predispose to specific diseases. However, this approach will fail to account for important heterogeneity within the disease cohort. By exploiting allied phenotypic data, it is possible to examine the genetic contribution to such aspects of disease biology (including prognosis) by comparing the genetic profiles of patients with contrasting clinical phenotypes—a so-called ‘within-cases' analysis.
Mentions: Whether genetic variation might play a role in determining disease prognosis was largely unknown, for while disease susceptibility loci may not influence prognosis, this does not preclude the existence of other genetic variants that do. Indeed, given that GWAS identifies disease susceptibility loci through comparison of unstratified cases and controls, it would not be expected to reveal genetic variants that specifically associated with the outcome. This is because although the cases may share a common diagnosis, their clinical outcomes will be heterogeneous, such that a true prognostic variant may only be more common in a small subgroup of patients (for example, those with aggressive disease) and will also be reciprocally less common in another subgroup (for example, those with mild disease). We therefore hypothesised that to assess whether genetic variation influences disease course, a ‘within-cases' analysis would be necessary, in which the genetic profiles of patients with contrasting courses of disease could be directly compared (Figure 1). Here, we discuss our application of this approach to Crohn's disease (CD), a chronic and disabling form of inflammatory bowel disease, and the insights that a candidate gene study, recently published in Cell,6 have yielded both into the role of genetics in prognosis and also into the critical function of FOXO3 in regulating inflammation and thereby determining the outcome of autoimmune and infectious diseases.

Bottom Line: A well-recognised feature of autoimmune and infectious diseases is that their clinical course and eventual outcome can vary substantially between affected individuals.This variability in disease prognosis critically determines patient well-being, and yet is relatively poorly understood and largely understudied-with many investigators opting instead to study what causes disease development in the first place.Here, we highlight the previously under-appreciated role that genetics has in determining prognosis in autoimmune and infectious disease, and the common role that FOXO3 has been shown to have as a modulator of inflammatory responses, and thereby of outcome, across several distinct diseases.

View Article: PubMed Central - PubMed

Affiliation: Cambridge Institute for Medical Research, Cambridge Biomedical Campus , Cambridge, UK ; Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus , Cambridge, UK.

ABSTRACT
A well-recognised feature of autoimmune and infectious diseases is that their clinical course and eventual outcome can vary substantially between affected individuals. This variability in disease prognosis critically determines patient well-being, and yet is relatively poorly understood and largely understudied-with many investigators opting instead to study what causes disease development in the first place. Better understanding of what determines prognosis could provide unique insights into disease biology, potentially revealing new therapeutic targets, and will also be essential if prognosis-based 'personalised medicine' is ever to become a reality. Here, we highlight the previously under-appreciated role that genetics has in determining prognosis in autoimmune and infectious disease, and the common role that FOXO3 has been shown to have as a modulator of inflammatory responses, and thereby of outcome, across several distinct diseases.

No MeSH data available.


Related in: MedlinePlus