Towards Precision Medicine: Advances in Computational Approaches for the Analysis of Human Variants

Peterson, Thomas; Doughty, Emily; Kann, Maricel G.

doi:10.1016/j.jmb.2013.08.008

Cited by 121 publications

(123 citation statements)

References 172 publications

(174 reference statements)

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“…In the absence of experimental data, in silico algorithms can provide some guidance regarding the predicted functional consequences of the genetic variant [90]. Ideally, the results of multiple such computational methods are integrated that base their conclusions on diverse and complementing sets of criteria, including evolutionary conservation, physiochemical properties, secondary structure, variant effects on protein stability, and protein domain information [91]. The predictive power of algorithms to detect functional alterations in the gene product is however relatively low, particularly in ADME genes.…”

Section: Rare Variants and Precision Medicinementioning

confidence: 99%

Pharmacogenomic Biomarkers for Improved Drug Therapy—Recent Progress and Future Developments

Lauschke

Milani

Ingelman‐Sundberg

2017

AAPS J

114

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Abstract.Much of the inter-individual variability in drug efficacy and risk of adverse reactions is due to polymorphisms in genes encoding proteins involved in drug pharmacokinetics and pharmacodynamics or immunological responses. Pharmacogenetic research has identified a multitude of gene-drug response associations, which have resulted in genetically guided treatment and dosing decisions to yield a higher success rate of pharmacological treatment. The rapid technological developments for genetic analyses reveal that the number of genetic variants with importance for drug action is much higher than previously thought and that a true personalized prediction of drug response requires attention to millions of rare mutations. Here, we review the evolutionary background of genetic polymorphisms in drugmetabolizing enzymes, provide some important examples of current use of pharmacogenomic biomarkers, and give an update of germline and somatic genome biomarkers that are in use in drug development and clinical practice. We also discuss the current technology development with emphasis on complex genetic loci, review current initiatives for validation of pharmacogenomic biomarkers, and present scenarios for the future taking rare genetic variants into account for a true personalized genetically guided drug prescription. We conclude that pharmacogenomic information for patient stratification is of value to tailor optimized treatment regimens particularly in oncology. However, the routine use of pharmacogenomic biomarkers in clinical practice in other therapeutic areas is currently sparse and the prospects of its future implementation are being scrutinized by different international consortia.

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Section: Rare Variants and Precision Medicinementioning

confidence: 99%

Pharmacogenomic Biomarkers for Improved Drug Therapy—Recent Progress and Future Developments

Lauschke

Milani

Ingelman‐Sundberg

2017

AAPS J

114

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“…(28)(29)(30)(31) We utilized the free energy perturbation (FEP) (32,33) method based on standard molecular dynamics sampling 6 and also several other methods that are known to be fast to obtain a consensus prediction. Below, the FEP method implementation in the current work is described along with other methods and webservers utilized.…”

Section: In Silico Modelingmentioning

confidence: 99%

Impact of Rett Syndrome Mutations on MeCP2 MBD Stability

et al. 2015

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Rett syndrome causing missense mutations in the methyl-CpG-binding domain (MBD) of methyl CpG-binding protein 2 (MeCP2) were investigated both in silico and in vitro to reveal their effect on protein stability. It is demonstrated that the vast majority of frequently occurring mutations in the human population indeed alter the MBD folding free energy by a fraction of a kcal/mol up to more than 1 kcal/mol. While the absolute magnitude of the change of the free energy is small, the effect on the MBD functionality may be substantial since the folding free energy of MBD is about 2 kcal/mol only. Thus, it is emphasized that the effect of mutations on protein integrity should be evaluated with respect to the wild-type folding free energy but not with the absolute value of the folding free energy change. Furthermore, it was observed that the magnitude of the effect is correlated neither with the burial of the mutation sites nor with the basic amino acid physicochemical property change. Mutations that strongly perturb the immediate structural features were found to have little effect on folding free energy, while very conservative mutations resulted in large changes of the MBD stability. This observation was attributed to the protein's ability to structurally relax and reorganize to reduce the effect of mutation. Comparison between in silico and in vitro results indicated that some Web servers perform relatively well, while the free energy perturbation approach frequently overpredicts the magnitude of the free energy change especially when a charged amino acid is involved.

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“…In this context, efforts are put toward to the computational identification of features allowing prioritizing variants for follow-up in genetic and functional analysis. Strategies to attribute a severity score to a variant, recently reviewed in [2], include approaches based on evolutionary, physico-chemical and structural…”

Section: Introductionmentioning

confidence: 99%

Analysis of stop-gain and frameshift variants in human innate immunity genes

Rausell

Mohammadi

McLaren

et al. 2014

Preprint

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Loss-of-function variants in innate immunity genes are associated with Mendelian disorders in the form of primary immunodeficiencies. Recent resequencing projects report that stop-gains and frameshifts are collectively prevalent in humans and could be responsible for some of the inter-individual variability in innate immune response. Current computational approaches evaluating loss-of-function in genes carrying these variants rely on gene-level characteristics such as evolutionary conservation and functional redundancy across the genome. However, innate immunity genes represent a particular case because they are more likely to be under positive selection and duplicated. To create a ranking of severity that would be applicable to the innate immunity genes we first evaluated 17764 stop-gain and 13915 frameshift variants from the NHLBI Exome Sequencing Project and 1000 Genomes Project. Sequence-based features such as loss of functional domains, isoform-specific truncation and non-sense mediated decay were found to correlate with variant allele frequency and validated with gene expression data.We integrated these features in a Bayesian classification scheme and benchmarked its use in predicting pathogenic variants against OMIM disease stop-gains and frameshifts. The classification scheme was applied in the assessment of 335 stop-gains and 236 frameshifts affecting 227 interferon-stimulated genes. The sequence-based score ranks variants in innate immunity genes according to their potential to cause disease, and complements existing genebased pathogenicity scores. Author summaryThere are well characterized severe immunodeficiencies associated with loss-of-function variants in innate immunity genes. Genome sequencing projects identify rare stop-gain and frameshift variants in innate immunity genes whose phenotype is uncharacterized. Current methods to estimate the severity of rare stop-gains and frameshifts are based on evolutionary conservation of the gene and the likelihood for redundancy in its function. These parameters are not always applicable to innate immunity genes. We evaluated sequence-level characteristics of more than 30'000 stop-gains and frameshifts and prioritized variants according to their predicted functional consequences. Our scoring approach complements existing tools in the prediction of innate immunity OMIM disease variants and associates with functional readouts such as gene expression. In this framework, we show that many individuals do carry high pathogenicity peer-reviewed)

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Towards Precision Medicine: Advances in Computational Approaches for the Analysis of Human Variants

Cited by 121 publications

References 172 publications

Pharmacogenomic Biomarkers for Improved Drug Therapy—Recent Progress and Future Developments

Pharmacogenomic Biomarkers for Improved Drug Therapy—Recent Progress and Future Developments

Impact of Rett Syndrome Mutations on MeCP2 MBD Stability

Analysis of stop-gain and frameshift variants in human innate immunity genes

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