The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Overcoming Challenges of Real-World Implementation

Shuldiner, Alan R.; Relling, Mary V.; Peterson, Josh F.; Hicks, Kevin; Freimuth, Robert R.; Sadée, Wolfgang; Pereira, Naveen L.; Roden, Dan M.; Johnson, Julie A.; Klein, Teri E.

doi:10.1038/clpt.2013.59

Cited by 161 publications

(152 citation statements)

References 4 publications

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“…These recommendations are available in the Pharmacogenomics Knowledgebase (PharmGKB, www.pharmgkb.org), but significant barriers to the broad adoption of pharmacogenetic testing in clinical practice remain 92 . These barriers include genotyping logistics to provide rapid results; a dearth of prospective, randomized, clinical trials; clinician inexperience with pharmacogenomics; inconsistent reimbursement of pharmacogenomic screening; and a lack of consensus regarding treatment algorithms and professional society recommendations.…”

Section: Methodsmentioning

confidence: 99%

A Physiologic Approach to the Pharmacogenomics of Hypertension

Eadon

Chapman

2016

Advances in Chronic Kidney Disease

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Section: Methodsmentioning

confidence: 99%

A Physiologic Approach to the Pharmacogenomics of Hypertension

Eadon

Chapman

2016

Advances in Chronic Kidney Disease

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“…This personalized strategy may include the use of adjuvant therapies or adjustments in the frequency, volume, mode, and/or intensity of training. Conceptually, it might be possible that testing for ACE I/D genotype and other variants with replicated findings could be implemented similarly to pharmacogenetic implementation programs designed to prevent adverse responses to drug therapy (53). However, additional investigation is needed before such an implementation program could become a reality.…”

Section: Discussionmentioning

confidence: 99%

Genetic influence on exercise-induced changes in physical function among mobility-limited older adults

Buford

Hsu

Brinkley

et al. 2014

Physiological Genomics

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To date, physical exercise is the only intervention consistently demonstrated to attenuate age-related declines in physical function. However, variability exists in seniors' responsiveness to training. One potential source of variability is the insertion (I allele) or deletion (D allele) of a 287 bp fragment in intron 16 of the angiotensin-converting enzyme (ACE) gene. This polymorphism is known to influence a variety of physiological adaptions to exercise. However, evidence is inconclusive regarding the influence of this polymorphism on older adults' functional responses to exercise. This study aimed to evaluate the association of ACE I/D genotypes with changes in physical function among Caucasian older adults ( n = 283) following 12 mo of either structured, multimodal physical activity or health education. Measures of physical function included usual-paced gait speed and performance on the Short Physical Performance Battery (SPPB). After checking Hardy-Weinberg equilibrium, we used using linear regression to evaluate the genotype*treatment interaction for each outcome. Covariates included clinic site, body mass index, age, sex, baseline score, comorbidity, and use of angiotensin receptor blockers or ACE inhibitors. Genotype frequencies [II (19.4%), ID (42.4%), DD (38.2%)] were in Hardy-Weinberg equilibrium ( P > 0.05). The genotype*treatment interaction was statistically significant for both gait speed ( P = 0.002) and SPPB ( P = 0.020). Exercise improved gait speed by 0.06 ± 0.01 m/sec and SPPB score by 0.72 ± 0.16 points among those with at least one D allele (ID/DD carriers), but function was not improved among II carriers. Thus, ACE I/D genotype appears to play a role in modulating functional responses to exercise training in seniors.

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“…[20] This consortium has coauthored a number of publications that inform how to use genetic information in selecting drugs and doses that are beginning to be implemented across diverse health care systems. [21] …”

Section: Practical Hurdles Of Pharmacogenomics Todaymentioning

confidence: 99%

Pharmacogenomics of Metformin- A Way to Personalised medicine

Vakharia¹,

Zad²,

Mankar³

et al. 2016

IJPCS

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Diabetes is fast gaining the status of a potential epidemic in India with more than 62 million diabetic individuals currently diagnosed with the disease. There are atleast 10 different drug classes for the treatment of Type 2 diabetes mellitus (T2DM) but metformin is recommended as the initial medication for treatment of T2DM. Inter-individual variability in response and few clinical or biomarker predictors of response reduces its optimal use. Personalized medicine promises a path for individually optimized treatment, but realizing this promise will require a more comprehensive characterization of disease and drug response. As per American Medical Association, pharmacogenomics is the study of genetic variations that influence individual response to drugs. Knowing whether a patient carries any of these genetic variations can help prescribers individualize drug therapy, decrease the chance for adverse drug events, and increase the effectiveness of drugs. There are variety of genes controlling metformin transport in the body, for eg-SLC22A1, SLC22A2, SLC22A3, SLC22A4 etc. The purpose of this review article is to explain in brief pharmacogenomics of metformin and its application and practical hurdles in its translation.

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The Pharmacogenomics Research Network Translational Pharmacogenetics Program: Overcoming Challenges of Real-World Implementation

Cited by 161 publications

References 4 publications

A Physiologic Approach to the Pharmacogenomics of Hypertension

A Physiologic Approach to the Pharmacogenomics of Hypertension

Genetic influence on exercise-induced changes in physical function among mobility-limited older adults

Pharmacogenomics of Metformin- A Way to Personalised medicine

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