Plenge Lab
Date posted: November 15, 2014 | Author: | No Comments »

Categories: Drug Discovery Human Genetics Precision Medicine

At the Harvard-Partners Personalized Medicine Conference last week I participated in a panel discussion on complex traits. When asked about where personalized medicine for complex traits will be in the future, I answered that I envision two major categories for personalized therapies.

(1)Development of drugs based on genetic targets will lead to personalized medicine; and

(2)Large effect size variants will be detected in clinical trials or in post-approval studies and will lead to personalized medicine.

This answer, I said, was based in part on current categories of FDA pharmacogenetic labels and in part on how I see new drug discovery occurring in the future.  But did the current FDA labels really support this view? 

The answer is “yes”.  In reviewing the 158 FDA labels (Excel spreadsheet here), my crude analysis found that 31% of labels fall into the “genetic target” category (most from oncology – 26% of total) and 65% fall into the “large effect” category (most from drug metabolism [42% of total], HLA or G6PD [15% of total]).

A subtle but important point is that I predict that category #2 (PGx markers for non-oncology “genetic targets”) will grow in the future.  In other words, development of non-oncology drugs will riff-off the success of drugs developed based on somatic cell genetics in oncology. …

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Date posted: March 13, 2013 | Author: | No Comments »

Categories: Human Genetics Precision Medicine

The value of genetics to clinical prediction depends upon the underlying genetic architecture of complex traits (including disease risk and drug efficacy/toxicity).  It is increasingly clear that common variants contribute to common phenotypes, but that extremely large sample sizes are required to tease apart true signal from the noise at a stringent level of statistical significance.  Occasionally, common variants have a large effect on common phenotypes (e.g., MHC alleles and risk of autoimmunity; VKORC1 and warfarin metabolism), but this seems to be the exception rather than the rule.

 A recent paper published in Nature Genetics explores this concept in more detail (download PDF here).  As stated in the manuscript by Chatterjee and colleagues: “The gap between estimates of heritability based on known loci and those estimated owing to the comprehensive set of common susceptibility variants raises the possibility of substantially improving prediction performance of risk models by using a polygenic approach, one that includes many SNPs that do not reach the stringent threshold for genome-wide significance.”  They measure the ability of models based on current as well as future GWAS to improve the prediction of individual traits.  

The results, which are intriguing, depend not only on the underlying genetic architecture (which is often unknown, especially for PGx traits), but also disease prevalence and familial aggregation:  “We observed that for less common, highly familial conditions, such as T1D and Crohn’s disease, risk models that include family history and optimal polygenic scores based on current GWAS can identify a large majority of cases by targeting a small group of high-risk individuals (for example, subjects who fall in the highest quintile of risk).

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Date posted: February 8, 2013 | Author: | No Comments »

Categories: Drug Discovery Precision Medicine

Genetics can guide the first phase of drug development (identifying drug targets, see here ) as well as late phase clinical trials (e.g., patient segmentation for response/non-responder status, see here ). But is there a convergence between the two areas, or pharmaco-convergence (a term I just made up!)? And are there advantages to a program anchored at both ends in human genetics?


Consider the following two hypothetical examples.

(1) Human genetics identifies loss-of-function (LOF) mutations that protect from disease. The same LOF mutation is associated with an intermediate biomarker, but is not associated with other phenotypes that might be considered adverse drug events. A drug is developed that mimics the effect of the mutation; that is, a drug is developed that inhibits the protein product of the gene. In early mechanistic studies, the drug is shown to influence the intermediate biomarker in a way that is consistent to that predicted by the LOF-protective mutations. Further, because functional studies of the LOF-protective mutations provide insight into relevant biological pathways in humans (e.g., a gene expression signature that correlates with mutation carrier status), additional information is known about genomic signatures of those who carry the LOF-protective mutations (which mimics drug exposure) compared to those who do not carry the LOF-protective mutations (which mimics those who are not exposed to drug).…

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Date posted: February 1, 2013 | Author: | No Comments »

Categories: Precision Medicine

Are the same standards applied to genetic and non-genetic tests in clinical medicine?  In a review by Munir Pirmohamed and Dyfrig Hughes (download PDF here), the authors “strongly argue that the slow progress in the implementation of pharmacogenetic (and indeed other genetic) tests can partly be explained by the fact that different criteria are applied when considering genetic testing compared with non-genetic diagnostic tests.”  They provide a few compelling examples:

(1) Atomoxetine

There is no regulatory requirement to undertake clinical trials to show that the dosing recommendations for patients with, for example, renal impairment are equivalent in terms of clinical outcomes to those for patients with normal renal function. Indeed, such a stipulation would be impractical and costly, and would never be done during the drug development process, potentially disadvantaging vulnerable patient populations.

Atomoxetine, a drug widely used for attention deficit hyperactivity disorder, is metabolized in the liver by CYP2D6. The SmPC for atomoxetine states that the dose should be reduced by 50% in patients with hepatic impairment (Child-Pugh class B), as drug exposure goes up by twofold. It is also known that drug exposure is increased by a similar amount in CYP2D6 PMs; however, although the SmPC for atomoxetine mentions the effect of CYP2D6 polymorphisms, it does not mandate testing for their presence.…

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