Plenge Lab
Date posted: May 17, 2013 | Author: | No Comments »

Categories: Drug Discovery Human Genetics


After all, baseball is a metaphor for life.

Bill James developed the “Keltner list” to serve as a series of gut-check questions to test a baseball player’s suitability for the Hall of Fame (see here).  The list comprises 15 questions designed to aid in the thought process, where each question is designed to be relatively easy to answer.  As a subjective method, the Keltner list is not designed to yield an undeniable answer about a player’s worthiness.  Says James: “You can’t total up the score and say that everybody who is at eight or above should be in, or anything like that.”

The Keltner list concept has been adapted to address to serve as a common sense assessment of non-baseball events, including political scandals (see here) and rock bands like Devo (see here).

Here, I try out this concept for genetics and drug discovery.  That is, I ask a series of question designed to answer the question: “Would a drug against the product of this gene be a useful drug?”  I use PCSK9 as one of the best examples (see brief PCSK9 slide deck here).  I also used in on our recent study of CD40 in rheumatoid arthritis, published in PLoS Genetics (see here).

Comments and feedback are welcome!

1. Does the gene harbor a causal variant that is unequivocally associated with a medical trait of interest?

It is critical that the genetic finding be robust.  Consistent replication of the genetic finding is one of the most important measures of significance.  For PCSK9 – yes.  Variants are reproducibly associated with LDL cholesterol levels and coronary heart disease.

2. Is the biological function of the causal gene and causal variant known? 

You need to know whether a gene is a positive or negative regulator of a pathway, and where a variant is a gain-of-function (GOF) or loss-of-function (LOF). Studies in human tissues are invaluable for understanding the effects of individual alleles, and animal models can be very helpful in understanding the function of the gene itself.  For PCSK9 – yes. Studies in human and animal models provides a mechanistic understanding of the role of PCSK9 in cholesterol metabolism.

3. Does the gene harbor multiple causal variants of known biological function? 

Evidence that multiple alleles influence the trait, or a related trait, provides evidence for dose-response curves at the time of target validation.  For PCSK9 – yes. The gene has both GOF and LOF alleles.

4. Is the causal variant a LOF allele that protects against disease or GOF allele that increases risk of disease? 

The rationale behind this criterion is that it is easier to develop drugs that are inhibitors rather than activators of protein targets. For PCSK9 – yes and yes.

5. Is the genetic trait related to the clinical indication targeted for treatment? 

Accordingly, the clinical indication for drug development must be precisely defined, and supporting evidence must link the biological pathways underlying the genetic trait to the biological pathways for the clinical indication for treatment.  For PCSK9 – yes.

6. Is the causal variant also associated with an intermediate phenotype that can be used as a biomarker?

A relevant biomarker will help with PK/PD studies, as well as early proof-of-concept mechanistic studies in humans.  For some alleles, a relevant biomarker may be developed during the course of functional studies, which can then be used during clinical trials. For PCSK9 – yes. LDL cholesterol is a great biomarker.

7. Is the gene product “druggable”?

One of the challenges for human genetics is that only a subset of potential drug targets is “druggable” using standard chemistry and assays.  Thus, human genetics may uncover exciting new targets, but if these are not druggable, then little is gained. What is considered druggable today is likely to change in the future, however. For PCSK9 – yes, via monoclonal antibodies against the cell-surface receptor.

8. Is the variant associated with other phenotypes that might be considered “adverse events”? 

This is an interesting aspect of human genetics that can be used to predict “on-target” side effects.  It serves as a form of “Mendelian randomization”.  If a drug inhibits function of a gene product, then it would be useful to know the clinical consequences of an allele that knocks-out function of the same gene.  I predict that genetic data linked to clinical data from electronic medical records (EMR) will be a valuable tool to assess toxicity. For PCSK9 – probably yes.  I haven’t seen a rigorous test of this question.

9. Is there corroborating biological data to support the genetic findings? 

Genetic data should be integrated with other aspects of disease biology – including animal models, epidemiological studies, and in vivo expression studies.  If non-genetic data support the role implicated by the associated gene, then this strengthens greatly relevance to disease.  For PCSK9 – yes.

If you have any COMMENTS or feedback, please post them below.

And if anyone cares…here is my prediction about the 2013 Red Sox, which really has nothing to do with the list above, other than a connection with baseball.

1. They will win between 85-90 games, but likely miss the playoffs.

2. They have an outside chance of making it to the World Series IF: (a) the stop three starting pitchers (likely Lester, Bucholtz and Dempster) pitch in >90% of scheduled starts and the team wins about two-thirds of those games [or about 60 wins in total]; (b) the bullpen develops an obvious set-up guy (likely Tazawa or Uehara) and closer (likely Bailey); (c) the five batters at the top of the order “catch fire” during the last month of the season (September), with an average on-base percentage around 0.400 with evidence of power; and (d) the schedule at the end of the season works out for them such that they are able to line up their starting three pictures on better-than-average rest.

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