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On April 16, The New York Times published an article, “Genes Show Limited Value in Predicting Diseases,” based on commentaries and a review article on genetic risk prediction in the April 23 issue of The New England Journal of Medicine. The New York Times quoted one of the authors, David B. Goldstein, as saying, “With only a few exceptions, what the genomics companies [that offer personal genomic information] are doing right now is recreational genomics.” (I inserted the clarification to emphasize that Goldstein was not talking about genomics companies in general—only those that are offering personal genomic information to physicians and patients.) Curious, I downloaded the original papers.

Goldstein’s article, “Common Genetic Variation and Human Traits,” asserts that genomewide association studies are not an efficient way to identify gene variants capable of predicting risk in any meaningful way, and that the more gene variants associated with a given disease, the more time- and resource-intensive it would be to identify a manageable and usable set of risk predictor genes. The article also offers the interesting perspective that the “apparently modest effect of common variation on most human diseases and related traits probably reflects the efficiency of natural selection in prohibiting increases in disease-associated variables in the population.” And Goldstein points to the promise of looking at polymorphisms associated with responses to drugs or infectious agents. (Being a marketer, I am always looking for the silver lining.)

In “Genomewide Association Studies—Illuminating Biologic Pathways,” Joel N. Hirschhorn offers a different perspective—that the main goal of genomewide association studies is not to figure out how to predict individual risk of diseases and traits, but to elucidate underlying biologic pathways. As an example, he notes that of the 23 loci found to be associated with lipid levels in genomewide studies, 11 point to genes that have previously been shown to encode key proteins involved in lipid metabolism. Hirschhorn goes on to enumerate a number of genes encoding sites of action of drugs approved by the FDA that have been similarly identified. Citing the distance between the deciphering of the chemical composition of cholesterol and the development of statins, which were separated by “nearly a century and three Nobel Prizes,” he cautions that “each discovery of a biologically relevant locus is a potential first step in a translational journey” and that “some journeys will be shorter than others.”

Peter Kraft and David J. Hunter raise the question, “Genetic Risk Prediction—Are We There Yet?” and concur that there are few monogenic diseases. For example, Crohn’s disease is associated with more than 30 loci and thus potentially more than 30 genes. The graph on page 1702 of the article shows that the higher the number of undiscovered genetic factors for the disease, the lower the likelihood of assessing the risk level for the disease in any meaningful way. Kraft and Hunter outline factors determining the clinical value of a genetic test, and point out the importance of looking not only at test performance (sensitivity, specificity, positive and negative predictive values) but also at costs and benefits of interventions, as well as outcome data, in determining the clinical value of a genetic test. Most important, the authors suggest that while testing for genetic risk may not be here today, it may only be two or three years away, and advocate the urgent need to develop guidelines for physicians, which are now lacking.

John Hardy and Andrew Singleton’s review article, “Genomewide Association Studies and Human Disease,” is an excellent backgrounder for anyone with any interest in this field. It details the stages of a genomewide association study, summarizes its benefits, misconceptions and limitations and offers a helpful glossary. Importantly, it includes an elegant explanation of genetic variability in gene expression, which adds yet another dimension to the understanding of genetic risk of diseases—“moving from dichotomous to graded genetic risk” as the authors subtitled one of the paragraphs. What I found very interesting, also, is the notion that the interaction between genome and environment, which many people like me believed was a given, has not been demonstrated for the most part. And, like the other reviewers, Hardy and Singleton are largely optimistic about the future and the scientific community’s ability to solve the complex puzzle of genes and diseases.

1. Paint a clear picture of the desired outcome by writing clear statements of objectives that are intended to drive action. Some people confuse objectives with just a description of the assignment. For example, “Develop a new ad campaign for XYZ brand” is not a statement of objective; “Correct misperception of XYZ brand” is.

2. Make the target audience come to life. Go beyond the basics such as job titles and roles in decision-making process to a snapshot of the audience as people. That will help the creative team connect to them as humans. Draw on the audience analysis you probably have done already in earlier strategic development processes.

3. Help the creative team envision the competitive environment (trends, recent developments) and explain the rationale for the communication program in this context. For example, this is a preemptive strike against a competitive new product. Go beyond comparisons of your brand vs. the competition.

4. Don’t send your writers on a fishing expedition with a general dump of monographs, reprints, data sheets etc. Guide the writing team with clear and concise direction. Your message platform is a strategic document and a good starting point, but your writing team will benefit from additional input on what’s important and what’s secondary as they review these documents.

5. Satisfy your writers’ curiosity. A corollary to providing clear direction to the writing team is to include relevant source materials. Writers are curious and, in our space, analytical people who often want to fact check and verify your synthesis of the information sources.

6. Make your single most important message singular. In my experience, this is the most difficult task—to zero in on the one message that is relevant and powerful enough to motivate the audience to take action. This is especially important in advertising, when appending to a singular, core message does little more than confuse the audience by losing focus.

Did I forget something? Please add to this list or expand on some of the points by posting your comment below.

Solving the Puzzle: Living Longer, Living Well and Reversing the Epidemic of Alzheimer’s and Related Disorders was the title of a lively panel discussion that launched Penn Medicine Advances, a seminar series hosted by the University of Pennsylvania School of Medicine (Penn), last week. The topic is timely—note the publicity generated by the unveiling of the strategic plan by the Alzheimer’s Study Group and the Study Group’s vocal co-chair Newt Gingrich.

NIH’s announcement on an important step in biomarker testing for Alzheimer’s disease, based on levels of amyloid beta42 peptide and tau protein, sparked discussion about the value of testing when today’s Alzheimer’s therapeutics are limited largely to symptomatic relief. Virginia Lee, PhD, director, Center for Neurodegenerative Disease Research at Penn, pointed out that while there are many drugs for Alzheimer’s disease in clinical trials today, biomarkers for assessing disease progress and therapeutic effectiveness are glaringly missing. Biomarkers also have a role in studies to identify risk factors, in particular life style-related risk factors such as obesity and metabolic syndromes, both of which have been implicated in Alzheimer’s disease.

Jason Karlawish, MD, associate professor of Medicine and Medical Ethics, suggested that Alzheimer’s disease may have a different name a few years from now, as medicine increasingly thinks of cognitive impairment or decline as a disability and one that does not have to progress to disease and sequelae. Karlawish used hypertension as an example, where the standard of care today is to treat hypertension rather than wait until progression to kidney failure. But, he also cautioned that while early diagnosis and preventive care are important, they have to be considered “in a way that respects the cost.” This is especially important due to the rising prevalence and societal burden of Alzheimer’s disease. Steve Arnold, MD, director of Penn Memory Center, added that there are several drugs in late phase clinical trials targeting the pathology (e.g., amyloids and tau proteins), and animal studies suggest that early diagnosis and early treatment, ideally before disease onset, will prove the most beneficial. John Trojanowski, MD, director of Penn’s Institute On Aging, noted that pharmacoeconomic models project that a five to seven-year delay of disease onset in the high-risk age groups can dramatically reduce prevalence and thus associated costs—another reminder of the importance of identifying and educating the public about the impact of lifestyle on the disease.

The discussion turned to an emerging model of academia-industry collaboration, where pharmaceutical companies contribute funding for drug discovery programs at Penn in exchange for early access and rights of refusal to discoveries. In many ways, academia offers more research continuity within a naturally multidisciplinary environment and the ability to draw from rich experience and diverse models. Arnold spoke of Penn’s vertical integration from basic research to clinical practice and ethics and societal issues. And, indeed, judging from the audience in the room, with representatives from academia, industry, media and the community, integration is inherent to a disease that touches on so many facets of society.

If you are interested, HBO has a new series, The Alzheimer’s Project: Momentum in Science. Part 1 will air Monday, May 11th at 8pm ET/PT; Part 2 will air on Tuesday, May 12, also at 8pm ET/PT.

Most of us are continually challenged to deliver more for our marketing communication budget. One good place to start is to take a look at your website. There are a lot of free or almost free tools and information on the Internet. Taking the time to learn about them and allocating a modest budget to get your IT support team to deploy some of these tools could yield good returns in a relatively short time.

Start by taking a look at how your website is doing—traffic patterns, visitor profiles, how the site is being used, etc. Google Analytics not only provides great tools, which you or your IT team can customize, but also case studies and tutorials that I found very helpful in bringing me up to speed on relevant metrics and how to improve them. Check your web hosting service—many also offer analytics, sometimes complementary to what you can get on Google.

For most websites, search engines are the main source of incoming traffic. It is no wonder that search engine optimization (SEO) consultants command premium fees for their expertise. Whether or not you have the budget to retain SEO consultants, understanding the basics goes a long way. Google offers a very comprehensive, easy-to-read starter guide that you can download and review. Obviously, SEO is something you want to consider when you’re building the site, not after the fact. However, even if you are not planning a major overhaul of your site anytime soon, you can make incremental improvements as you upload new content onto your site and definitely when you update sections—for example, to support a new product launch or product enhancement.

Give it a try. Just taking an analytical look at your website and implementing some basic good SEO practices may yield surprising returns. What do you think? Drop me a note or post a comment.