Authors: Anne MacGregor & Alec Mian
We can easily recognize the face of someone we know from thousands if not millions of other humans. However, it turns out that individual differences in physical appearance are dwarfed by the biochemical differences within us. In the middle of the last century, Roger J. Williams, PhD, a distinguished American scientist specializing in nutrition at University of Texas, argued eloquently that clinically speaking, the “average man” simply does not exist (1). Indeed, he said the very hallmark of being human is the high degree of individual variation our species exhibits. The variability that Dr. Williams referred to went beyond the obvious differences between individuals: sex, weight and age or even the presence or absence of a single genetic change that can alter drug response. Dr. Williams wrote: "If normal facial features varied as much as gastric juices do, some of our noses would be about the size of navy beans while others would be the size of twenty-pound watermelons." (2)
And today, more than 50 years later, the medical community lacks the tools to embrace the “everybody is unique” paradigm. The current state of the industry prompts three questions. Where did our current medical “one size fits all” approach come from? How effective is it if we develop medicines for Mr. or Ms. Average? And if it is not, how could we move on to a more effective approach? The answer to the first question revolves around the tendency to aggregate populations of people into a single number that may not be representative of any individual. If other industries used this approach, they would go out of business fairly rapidly. Imagine if the clothing industry only offered one size fits all (Figure 1).
Figure 1. Imagine if the clothing industry acted like healthcare.
A high degree of individual variation poses a serious problem for the healthcare industry (3). For example, discovering and developing custom-made pharmaceuticals targeted to a single individual’s biochemistry and that person’s particular variation of a disease is not as simple as producing a well-fitted pair of pants. One would first have to measure and decipher the relevant biochemistry underlying the disease variation of that individual and then (if a well-fitted treatment is by coincidence not available) discover, develop and monitor a custom drug in years of clinical trials. How bad is it really if we develop them instead for Mr. or Ms. Average - as many medical companies currently do? How many people are average? And for those who are not average, will those medicines work?
Let’s look at the population performance of the top selling drugs in migraine, a classic example of a chronic disease with unpredictable but often devastating episodic attacks. What percentage of the population is effectively treated if you give them the drug in question? What is astounding is that the best of the acute treatments (ibuprofen) and preventive treatments (topiramate and TEV-48125) are effective in only one in three patients and the worst (aspirin and AMG 303) were therapeutically effective in only one in five and one in six (respectively) (Figure 2). The fact that any given drug is therapeutically effective in only a minority of patients flags a number of issues. First, how much faith can we place in any “one size fits all” therapeutic approach? Since the biochemical basis for this failure is poorly understood, shouldn’t we try to understand the mechanisms of individual disease variation that limit the “one-size-fits-all” approach? Finally, and most importantly, how can we develop better therapeutic approaches that are built upon recognition of individual variability?
Figure 2. Examples of top selling drugs in migraine and the portion of the population in which they are effective.
Migraine, one of the leading causes of disability worldwide is a model condition if we want to study variation between individuals and the therapeutic implications of these differences (4). The hallmark of migraine is episodic, debilitating attacks that are easily diagnosed and monitored. In addition, many people with migraine have several attacks per month, so profiling risk factors both positive and negative (e.g. therapies, protectors, potential triggers etc.) associated with making an individual patient better or worse can be done relatively rapidly. Many migraine population studies have already been conducted, generating aggregate data about the average migraine patient, which we can use to benchmark against variation in the individual patient.
A first step toward understanding the level and basis of individual variation in a chronic disease such as migraine versus an “average profile” was recently accomplished in a study done in collaboration with the Department of Neurology, Medical University of Vienna and the Biostatistics Unit, Faculty of Medicine, Universitat Autonoma de Barcelona and a healthcare startup called Curelator Inc. The study examined risk profiles of more than 300 individual patients (5). A key aspect of this research was that it examined a previously analyzed database from a landmark study called the PAMINA study (6), where individuals recorded their daily exposure (or lack thereof) to a list of commonly believed “risk factors” associated with migraine: weather, dietary, emotional, physical etc. The original PAMINA study yielded the “average trigger profile” of the average migraineur. But the reanalysis of each individual patients revealed two unexpected findings…
First, virtually all of the patients in the study where a trigger profile was generated showed unique profiles. How many shared an average profile of four potential triggers, the most common being menstruation, neck pain, tiredness and bright lights? Not even one patient. Second, the data revealed that trigger factors in some people were protective factors in others and vice-versa (7). The variation between individual migraine risk factor profiles certainly alerts us that everybody is different on a risk susceptibility level, but will we ever be able to understand the mechanisms driving these differences and relate them to individual therapeutic response?
It seems that an important next step would be to acknowledge the need to understand both the degree of and basis for individual variation in chronic disease. If the average approach is limiting, or possibly even causing harm in some individuals, then optimizing individual therapeutic pathways and outcomes may be the most effective way forward for patients with chronic disease not adequately addressed by the aggregate approach in modern medicine.
This blog is a shortened version of an existing article written by Alec Mian and Anne MacGregor. To view the full article, please visit: https://n1-headache.com/patients/migraine-articles/will-the-real-mr-average-please-stand-up/
About the Authors
Anne MacGregor, MD
Specialist in Headache and Women’s Health, Barts Health NHS Trust, London, UK
Alec Mian, PhD
Chief Executive Officer for Curelator Headache (https://n1-headache.com)
References
Williams RJ (1956) Biochemical Individuality. New York: John Wiley & Sons
Williams RJ (1967) You Are Extraordinary. New York: Random House
Schork NJ (2015) Personalized medicine: Time for one-person trials Nature 520(7549), pp609-11
Vos et al (2012) Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990-2010: a systematic analysis for the Global Burden of Disease Study 2010 Lancet 380 pp2163–96
Peris et al (2016) Towards improved migraine management: Determining potential trigger factors in individual patients Cephalagia DOI: 10.1177/0333102416649761
Wöber et al (2007) Prospective analysis of factors related to migraine attacks: the PAMINA study Cephalalgia 27(4) pp304-14.
Donoghue et al (2021) Identification of individual “protective factors” associated with reduced risk of migraine attacks.