Monday, January 2, 2023

Quantified Self: From Sousveillance to Personal Science and Phenotyping

The quantified-self movement which involves using technology to track various aspects of one's daily life and behaviors, could be traced back to the sousveillance-like monitoring described in 1970. One of the first platforms for these activities - Nike+ website publicly launched in 2006 - was helping runners to track and share their workouts. 

The term "quantified self" was coined in 2007 by Wired magazine editors Gary Wolf and Kevin Kelly who co-founded the Quantified Self Institute and "Quantified Self Meetups." The movement experienced a period of rapid growth in popularity in the 2010s. Forbes has even called 2013 "The Year of the Quantified Self". 

As the technology for self-tracking has become more advanced and widespread, it has attracted the attention of commercial hardware developers. Fitbit founded in 2007 as Healthy Metrics Research, released their first tracker in 2009. In the 2010s, a number of major tech companies, including Apple, Google, and Samsung, began to develop and market wearable devices and self-tracking apps.

Quantified Self movement has not become a mainstream trend due to a combination of cost, technical barriers, and privacy concerns. Many people resented self-tracking being pushed by their employers, health and life insurers in order to monitor them. And despite many attempts to develop analysis tools, most people are still lacking the skills to process their data in order to make better decisions in everyday life.

"Personal science" (the use of scientific methods and principles to analyze personal lifelogging) and N-of-1 studies (when individual is studied in isolation, rather than as part of a larger group in a clinical study) are related to the quantified-self movement in that they both involve the use of technology and data to track and understand one's own health and behavior. These approaches, however, are not yet widely used or understood by the general public. 

The use of self-tracking data has the potential to inform the study of various medical conditions through the process of phenotyping, as several papers have demonstrated (eg, for vaccine-triggered anorexia and endometriosis). However, the understanding of how to effectively use this type of data for this purpose is still in the early stages, and it has not yet been widely adopted by traditional medical science. In contrast to what was expected 20 years ago, phenotyping has taken a back seat in human genetics research. It was thought that having a precise or well-measured phenotype was far less relevant than having a huge sample. However, now that the field of genetics has a working strategy for gene discovery, and AI is getting more sophisticated, the importance of phenotype is re-emerging, and this will likely lead to a renewed interest in the quantified self.


McClusky M. The Nike experiment: how the shoe giant unleashed the power of personal metrics. Wired. 2009 Jun 22;17(07).

Gabashvili IS. Why Red Beans and Rice Are Good ... But Not with Coffee, Forbes 2012, April 30. DOI: 10.6084/m9.figshare.13600517

Osozawa S. Case report: anorexia as a new type of adverse reaction caused by the COVID-19 vaccination: a case report applying detailed personal care records. F1000Res 2022 Jan 4;11:4

Urteaga I, McKillop M, Elhadad N. Learning endometriosis phenotypes from patient-generated data. NPJ digital medicine. 2020 Jun 24;3(1):1-4.

Dick DM. The Promise and Peril of Genetics. Curr Dir Psychol Sci. 2022 Dec;31(6):480-485. doi: 10.1177/09637214221112041. Epub 2022 Sep 16. PMID: 36591341; PMCID: PMC9802013.


Special thanks to OpenAI's Assistant for their help with illustrating and writing this article.

Friday, November 4, 2022

COVID-19: vaccines and infections

Personalized, precise and predictive vaccinology's holy grail is to anticipate immune response for every individual, depending on their genetic background and all other factors that may impact vaccine immunogenicity, efficacy, and safety.

The high expense of comprehensive genomic and immune-profiling tests, however, prohibits their routine use and this disproportionally affects underserved populations.

A new paper reports preliminary results of an ongoing study of COVID-19 vaccination in geographic neighborhoods and online health support groups. Due to innovative recruitment and monitoring strategies, the study has the largest representation of active "oldest old" - individuals aged 80 or older - than all other trials with diverse age groups. 

Despite widespread belief of a biphasic pattern for the frequency of systemic adverse events post-vaccination (VAEs), the paper reports statistically significant differences in the incidence of VAEs for both younger and 80+ populations when compared to those in the 60-69 and 70-79 age brackets. The subtypes of adverse events in younger and older populations are different. This short paper groups post-vaccination events in three types: "No or minimal VAEs", and short- or long-term reactions that significantly impacted activities of daily living.    

The paper suggests genetic origin for some adverse reactions. Scientists have only just begun to look into genetics of less common VAEs. HLA-A∗03:01 (contributing to low risk of severe COVID-19) was recently found to be associated with increased risk of stronger side effects (including fever and chills) from Pfizer-BioNTech COVID-19 vaccination. In another recent study, HLA-DQB1*06 alleles were found to protect from breakthrough infection during the ancestral SARS-CoV-2 virus and subsequent Alpha-variant waves compared with non-carriers. Hopefully, more studies will follow. 


Gabashvili IS. The Incidence and Effect of Adverse Events Due to COVID-19 Vaccines on Breakthrough Infections: Decentralized Observational Study With Underrepresented Groups. JMIR Form Res. 2022 Nov 4;6(11):e41914. doi: 10.2196/41914. PMID: 36309347.

Current Impact score of the journal is: 2.38 (Resurchify)

JMIR Formative Research has been accepted for the Web of Science: Emerging Sources Citation Index. The journal will receive a Journal Impact Factor in 2023. 

Saturday, September 17, 2022

The Rapid Expansion of DTC Healthcare

Preventive care is recognized as the most effective strategy for health care cost reductionScreening for early signs of heart disease, cancer, maintenance of diabetes and allergies and prevention of infectious diseases can be done without a supervising physician. Direct-to-consumer (DTC) laboratory testing allows individuals to order tests directly from a laboratory without going through their healthcare provider, and often at lower costThe number of companies providing direct-to-consumer diagnostic testing is rapidly growing, along with the range of health information provided by these tests. Ancestry (genealogy) testing is an example. And so are new devices for cardiac monitoring

Experts anticipate a near-term explosion in the DTC marketplace. DTC healthcare already was a US$700 billion industry in 2020, including over-the-counter drugs. The Mark Cuban Cost Plus Drug Company, PBC (MCCPDC) is nearing one million customers. An analysis of 2011-1019 records from Rock Health Digital Database, showed that 252 (21%) of 1214 digital health companies pursued a direct-to-consumer strategy. The pandemic has accelerated this growth. According to research by Deloitte, the number of people using virtual healthcare rose from 15% to 19% from 2019 to early 2020, then jumped to 28% in April 2020. On average, 80% were likely to have another virtual visit, even post COVID-19 and said they will use this type of care again. Latest data showed that consumers’ appetite for virtual health and digital health tools continued to steadily increased, although there was significant variation in physician adoption. 

Human touch remains central to care delivery. In the 2022 Deloitte Survey of US Health Care Consumers, 70% of respondents who had a virtual visit in 2022 (vs. 67% in 2020) thought that the quality of virtual care was as good as in person, but only 73% (vs. 82% in 2020) thought they were able to connect with the clinician the same way they would in-person. Integration of data from patients' wearables and their self-reported outcomes into health records also experienced a setback

The global market for Direct-to-Consumer (DTC) testing was predicted to grow from $1.4 billion in 2020 to $2.6 billion by 2025. There were cautionary cases of uBiome and Theranos, there are quackery labs, but as the industry matures and moves toward utilization of clear clinical metrics, and as the capabilities of technology advance, DTC testing will me more and more impactful. There are DTC companies that offer the tests and biometric screenings that a physician would typically order as part of a routine annual physical, such as a complete blood count, comprehensive metabolic panel, urinalysis, and cardiovascular and diabetes risk assessment. Ultalabs, JasonHealth, discounted labs, drsays and privatemdlabs all allow to self-order laboratory tests and Quest and Labcorps locations. 
No more uncomfortable questions for a blood test prescription. No doctor visit needed to gettest results - they will be emailed instead. Consumers pay up front and know exactly what they are paying for. Unfortunately, the same cannot be said for many other healthcare services.

Genetic counseling for patients who are pursuing genetic testing in the absence of a medical indication, referred to as elective genomic testing (EGT), is becoming relatively common. More people are using technology to monitor their health, measure fitness, and order prescription refills. Before COVID-19, there was a slight decline in people who were willing to share their health data—but during the pandemic, new data showed that people are more comfortable sharing data during a crisis


Cohen AB, Mathews SC, Dorsey ER, Bates DW, Safavi K. Direct-to-consumer digital health. The Lancet Digital Health. 2020 Apr 1;2(4):e163-5.

Stoffel M, Greene DN, Beal SG, Foley P, Killeen AA, Shafi H, Terrazas E. Direct-to-Consumer Testing for Routine Purposes. Clinical Chemistry. 2022 Sep;68(9):1121-7.

2022 Global health care sector outlook | Deloitte


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