New Fields of Research Defined by Open Science Visionaries

The purpose of an open-science non-profit research startup like DIYgenomics is research innovation.

The value is in being able to propose a unique and visionary research agenda of questions that are forward-looking and not the focus or interest of the institutional research industry.

Research innovation falls into two tiers:

First is preventive medicine questions, ‘medicine that matters to me’ (e.g.; small groups or individuals), and non-pathologies.

More importantly, the second tier is defining completely new fields of research such as athletic performance genomics, social intelligence genomics, cognitive performance genomics, and DIYneuroscience, and making progress on widespread philosophical and societal problems such as the destigmatization of physical and mental health issues, and the reduction of discrimination as a broad social problem.

DIY open-science, crowdsourced health social networks, and community biohacking labs are the early-stage startup/venture capital arm of the expanding preventive medicine ecosystem of health services, and are able to surface projects of interest that can then be pursued at the institutional level as relevant.

Crowd Models Become Pervasive Across Society

Crowd-based models are becoming so pervasive that almost no major segment of modern life is left untouched by them. The concept of digital crowd models refers to the coordination of large numbers of individuals (the crowd) through an open call on the Internet in the conduct of some sort of activity.

Not only are crowd models an efficient at-scale alternative to former methods that the Internet now affords, but at another level, crowd models are also a node of progress for humanity, both individually and en masse. An inherent property of crowd models is greater autonomy, decision-making, and action-taking by the individual. This means greater individual agency whilst simultaneously enabling group collaboration projects at previously unimaginable scales, for example, possibly ultimately coordinating and employing the cognitive power of millions of human agents.  

Crowd Models by Sector

• In economics, there are crowdsourced labor marketplaces where simple tasks and professional services requests can be posted and fulfilled, crowdfunding websites for financing projects, and group purchasing mechanisms. 
• In politics, crowd models mean the use of big data and social media to organize opinion and action, conduct direct marketing, and affect change. 
• In the social venue, blogs, social networks, and online dating sites are examples of crowd models. 
• In entertainment, there are massively multiplayer online games and virtual worlds. In education, vast eLearning networks are populating the landscape. 
• In health, there are health social networks, digital health collaboration and experimentation communities, crowdscience competitions, and new movements such as the quantified self. 
• In the legal venue, digital public goods have arisen through crowd contributions such as the Wikipedia, online health databanks, and other data commons resources.

Memory and empathy studies launch on crowdsourced health platform!

Two new health studies organized by DIYgenomics and collaborators have recently launched on the crowdsourcing platform Genomera. One is a memory study: Dopamine Genes and Rapid Reality Adaptation in Thinking and the other is an empathy study: Social Intelligence Genomics & Empathy-Building.

The Genomera platform boasts over 700 community members who are interested in participating in studies. While several of the approximately 30 listed studies investigate genetics as a related component of health, it is not necessary to have data from 23andMe or other consumer genomics services to join the health collaboration community and participate in studies. There are already 40 participants in the memory study and almost 20 in the empathy study.

The objective of the memory study is to see if genetic variants related to dopamine processing in the brain impact the processing of memories. The study is being conducted in conjunction with leading researchers at the Center of Cognitive Neurorehabilitation in Geneva Switzerland. The participation requirements are to complete an online Memory Filtering Task which takes approximately 40 minutes and a short Demographic Survey.

The objective of the empathy study is to confirm and extend research linking genetic profile and social intelligence, specifically whether individuals with certain genetic profiles may have a greater natural capacity for optimism and empathy, extraversion, and altruism. The participation requirement is to complete two short standardized online surveys for empathy quotient and other personality attributes. In addition, there is an optionally available Personal Virtual Coach app for empathy-building, a sort of SIRI 2.0 for mental performance optimization.

Key challenge of our era: health and preventive medicine

Delivering health care and keeping populations healthy is a key problem of the current era. Health expenditures currently comprise 17% of U.S. GDP and are growing; simultaneously health in the U.S. is in decline, with a new CDC report estimating that by 2030, 42% of American adults will be obese, compared to 34% today and 11% will be severely obese, compared to 6% today.

The Realization of Preventive Medicine
A key part of addressing health challenges is the realization of preventive medicine. Preventive medicine and health maintenance consist of identifying and managing conditions in the 80% of their life cycle before they become clinical, ideally avoiding clinical onset. Workable models for the execution of preventive medicine need to be developed. By definition, a broader ecosystem than the traditional medical establishment will be participating in all steps of the value chain ranging from health research to clinical delivery. More flexible regulatory models are needed that preserve the core ethical principles of the traditional models, but are geared towards the internet era and an expanded notion of health and health maintenance with a larger ecosystem of service providers and participants. The payments ecosystem needs to adapt in parallel, allowing for a wider range of payment mechanisms including out-of-pocket payments, H.S.A. dollars, patient advocacy group funding, and traditional (and increasingly diminishing) insurance payments.

Job of the near-future: health advisor

The health advisor is analogous to the financial advisor or mortgage broker that arose last decade when it became possible to trade stocks and get mortgage quotes on the internet. This advisor is familiar with the whole ecosystem of services and service providers in a sector whether finances, home buying and selling, or in this case, personalized health management.

The health advisor designs comprehensive wellness plans that integrate multiple health data streams such as family history, personal health history, genomics, and eventually microbiomic, proteomic and metabolomic profiles. The health advisor would recommend what type of genomic sequencing to sign up for (for example, 23andMe genotyping or Illumina whole human sequencing) and interpret the results and suggest action items. The health advisor would recommend and administer self-tracking programs and gadgets for diet, nutrition, medication and supplementation, exercise, and sleep management. The health advisor would recommend clinical trials or crowdsourced health studies that might be relevant for individuals to join. The health advisor could be compensated with pre-tax HSA (health savings account) dollars or other tax-advantaged funds.

This is a job category of the near future, as health advisor certification programs and wellness coaches are already arising.

Scaling citizen health science and ethical review

Many things are needed to scale citizen science from small cohorts on the order of a few individuals to medium and large-sized cohorts. Building trust in online health communities, motivating sustained engagement from study participants, and lower-cost easier-access blood tests are a few things that are needed.

Legal and ethical issues are also a challenge. Independent ethical review is appropriate but the current IRB (Institutional Review Board) requirement for funding and journal publication is a barrier to crowdsourced study growth. In 23andMe's early studies, there was a definitional debate as to whether their research constituted 'human subjects research,' and whether there was a difference in interacting with subjects in-person versus over the internet.

The U.S. HHS (Health and Human Services) definition of 'humans subjects research' is research that "obtains (1) data through intervention or interaction with the individual, or (2) identifiable private information." (45 CFR 46.102(f)) The strict reading is that any research obtained by 'interacting' with a human subject (e.g.; likely all personalized health collaboration community research) would require an IRB for the funding needed to do it at scale.

Acknowledgement: Thank you to Thomas Pickard for providing background research

Longevity genomics paper retracted

On July 22, 2011, a high-profile longevity genomics paper published in Science in July 2010 was retracted. The paper, ‘Genetic Signatures of Exceptional Longevity in Humans,’ was the work of Thomas Perls and Paola Sebastiani (Boston University). The initial study had been revised per editorial concerns that arose last year, but has now been retracted possibly due to issues related to the replicatability the findings.

The revised study results were presented by the team at the American Aging Association meeting in June 2011. These data featured nine single SNP associations (versus two previously), and linked 281 SNPs to signatures for exceptional longevity (versus 180 SNPs previously). The overall conclusion remained unchanged - that

centenarians, while having the same disease mutational profiles as non-centenarians, have other specific aspects to their genetic profiles which indicate a signature for exceptional longevity

Towards an epistemology of citizen science

Now that citizen science in the health domain is becoming more established, it is relevant to scale it up to tackle larger projects. Several things can be done such as the definition and introduction of liability and oversight models that would be the analogue of the traditional IRB (institutional review board), and the professionalization of participant roles in the study ecosystem such as that of the study manager.

A more subtle issue is to develop an epistemology of citizen science. This would provide a structure and context for exploring the knowledge that is derived from citizen science. One question is whether new kinds of knowledge are being formed through group collaborations such as wikipedia and health social networks. Another question is characterizing the differences (if any) in the types of knowledge generated by traditional medicine, self-experimentation, and health collaboration communities.

App fever at Mobile Health 2011

This year’s attendance was double last year’s at the Mobile Health conference, held at Stanford University May 4-5, 2011. The main theme last year was monetizing mobile health apps, without any real ideas of how to do so. This year the main theme was app fever – everyone either having or thinking that they need to have an app. No one seemed to be immune - large and small health service providers, physician groups, insurers, and entrepreneurs alike are scrambling to launch apps.

Rather than having each organization struggle through multi-platform app development,

what is needed is the GeoCities of mobile apps,

a plug and play platform where app creators can select different widgets for app customization. The most obvious mobile health app widgets would be for appointment scheduling, prescription management, lab test results, physician interaction, and EMRs.

Since app fever reaches far beyond the health sector, GeoCities/Dreamweaver-level platforms, much more accessible to the layperson than Google App Inventor and unified mobile code base tools, could cause even greater activity in the already booming mobile sector.

Automated nourishment

An interesting question arose from discussions at the recent IFTF annual forecast presentation - Would people be more or less healthy in a possible future era of 3-D food-printing on-demand?

Both sides of the case can be seen. The immediate conclusion might be that if anyone could print any food item on-demand any time, people would over-consume and be less healthy.

However, one of the biggest mistakes that can occur when considering a potential future advance is thinking of it in isolation and not bringing forward all other aspects of technology and society to this point too. In an era with on-demand 3-D food printing, other changes are also likely to have occurred. The first and most obvious is that perhaps food content or accompanying supplements, drugs, and nutraceuticals have changed to mean that food that tastes good is not necessarily unhealthy, even when consumed in large quantities. Non-fat non-sugar substitutes may have become seamless matches in the quality of taste but not in caloric consumption. Today’s unhealthy foods could go the way of cigarettes. Automated calorie consumption data collection might finally be possible.

A second argument for why people would be more rather than less healthy in an era of on-demand 3-D food printing is the massively granular physical tracking and biofeedback tools that could exist for each person. Smarthouse and smartclothing data collection through scanning and air, toilet, and unnoticeable blood stick diagnostics could be inputs to a continuously updating personal digital health model (e.g.; the future analog to Entelos's virtual patient or Archimedes's virtual twin). A personal digital health model could be used to assess exactly which real-time nutritional adjustments are needed by an individual. An automated menu plan from the kitchen printer may be preferable for creating meals based on an individual’s known preferences and reactions together with real-time needs. The portable personal digital health model could be permissioned into restaurant settings to similarly allow for customized meal synthesis.

A third argument comes from considering the potential trajectories of social networking and behavior change research. Already peer social networks have a strong influence on individual behavior. One’s whole peer network or interest group could be encouraging healthy behavior via team-based support and/or competition. The advent and widespread adoption of self-tracking and social interaction tools could bring about a new sensibility and personal responsibility for health self-management. Optional financial incentives from insurance companies could further facilitate behavior change.

Conclusion
In any possible future, there could be different technologies and social behavioral norms influencing the process of human nourishment. Food could become healthier over time and unobtrusive self-tracking tools and financial incentives could shift people to automated menu plans. Healthier behavior could be triggered just by making it easy.

Health 2.0 business models

Health 2.0 is about re-envisioning every aspect of health and health care. New business models are starting to develop to support this innovation ecology. First, accompanying the new paradigm of community research (peer cohort studies à la Patients Like Me (lithium) and DIYgenomics (MTHFR mutation/Vitamin B-12 deficiency), could be social venture finance, corporate sponsorship from supplement companies and other remedy vendors, crowdsourced finance (i.e.; Kickstarter), and philanthropist contributions. Second, the traditional venture capital model is already being applied to health 2.o startup companies, including through organizations such as the Health 2.0 Accelerator. Third, whole new industries may sprout from the nascent efforts of health advisors and wellness coaches. The health advisor is the analog to the financial advisor or mortgage broker, able to integrate a client's health data streams, needs, and interests with available offerings, across a spectrum of economic models: insurance reimbursable, HSA dollars, and direct out-of-pocket spending.

Health Literacy Toolkit

With one key life sciences focus shifting to health as opposed to healthcare (as HealthCamp founder Mark Scrimshire exhorts) and to preventive, predictive health management as opposed to therapy and treatment, there should be the concept of a health literacy toolkit that would be a component of standardized knowledge, such as how to write, drive or get a job.

Definition of health literacy
Surprising but emblematic of the traditional health mentality (e.g.; treat illness) is the prevailing definition of health literacy…”a patient’s ability to acquire and understand information about a condition and options once diagnosed…” Moving into the preventive era, the definition of health literacy needs to shift from being backward-looking to forward-looking. Having health knowledge ahead of time could inform behaviors to prevent, slow or lessen the development of disease. Health literacy should be a general set of knowledge for everyone to know, not related to a condition once a patient has it.

Gap between health literacy and demand for health information
A U.S. Department of Health and Human Services (HHS) study finds that only 12% of adults have proficient health literacy (p. 26); that nearly 9 out of 10 adults may lack the skills needed to manage their health and prevent disease.

The biggest reason for low health literacy could be a lack of appropriately accessible and presented health information.

A Pew Internet Study “The Social Life of Health Information” in June 2009 finds that 61% of U.S. adults are looking for health information online. The gap between health literacy and the demand for health information suggests that there is a substantial opportunity for a range of health information services and management tools, many of which could be fee-based such as the LIVESTRONG nutrition and exercise management program.

Health literacy toolkit
What should be the components of a standard health literacy toolkit? Many professionals (e.g.; physicians, academicians, etc.) believe that even HDL/LDL cholesterol information is too complicated for the lay public, but this just cannot be correct. When simple numeric information is presented clearly, people of any background and capability are often quite able to understand it and take action. For example, when utility bills started to provide straightforward quantitative data regarding power consumption, including day/night usage and costs, many people shifted their behavior in a positive informed way.

Figure 1: Ongoing Total Cholesterol readings for one individual

Figure 1 illustrates an example individual’s ongoing total cholesterol readings presented in a clear and informative way. Anyone inspecting the chart can easily identify the overall trend, down, which is good, wonder about the range of numeric measurements (157-185) vs. the average and how this translates into good or bad health tiers (e.g.; under 200 is generally good, but a rising trend that is still under 200 could be an indication of arising health issues for that individual), and inquisitively wonder about the peaks. The next level of information would be HDL and LDL readings, small lipids as is now de rigueur and triglycerides, but even this simple plot of total cholesterol measures is understandable, useful and potentially actionable. It is also the perfect level of information for individuals who are interested in being responsible for self-managing their health but from an efficient, easily-actionable level that does not require deep engagement of time or knowledge acquistion.

Some of the most obvious aspects to include in a health literacy toolkit would be nutritional information and its interpretation, caloric consumption and expenditure and ongoing quantitative measures of health from blood analysis and other tests (e.g.; blood pressure, glucose, cholesterol, BMI, weight, VO2 max, etc.). The data can be summarized (with detail available) and directly linked to actionable explanatory information (e.g.; measures may go up or down if they were not measured at the same time or situation, for example if a meal had been eaten before some but not all of the measurements). Other components of a standard health literacy toolkit could include where and how to obtain information and tools for self-tracking, how to integrate multiple data sources into a unified view, and how and what to expect when interacting with the medical community. Genomics is already part of the health literacy toolkit for early adopters and could become a standard toolkit component for everyone within five years, already helpful Genetics 101 sites are emerging.

Automated health monitoring tools
Health-self management in large quadrants of the population could accelerate with the advent of automated health monitoring tools that would capture frequent datapoints and aggregate the information into easily viewable web-based charts. Many devices such as blood pressure monitors, heart monitors and scales are now battery-intensive Bluetooth-enabled which is a nice intermediate step but what is really needed is for all of these monitoring devices to be directly on home WiFi networks. Where possible, having the monitoring applications directly on the smartphone is another obvious step rather than having separate devices. There are some WiFi-enabled devices, for example the FitBit calorimeter, which has been delayed in launching, and glucose monitors such as the GlucoMON, however its $75/month subscription fee appears exorbitant.

Status of cancer detection

The Canary Foundation’s annual symposium held May 4-6, 2009 indicated progress in two dimensions of a systemic approach to cancer detection: blood biomarker identification and molecular imaging analysis.

Systems approach to cancer detection
A systems approach is required for effective cancer detection as assays show that many proteins, miRNAs, gene variants and other biomarkers found in cancer are also present in healthy organisms. The two current methods are one, looking comprehensively at the full suite of genes and proteins, checking for over-expression, under-expression, mutation, quantity, proximity and other factors in a tapestry of biological interactions and two, seeking to identify biomarkers that are truly unique to cancer, for example resulting from post-translational modifications like glycosylation and phosphorylation. Establishing mathematical simulation models has also been an important step in identifying baseline normal variation, treatment windows and cost trade-offs.

Blood biomarker analysis
There are several innovative approaches to blood biomarker analysis including blood-based protein-assays (identifying and quantifying novel proteins related to cancer), methylation analysis (looking at abnormal methylation as a cancer biomarker) and miRNA biomarker studies (distinguishing miRNAs which originated from tumors). Creating antibodies and assays for better discovery is also advancing particularly protein detection approaches using zero, one and two antibodies.

Molecular Imaging
The techniques for imaging have been improving to molecular level resolution. It is becoming possible to dial-in to any set of 3D coordinates in the body with high-frequency, increase the temperature and destroy only that area of tissue. Three molecular imaging technologies appear especially promising: targeted microbubble ultrasound imaging (where targeted proteins attach to cancer cells and microbubbles are attached to the proteins which make the cancerous cells visible via ultrasound; a 10-20x cheaper technology than the CT scan alternative), Raman spectroscopy (adding light-based imaging to endoscopes) and a new imaging strategy using photoacoustics (light in/sound out).

Tools: Cancer Genome Atlas and nextgen sequencing
As with other high-growth science and technology areas, tools and research findings evolve in lockstep. The next generation of tools for cancer detection includes a vast cataloging of baseline and abnormal data and a more detailed level of assaying and sequencing. In the U.S., the NIH’s Cancer Genome Atlas is completing a pilot phase and being expanded to include 50 tumor types (vs. the pilot phase’s three types: glioblastoma, ovarian and lung) and abnormalities in 25,000 tumors. The project performs a whole genomic scan of cancer tumors, analyzing mutations, methylation, coordination, pathways, copy number, miRNAs and expression. A key tool is sequencing technology itself which is starting to broaden out from basic genomic scanning to targeted sequencing, whole RNA sequencing, methylome sequencing, histone modification sequencing, DNA methylation by arrays and RNA analysis by arrays. The next level would be including another layer of detail, areas such as acetylation and phosphorylation.

Future paradigm shifts: prevention, omnisequencing, nanoscience and synthetic biology
Only small percentages of annual cancer research budgets are spent on detection vs. treatment, but it is possible that the focus will be further upstreamed to prevention and health maintenance as more is understood about the disease mechanisms of cancer. Life sciences technology is not just moving at Moore’s Law paces but there are probably also some paradigm shifts coming.

The three most suggestive areas for coming life science discontinuities are genomic sequencing, nanoscience and synthetic biology.

Genomic sequencing contemplates the routine scanning of each individual and tumor at multiple levels: genomic, proteomic, methylomic, etc. Nanoscience is the ability to design, construct and render mobile a large variety of molecular [biological] devices. Synthetic biology is designing new or modifying existing biological pathways in order to produce systems with superior or different properties, exercised by both traditional practitioners (recent conferences: Advances in Synthetic Biology, Synthetic Biology 4.0) and diybio’ers.