Thank you for registering for updates about the Personal Genome Project (PGP). Since our last newsletter in March, we have new developments to report, including the enrollment of the PGP-1K, new online tools, and several exciting collaborations.

Welcome to the team, PGP-1K!

We are excited to announce that the next 1,000 participants in the Personal Genome Project (PGP) will be enrolled in the coming week. We will notify selected individuals who have already completed the pre-enrollment process about their enrollment via email no later than October 15, 2010.

Once we complete the enrollment of the PGP-1K, we will immediately begin enrollment of the 10,000 participant cohort ("PGP-10K"). If you or someone you know would like to apply for enrollment in the PGP, sign-up now online.

Family Foundation Sponsors PGP-1K Genome, Act Now to Participate

Thanks to work we are doing with the Alan & Priscilla Oppenheimer Foundation, the PGP will select one individual from the PGP-1K cohort for whole-genome sequencing over the next week and start that sequencing right away. This collaboration gives us an exciting opportunity to evaluate the new trait collection tools available to PGP participants, including the ability to link Google Health accounts with PGP public profiles (more details on that below).

All participants in the PGP-1K cohort are eligible to be chosen for this first PGP-1K sequencing. To be considered for selection, enrolled participants should complete the new online modules (linking Google Health, Family Relationships, Geographic Information) no later than midnight Pacific time on Monday October 18th, 2010. On October 19th, the PGP will review the public profiles created by PGP-1K participants and select one individual to submit a saliva sample for whole-genome analysis. In the early part of 2011, once the genome sequencing is finished, we will return the genome sequence to the participant along with a "Preliminary Research Report" (PRR), as described in our consent document, and request the participant to voluntarily publish his/her genome sequence to the PGP public repository.

The sponsorship of a PGP genome sequence by the Alan & Priscilla Oppenheimer Foundation is an example of how novel collaborations will allow the PGP to expand our efforts to create a public resource of integrated genome-phenome datasets. We are actively pursuing relationships with financial sponsors, research collaborators, sequencing providers and disease foundations. If your organization is interested in sponsoring subsets of the PGP cohort (e.g., genome sequencing of participants with specific traits), please contact us.

A Focus on Phenomes

The structure of the PGP research study has evolved. While we initially hoped to conduct genomic sequencing and phenotypic data collection in parallel for each participant, we have learned from patient groups, disease foundations and research collaborators that, in many instances, the phenotype determines which genomes should be sequenced. In the coming months, we will be announcing several new collaborations where phenotyping is used to help identify PGP participants for whole genome sequencing.

We are pleased to announce a new collaboration with Dr. Peter K. Gregersen (Head, Center for Genomics and Human Genetics at the Feinstein Institute for Medical Research) to study the genetics of absolute pitch. The first step is to screen enrolled PGP participants for the trait of absolute pitch and then select a subset for additional screening and, ultimately, whole-genome analysis. Screening the PGP population for the absolute pitch trait is expected to begin before the end of the year.

As a result of these developments, and as reflected in the recently revised informed consent document and study protocol, we have revamped the PGP to enable participants to enroll and to begin providing phenotypic data (medical history, environmental and other trait data, etc.) prior to sequencing. Overall, we expect this change to increase our ability to expand enrollment in the PGP more quickly than before and, most importantly, to enhance the visibility of those participants willing to share their data to advance our understanding of how our genomes combine with the environment to form human traits. The increased visibility of the PGP cohort will help us identify organizations willing to sponsor specific groups of participants or aspects of the PGP.

Google Health

A major component of the PGP’s new focus on phenotypes is the completion this month of an integration with Google Health. Enrolled participants who manage their personal health information via Google Health may now link their account with their PGP public profile, so that their PGP profile is updated automatically. The types of information that participants can manage through Google Health include:

1. Personal Information (e.g., age, sex, etc.)
2. Wellness (e.g., height, weight, etc.)
3. Problems (e.g., medical conditions or symptoms)
4. Medications (e.g., prescriptions, supplements, etc.)
5. Allergies
6. Test results (e.g., LDL cholesterol, etc.)
7. Procedures (e.g., appendectomy, chest X-ray, etc.)
8. Immunizations

Google Health also provides a variety of third party services that enable users to import data from major pharmacies, diagnostic testing labs, and tracking devices (such as wifi-enabled scales).

Enrolled participants who wish to link their Google Health account with their PGP public profile should log-in to their PGP account and follow the simple instructions. Also note that we have a new URL for enrolled participants to manage their PGP profiles:

https://my.personalgenomes.org

Exploring the Human Microbiome

Did you know that the human body contains 10 times as many microbial cells as human cells, and hundreds of times more bacterial genes than human genes? We are delighted to announce a new collaboration with Rob Knight and Noah Fierer (Howard Hughes Medical Institute and University of Colorado) that will enable us to explore the microbial diversity of various habitats of the human body with volunteers from the PGP-1K cohort. Over the next several months, we will begin shipping sampling kits to volunteers. The sampling procedure is non-invasive and can be done with q-tips. The short-term goal is to see which microbes are in each of 5 key body sites, and to test whether there are any associations between specific microbes and diseases (especially chronic diseases such as diabetes, obesity, inflammatory bowel disease, and even depression – new evidence from mice suggests that the microbes can sometimes control host behavior).

Longer term, as more of the PGP-1K cohort have their genomes sequenced, we will look at genome-microbiome interactions. We also hope to explore how microbes vary over time within an individual and change in response to diet by collecting a series of samples over a period. Characterization of additional body sites and viral and metabolic profiling will help us understand the links among bacteria and viruses and to understand how different microbes can affect the metabolism of different foods and drugs. These studies will help us understand how the genomes of our bacterial symbionts influence our health and change in response to health status, and will allow us to develop biomarkers that better predict disease states and options for personalized medicine.

Updating the PGP-10

We have new data to share! By the end of November, we will be making publicly available more genome data for the currently enrolled PGP participants, including full genomes from the initial ten participants ("PGP-10") and several recent enrollees. This will bring the tally of complete genomes in the PGP database to 14. We are continuing to develop tools to help researchers and the public genomics community explore and understand this data. Analyses of the PGP genomes will be available on our new genome analysis site, "GET-Evidence":

http://evidence.personalgenomes.org

GET-Evidence Tool for Genome Analysis

Without tools to assist you, interpreting whole genomes can be pretty tough. Each genome has millions of sites which vary—thousands of these are predicted to affect protein structures, and hundreds have some relevant published literature. A lot of reading and interpretation is required for each genome, but these efforts also have a lot of redundancy: most variants will be seen again in other genomes. In addition, it is difficult to ascertain which of these variants are most likely to have clinical implications and should be prioritized for review. To address these issues we have created "GET-Evidence".

GET-Evidence assists genome analysis by providing a Wikipedia-style location where individuals can record their interpretations of individual variants and review relevant literature. It is a forum where the community may reach consensus on the interpretation of genetic variants. In addition, GET-Evidence assists users by noting various types of evidence (e.g. allele frequency, presence in other databases) and suggests prioritization for variant reviews. We hope this tool helps make the analysis of whole genome data more efficient and productive over time.

If you’d like to help – especially if you're already reading literature just as we've described – we invite you to log in to GET-Evidence and participate! If you have any questions or suggestions, please join and send messages to our "get-editors" mailing list. As with Wikipedia, all data recorded on GET-Evidence will be freely available for others to use.