Android mobile app for 23andMe data

DIYgenomics released a personal genome Android app update on January 9, 2011 adding three new elements of functionality: the ability to upload and store 23andMe data in the app, multiple views for health risk, drug response, and athletic performance (Figure 1), and a quality ranking system for each SNP.

Figure 1: DIYgenomics Android mobile app view categories.

What is this information?
Selecting any item displays a list of variants or SNPs (places of potential genetic typos), such as for Alzheimer's disease (Figure 2). The locus, gene and variant (SNP) details are shown, along with the normal type (e.g.; no mutation) for 23andMe data (if it exists) in black, an individual's 23andMe data (if loaded) with normal alleles in green and mutations (polymorphisms) in red. Stars (from 1-5) indicate the research quality of the SNP (per the journal ranking of the study, the number of cases and controls, etc.). The colored blocks show which service providers cite the SNP (per color legend), and how many studies they cite.

Figure 2: DIYgenomics health condition Alzheimer's disease.

What does this information mean?
In Health Conditions, a mutation (polymorphism) presented in red generally indicated being at higher potential risk for developing a condition. In Drug Response, a mutation could mean that the normal dose of the drug may not work as well, that there could be side effects, or that there could be a higher change of addiction (for substances). In Athletic Performance, the favorable mutation (green), suggests greater than average athletic capability.

Citizen science genomics

A group of interested citizen scientists came together to explore how they could make their 23andMe personal genomic data actionable. A small (n=7) non-statistically significant pilot study was conducted looking at polymorphisms (e.g.; typos) in SNPs in the MTHFR gene and their connection to Vitamin B deficiency and high (undesirable) homocysteine levels. Four out of seven participants, though healthy, had high baseline homocysteine levels. For five of the study participants, a regular drugstore multivitamin worked best for reducing homocysteine levels. Overall, homocysteine levels were reduced 19%, commensurate with 23% reductions achieved in traditional clinical trials.

This is an important example for two reasons: the preventive medicine model and the crowdsourced research model.

1. This study illustrates one approach to the challenge of preventive medicine. Prospective tracking of genomic data + phenotypic data + interventions could help to establish baseline measures of wellness in large populations, shift health management responsibility to individuals, and potentially prevent or delay the clinical onset of conditions.
   
2. This study shows the value of crowdsourcing citizen scientists for research studies as they increasingly have access to their health information, may be willing to contribute their data to various studies, and have the interest and motivation to investigate conditions of personal relevance.

Paper: Citizen Science Genomics as a Model for Crowdsourced Preventive Medicine Research, December 23, 2010

Personal genome: data analysis challenge

Five themes emerged from the material presented at the 3rd annual personal genomes meeting at Cold Spring Harbor Laboratory held September 10-12, 2010.

First was the trend of family sequencing becoming more of a norm; looking at genetic disease as it is represented in trios, quartets or other family groups.

Second was the trend of increasingly common multi-level analysis, investigating traditional genotype data together with structural variation, expression data, pathways, and cell lines.

Third was the trend of greater breadth and sophistication in cancer genome analysis; the fledgling field of a few years ago now including dozens of sequenced cancer tumor genomes, the first cancer methylome, and cancer transcriptome analysis.

Fourth was the trend of the oft-heard challenge of scaling personal genome interpretation, making it automated, affordable, and actionable.

The fifth theme was the continued improvement in genome sequencing technology through new approaches such as quantum dot nanocrystal sequencing and strobe sequencing.

Rational growth in consumer genomics

The overall tone of the Consumer Genetics Show, held June 2-4, 2010 in Boston MA, was a pragmatic focus on the issues at hand as compared with the enthusiasm and optimism that had marked the conference’s inaugural event last year. One of the biggest shifts was the new programs that some top-tier health service providers have been developing to include genetic testing and interpretation in their organizations. It also became clear that the few widely-agreed upon success stories for genomics in disease diagnosis and drug response (i.e.; warfarin dosing) have been costly to achieve and will not scale to all diseases and all drugs. Cancer continues to be a key killer app for genomics in diagnosis, treatment, prognosis, cancer tumor sequencing, and risk prediction. Appropriate approaches to multigenic risk assessment for health risk and drug response remain untackled. Greater state and federal regulation seems inevitable. Faster-than-Moore’s-law improvements in sequencing costs continue as Illumina dropped the price of whole human genome sequencing for the retail market from $48,000 to $19,500.

There was generally wide agreement that from a public health perspective, personalized genomics is scientifically valid, clinically useful, and reimbursable in specific situations, but not universally – at this time, better information should be obtained for some people, not more information for all people. The focus should be on medical genetics strongly linked to disease, and on pharmacogenomics in treatment. For example, genomic analysis is required for some drugs by the FDA (maraviroc, cetuximab, trastuzumab, and dasatinib), and recommended for several others (warfarin, rasburicase, carbamazepine, abacavir, azathiprine, and irinotecan). A key point is to integrate the drug test with the guidance for drug dosage.

Even when genomic tests are inexpensive enough to be routine, interpretation may be a bottleneck as each individual’s situation is different when taking into account family history, personal medical history, and environmental and other factors. One idea was that the 20,000 pathologists in the US could be a resource for genomic test interpretation; pathologists are already involved as they must certify genetic test data in CLIA labs. Genomic tests and their interpretation would likely need to be standardized and certified in order to be reimbursed in routine medical care. A challenge is that health service payers are not interested or able to drive genomic test product design.

Key science findings

1. The Regulome and Structural Variation

Michael Snyder presented important research that the regulome, the parts of the genome located around the exome (the 1-2% of the genome that codes for protein), may be critical in understanding disease genesis and biological processes. The complexities of RNA are just beginning to be understood. It is known that there is more than just the simple transcription of DNA to RNA involved in controlling gene expression. For example, there is also tight regulation in splicing newly synthesized RNA molecules into the final RNA molecule and in translating messenger RNA to ribosomes to create proteins. Research findings indicate a global/local model of gene regulation, that there are master regulators with universal reach and local regulators operating on a local range of 200 or so genes.

Snyder also presented updates on his lab’s ongoing research into the structural variation of the human genome. A high-resolution sequencing study has been conducted regarding the amount of structural variation in humans, finding that there are ~1,500 structural variations per person that are over 3 kilobases long and that the majority of the structural variations are 3-10 kilobases long with a few extending to 50-100 kilobases (application of this research: Kasowski M, Science, 2010 Apr 9).

2. Reaching beyond the genome to the diseasome, proteome, and microbiome

Several scientists addressed the ways in which science is quickly reaching beyond the single point mutations and structural variation of the genome to other layers of information. There is a need for the digital quantification of the epigenome, the methylome, the transcriptome, the proteome, the metabolome, and the dieaseome/VDJome. For example, the immune system is one of the best monitors of disease state and progression. The strength of individual immune systems can be evaluated through the VDJome (the repertoire of recombined V-D-J regions in immune cells; cumulative immunoglobulin and T-cell receptor antigen exposure)

There are many areas of interest in proteomics including protein profiling, protein-protein interactions, and post-translational modification. A large-scale digital approach to proteomics was presented by Michael Weiner of Affomix. A key focal area is post-translational modification. At least one hundred post-translational modifications have been found, and two are being investigated in particular: phosphorylation (the signal transduction can possibly indicate tumor formation) and glycosylation (possibly indicating tumor progression).

The microbiome (human microbial bacteria) and host-bacteria interactions are an important area for understanding human disease and drug response, and for Procter & Gamble in creating consumer products. The company has basic research and publications underlying products such as the ProX anti-wrinkle skin cream (Hillebrand, Brit Jrl Derm, 2010), rhinovirus, and gingivitis. The company has a substantial vested interest in understanding the microbiome with its variety of nasal, oral, scalp, respiratory, skin, and GI tract-related products.

Personal genome citizen science

Enough people are in possession of SNP genotype data from direct-to-consumer genomic services (e.g., 23andme, deCODEme, Navigenics) that collaborative citizen science genomics is starting to make sense. Participants could contribute genotype data for individual SNPs or their genotype data file (600,000 – 1 million SNPs) to secure peer collaboration platforms, with different levels of permissioning to different groups of ‘gene friends.’

Personal genome citizen science could be carried out in a number of domains ranging from ancestry to health to athletic performance. Research could both replicate and extend existing academic studies and look for new associations between genomic profiles and disease. Citizen scientists could explore and identify different kinds of phenotypic data to collect and apply in attempts to make genomic data meaningful and useful. The proven benefits of opening up datasets to the wisdom of the crowds could be expected with open personal genome research too.

Personal genome citizen science examples taken from the DIYgenomics Citizen Genomes Project list:

• One fun citizen science genomics project could be applying the information in the WIRED article “Don’t tell Geico, you may be a natural born bad driver.” DIY scientists could look up their genotype value for the relevant SNP (rs6265) on the BDNF gene and match this with actual driving records.
• Another project a Silicon Valley-based DIYbio team is starting to look into is Vitamin B12 deficiency. The two relevant SNPs on the MTHFR gene, rs1801133 and rs1801131, are genotyped by 23andme and maybe also by deCODEme and Navigenics. The first step is looking up genotype values for these SNPs, (AG and GT for one participant, for example). For more information on being a peer participant in this study, please contact m AT melanieswan.com
• A third opportunity concerns the application of existing genetic association studies to peer cohorts. For example, the long-awaited results from a Boston University centenarian study were presented in November 2009. Part of this study found 18 SNPs on the ADARB1 and ADARB2 genes for RNA editing associated with centenarians. Citizen scientists could identify individuals with the favorable genotypes for these SNPs and investigate whether these people have corresponding lack of phenotypic biomarkers of aging.
• Even better than having low-cost DNA sequencing tests for consumers would be being able to self-genotype in DIYbio labs. An early example of this was Katherine Aull genotyping herself for hemochromatosis.