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23ANDME, INC.

Address

899 West Evelyn Avenue
MOUNTAIN VIEW, CA, 94041-1225
USA

UEI: JUVFHKN9XCY3

Number of Employees: 236

HUBZone Owned: No

Woman Owned: Yes

Socially and Economically Disadvantaged: No

SBIR/STTR Involvement

Year of first award: 2010

Phase I Awards

Phase II Awards

33.33%

Conversion Rate

$1,265,362

Phase I Dollars

$3,126,061

Phase II Dollars

$4,391,423

Total Awarded

Awards

Up to 10 of the most recent awards are being displayed. To view all of this company's awards, visit the Award Data search page.

Estimating disease risk using genetic data

Amount: $241,905 Topic: 172

Project Summary In the past years over genetic variants have been linked to complex human traits through genome wide association studies GWAS However the predictive power of many of these variants remains limited and it is still unclear how best to use the wealth of information generated by GWAS to impact personal health and clinical practice For nearly years andMe has been not only a driving force in direct to consumer genetic testing but also has established an innovative crowd sourced genetics research platform This platform has yielded a compelling data resource and many genetic discoveries In this proposal we will address the next phase of andMe human genetics research the development of highly scalable and accurate disease risk estimation Two of the key challenges in human genetics research are to determine how to use results of GWAS to paint an accurate picture of an individualandapos s disease risk and to determine how these estimates can provide information of personal and clinical utility These challenges are difficult due to many factors including the wide spectrum of disease classes the paucity of genetic and phenotypic data and significant methodological and computational challenges In this proposal we present a plan to utilize the genetic and phenotypic data stores at andMe to develop validated risk estimation algorithms In Phase I we will build a computational pipeline that will be used to develop predictive algorithms for estimating disease risk Aim and use this pipeline to evaluate predictive ability of different estimation approaches in a broad class of human complex traits Aim In Phase II we will validate these algorithms in external cohorts and build customer facing reports that we will test for user comprehension We believe that the development of accurate risk estimation capability will have a major impact on both consumer genetics and clinical genetics markets Project Narrative The promise of genetics based estimation of disease risk has yet to be realized In this project andMe will use its database of genetic and phenotypic information from over research participants who have contributed more than phenotypic data points on a wide spectrum of disease to build risk estimation algorithms This project will enable andMe to produce the first validated risk estimation algorithms that provide both personal and clinical utility

SBIR

Phase I

2017

HHS

NIH

A new reference panel to boost African American genotype imputation

Amount: $1,758,557 Topic: 172

Project Summary Modern genetic studies have been conducted predominantly in cohorts of individuals of European ancestry By there were approximately ten times as many published genome wide association studies GWAS in people of European ancestry than studies in people of all other ancestries combined This research disparity has led to an uneven understanding of the genetic basis underlying disease in Europeans and non Europeans andMeandapos s web based large scale research model is ideal for scaling genetics research within non European populations and thereby bringing more parity to genetics research Our database is composed of genotypes and phenotypes of over consenting customers including over individuals with non European ancestry The data derived from non European individuals represent a particularly valuable resource for genetic discovery of novel variants that may not be found in the European population However research studies in non European populations are weakened by the lack of availability of large scale reference datasets and in particular genotype imputation panels Genotype imputation is a statistical methodology that uses observations of genotypes in a large reference panel to infer unobserved genotypes in a target dataset This methodology is widely used within GWAS and allows novel genetic associations to be identified and refined Due to this utility very large reference panels have been constructed containing thousands or tens of thousands of whole genome sequences Unfortunately the largest imputation panels are composed of predominantly European genomes reflecting the modern bias towards European studies in GWAS This proposal aims to address this imbalance by constructing an imputation panel specifically for the African American population In doing so we will expand andMe s ability to perform genetic discovery in non European populations and improve the understanding of global genetic variation underlying diseases and traits Key commercial outcomes of the research include the identification of novel genetic targets for internal and external therapeutic development The long term aim is to improve understanding of disease in minority populations which we hope may eventually lead to improved treatments of disease in these historically medically understudied groups Project Narrative Genome wide association studies have yielded many discoveries of genes associated with disease but the vast majority of such studies have been conducted in European populations This proposal aims to empower genetic research in non European populations by developing a reference dataset from targeted DNA sequencing of the diversity contained within the andMe research participant database This study will enable andMe and other researchers to better discover disease variants in individuals with non European ancestry with a particular focus on African American populations

SBIR

Phase II

2016

HHS

NIH

Admixture-driven discovery of disease-associated genetic variants not found in Europeans

Amount: $260,360 Topic: 172

DESCRIPTION provided by applicant Genetic studies have been conducted predominantly in cohorts of individuals of European ancestry By there were approximately ten times as many published genome wide association studies GWAS in people of European ancestry than studies in people of all other ancestries combined This research disparity has led to an uneven understanding in the genetic basis underlying disease in Europeans and non Europeans andMeandapos s web based large scale research model is ideal for scaling genetics research within non European populations and bring more parity in genetic research With our previous SBIR grant R HG we expanded andMeandapos s tools to mine the genetic and phenotypic information in the database largely through improved survey data collection as well as better management and computational tools This proposal will extend andMeandapos s infrastructure for association studies to leverage the variation found in admixed individuals individuals with ancestry from multiple continents We will develop a pipeline for large scale computationally efficient admixture mapping that allows us to interrogate the variation in admixed genomes Admixture mapping looks for regions of the genome that have an enrichment of one ancestral background in individuals with a disease indicative of the presence of risk variants that differ i frequency among the ancestral populations andMeandapos s genotype phenotype database derived from over research consented customers includes data from over Latinos and African Americans In our proposal we aim to harness genetic admixture to drive the discovery of disease variants found in non Europeans especially variants of African and Native American origin found in the admixed genomes of African Americans and Latinos Unlike previous admixture mapping studies which typically relied on small sets of ancestry informative markers we will leverage andMeandapos s fine scale local ancestry estimates and growing genotype phenotype database for admixture mapping in thousands of individuals across dozens of phenotypes We will implement an admixture mapping pipeline that leverages our existing infrastructure for fine scale local ancestry inference and validate the pipeline through replicatin of a previous hit Aim We will apply our pipeline to several diseases that have been either previously targeted by admixture mapping studies or have been identified by the CDC as contributing to growing health disparities among groups which will require determining which combination of cohorts and ancestries will give rise to greatest power in finding genetic associations Aim Lastly we follow up our top novel target to both validate findings and fine map Aim This proposal will expand andMeandapos s research pipeline to include admixture mapping and improve the understanding of global genetic variation underlying diseases and traits Key commercial outcomes of the research are novel genetic targets for internal and external therapeutic development The long term aim is to improve understanding of disease in minority populations which we hope may eventually lead to improved treatments of disease in these historically medically understudied groups PUBLIC HEALTH RELEVANCE Genome wide association studies have yielded many discoveries of genes associated with disease but largely in European populations This proposal aims to discover new associations of genetic variants from globally diverse backgrounds by developing methods that take advantage of information in genetically admixed andMe research participants This study will enable andMe to improve the knowledge of disease variants found in non Europeans especially variants of African and Native American origin found today in African Americans and Latinos

SBIR

Phase I

2016

HHS

NIH

Development of a web-based database and research engine for genetic discovery

Amount: $1,367,504 Topic: NHGRI

DESCRIPTION (provided by applicant): 23andMe, Inc., is a personal genomics company with a mission of accelerating medical discoveries by empowering consumers to participate in research. At the heart of this mission is the 23andMe research engine, a novel platform for conducting genetic studies that allows individuals to participate in genetic research by enrolling in the company's Personal Genome Service(R) and taking online surveys. Over 130,000 individuals have contributed genetic and phenotypic data, andthis number is growing by over 50,000 each year. Our initial publications have shown the power and efficiency of this web-based approach for discovering novel genetic associations for a range of traits and diseases. These early successes, however, made only partial use of the rich and rapidly expanding 23andMe database. Our current challenge is to fully mine the genetic and phenotypic information that we are collecting in order to accelerate the pace of human genetic research. In Phase I of this grant, wehave demonstrated the feasibility of this unique research approach. We have developed new computational tools to facilitate analysis of thousands of phenotypes in hundreds of thousands of people, curated survey data related to many new phenotypes, studiedthe reliability of our genetic data, and conducted user interviews for several surveys. Building on this foundation, in Phase II we will refine existing survey questions, develop and post new surveys, and analyze a subset of the resulting data to furtherdemonstrate the utility of this platform (Aim #1); implement novel web-based data collection tools to efficiently gather longitudinal and cognitive data (Aim #2); capitalize on the upcoming explosion of whole-genome sequence data through statistical imputation, making it possible for us to discover rare SNPs associated with disease (Aim #3); and test and refine a new tool, the 23andMe Research Portal, that will provide external researchers access to the 23andMe database (Aim #4). We expect that by the endof the proposed project the 23andMe database will include genetic and phenotypic data for over 400,000 individuals, including members of several understudied populations. This database has the potential to yield thousands of novel genetic associations fordiseases and traits, leading to a greater biological understanding of these conditions, potential drug targets, and improved tools to predict an individual's genetic risk of disease. A key commercial outcome of the project will be a database and researchengine that is more valuable to potential research partners. Furthermore, discoveries will drive new reports for 23andMe customers, thus increasing the value of the Personal Genome Service(R). PUBLIC HEALTH RELEVANCE PUBLIC HEALTH RELEVANCE: Genetic research has already produced biological discoveries and personalized treatments, but the field has far to go. This proposal aims to accelerate that research by taking advantage of 23andMe's growing membership of research participants who provide a wide range of personal as well as genetic information. The study will enable 23andMe to greatly increase the scope of their research and lead to new understanding of how genetics impacts human disease.

SBIR

Phase II

2013

HHS

NIH

Development of a web-based database and research engine for genetic discovery

Amount: $232,602 Topic: NHGRI

DESCRIPTION (provided by applicant): 23andMe is a personal genomics company with a mission of accelerating medical discoveries by empowering consumers to participate in research. At the heart of this mission is the 23andMe research engine, a novel platform for conducting genetic studies that allows individuals to participate in genetic research by enrolling in the company's Personal Genome Service(R) and taking online surveys. Over 80,000 genotyped individuals have contributed data, and this number is growing by over 50,000 each year. Our initial publications have shown the power and efficiency of this web- based approach for discovering novel genetic associations for a range of traits and diseases. These early successes, however, only made partial use of the rich and rapidly expanding 23andMe database. Our current challenge is to fully exploit the genetic and disease information that we can collect to accelerate the pace of human genetic research. To achieve this goal, we propose, in Phase I, to measure and improve the reliability of our self- reported data, to analyze and organize survey responses for hundreds of new traits, and to extract information of greater depth and quality from the previously collected genetic data. Successful completion of Phase Iwill demonstrate the feasibility of our web-based approach for studying a broad range of conditions. Building on this foundation, in Phase II we will develop a set of new surveys and implement novel web-based data collection tools to efficiently gather longitudinal data. Capitalizing on the upcoming explosion of whole-genome sequence data, we will also greatly improve the depth of our genetic data through statistical imputation and imputation via identity-by-descent. At the end of the proposed research, weexpect the 23andMe database to grow to over 200,000 genotyped individuals with detailed health and trait information. Applying computational sequencing methods to these data will deliver the informational equivalent of thousands of whole- genome sequencesat very low cost. This database has the potential to yield hundreds, if not thousands, of novel genetic associations for diseases and traits, leading to a greater biological understanding of these conditions, potential drug targets, and improved tools topredict an individual's genetic risk of disease. Using the diverse 23andMe cohort, we will extend genetic research to understudied populations. A key commercial outcome of the project will be a database and research engine that is more valuable to potential research partners. Furthermore, discoveries will drive new reports for 23andMe customers, thus increasing the value of the Personal Genome Service(R). PUBLIC HEALTH RELEVANCE: Genetic research has already produced biological discoveries and personalized treatments, but the field has far to go. This proposal aims to accelerate that research by taking advantage of 23andMe's growing membership of research participants who provide a wide range of personal as well as genetic information. The studywill enable 23andMe to greatly increase the scope of their research and lead to new understanding of how genetics impacts human disease.

SBIR

Phase I

2012

HHS

NIH

Genetics of Allergic Disease in a Participatory Research Cohort

Amount: $143,253 Topic: NHLBI

DESCRIPTION (provided by applicant): Genetics of Allergic Disease in a Participatory Research Cohort Asthma and allergic disease are extremely common conditions with substantial public health burdens, affecting as many as one in five Americans. Discovery of genetic variants affecting allergic disease risk would contribute to our understanding of disease mechanisms as well as guide work towards improved diagnostics and treatments. Genome wide association studies (GWAS) have become well established as powerful tools for elucidating the genetic basis of disease. Recent experience with GWAS of complex traits shows that effect sizes at individual loci tend to be small, hence, the field has moved towards large, collaborative studies that combine data from multiplecohorts. In this context, the 23andMe participant cohort, with more than 100,000 genotyped individuals who have consented to participate in research, is a unique resource for studying the genetics of common disease. We have collected survey data in the 23andMe cohort covering a variety of asthma and allergy related phenotypes. More than 25,000 participants report one or more allergies, more than 8000 report an asthma diagnosis, and more than 5000 report having eczema. Our objective is to use the 23andMecohort to investigate the genetic and environmental basis of asthma and allergic disease. In Phase I, we will fully characterize and validate our self- reported phenotypes in the 23andMe cohort, and relate them to clinical definitions used in other studies. We will perform association studies informed by that phenotypic analysis, and participate in large consortia to meta-analyze GWAS for asthma and eczema. In Phase II, we will extend these studies to include additional phenotypes, treatment response, gene-gene, and gene-environment interactions as well as to incorporate additional participants recruited from new customers of the 23andMe Personal Genome Service(R). We will incorporate results of these studies into our Personal Genome Service(R), by developing new reports and enhancing existing reports on allergy phenotypes for 23andMe customers. These reports will include personalized risk assessments for allergic disease. This work will also demonstrate the strengths and scientific validity of the 23andMe research platform and set the stage for commercial research partnerships in the allergic disease area. PUBLIC HEALTH RELEVANCE: Asthma and allergic disease are extremely common conditions with substantial public health burdens, affecting as many one in five Americans. The proposed research will investigate the genetic and environmental contributions to allergic disease in the 23andMe participant cohort. Discovery of genetic variants affecting allergic disease risk would contribute to our understanding of disease mechanisms as well as guide work towards improved diagnostics and treatments.

SBIR

Phase I

2012

HHS

NIH

Development of DNA Sequence Data-Quality Metrics for Personal Genomics

Amount: $197,398 Topic: NHGRI

DESCRIPTION (provided by applicant): In June 2011, the FDA hosted a public meeting: Ultra High Throughput Sequencing for Clinical Diagnostic Applications - Approaches to Assess Analytical Validity (FDA Public Meeting, 2011). The background documentation for this meeting noted that In order to effectively utilize new sequencing technologies for clinical applications, appropriate evaluation tools (e.g., standards, well established criteria) are needed to determine the accuracy of the results. Achieving excellent data quality from next-generation sequencing technologies and understanding when the results may be in error is of clear importance, whether the results are being viewed by a clinician or a consumer. For this application, 23andMe will focus onthe analysis of the accuracy of next-generation sequencing technologies using approximately 150 exomes (including 50 new exomes sequenced for this project) and 100 whole genomes, specifically with reference to false positive and false negative rates for variants located in known disease genes. 23andMe has genotyped over 125,000 individuals and reported data back to them on hundreds of disease-associated variants. This experience has shown us that many important disease genes are difficult to assay with a genotyping chip, whether due to pseudogenes (e.g., GBA), paralogs (e.g., SMN1, CYP2D6) or for unknown reasons (e.g., APOE). We have also noted differences in genotyping accuracy between blood and saliva. For this reason, we expend significant resources validating the results of our genotyping chip using positive controls derived from the 23andMe customer database. The 50 exomes we will sequence for this project will be chosen to carry Sanger sequencing-validated disease-associated variants in the disease genes listed above. This project is a crucial first step in our goal of creating a pipeline for next-generation sequence annotation that combines (a) stringent QC based on genotyping array and Sanger sequencing data; (b) manually curated data from the humangenetics literature; and (c) computationally derived variant assessment for variants of unknown significance; to produce a report that will be returned to a consumer for a personalized health assessment. PUBLIC HEALTH RELEVANCE: Before we can achieve broad adoption of novel sequencing technologies in the clinic, we must understand when their results are accurate. This project will investigate error rates from next-generation sequencing technologies in clinically relevant disease genes. This will help us define data quality metrics and technical specifications for a sequencing-based Personal Genome Service(R).

SBIR

Phase I

2012

HHS

NIH

Web-based Phenotyping for Genome Wide Association Studies of Drug Response

Amount: $189,844

DESCRIPTION (provided by applicant): Greater availability of personalized genetic information regarding the efficacy or toxicity of medications could lead to improved patient care and save consumers, insurers and medical institutions billions of dollars per year. Although the field of pharmacogenomics has had some success in discovering relationships between genetic variants and drug response, a great deal of genetic variation in drug response remains unexplained. Our broad, long term research aim is to identify novel pharmacogenetic associations using web-based phenotyping of efficacy and toxicity for several major drug classes. With that goal in mind, our short term aim is to determine whether web-based collection of phenotype data along with genome-wide data for thousands of 23andMe customers leads to replication of known associations between responses to proton pump inhibitors (PPIs) and the gene CYP2C19, and between responses to several commonly used medications and the gene CYP2C9. The specific aims of this study are (1) to develop and administer web-based surveys to collect information regarding response to several commonly used classes of medications (including antihistamines, analgesics, blood thinners, and proton-pump inhibitors) from at least 3,000 individuals; and (2) to determine whether this web-based research model yields replications of known associations between several commonly used medications and the genes CYP2C19 and CYP2C9. To conduct this innovative study the 23andMe research group will leverage several resources, including a broad set of drug metabolism-related single nucleotide polymorphisms (SNPs) on the 23andMe custom genotyping array. This project will also leverage involvement of a rapidly expanding, engaged, genotyped cohort of 23andMe customers who have the option to participate in research by responding to web-based questionnaires. The parallel and continuous nature of this research model allows for the efficient recruitment of participants to many studies at once and reduces the cost of re-contacting for additional analyses. As evidence of our rapid capability to assemble a cohort, an initial survey regarding commonly used medications solicited, within a month, responses from about 2500 individuals genotyped at 580,000 SNPs. Possible outcomes of this study include the replication of known pharmacogenomic associations and the discovery of novel associations. If the study is successful in yielding replications, it will set the stage for rapid, well-powered and cost-effective research on variation in response to a large number of medications, thereby significantly advancing personalized medicine. PUBLIC HEALTH RELEVANCE: The availability of personalized genetic information regarding the efficacy or toxicity of medications could lead to improved patient care, and save consumers, insurers and medical institutions billions of dollars per year. With that goal in mind, our near term aim in this grant is to determine whether web-based collection of phenotype data along with genome-wide data for thousands of 23andMe customers leads to replication of known associations two genes (CYP2C9 and CY2C19) and several major drug classes of commonly used medications.

SBIR

Phase I

2010

HHS

NIH