1,721,779 research outputs found
23andMe Inc.: Patent law and lifestyle genetics
No full textThe venture, 23andMe Inc., raises a host of issues in respect of patent law, policy, and practice in respect of lifestyle genetics and personalised medicine. The company observes: ‘We recognize that the availability of personal genetic information raises important issues at the nexus of ethics, law, and public policy’. 23andMe Inc. has tested the boundaries of patent law, with its patent applications, which cut across information technology, medicine, and biotechnology. The company’s research raises fundamental issues about patentability, especially in light of the litigation in Bilski v. Kappos, Mayo Collaborative Services v. Prometheus Laboratories Inc. and Association for Molecular Pathology v. United States Patent and Trademark Office and Myriad Genetics Inc. There has been much debate and controversy over 23andMe Inc. filing patent applications – particularly in respect of its granted patent on ‘Polymorphisms associated with Parkinson’s Disease’. The direct-to-consumer marketing of genetic testing by 23andMe Inc. has also raised important questions of bioethics and human rights. It is queried whether the terms of service for 23andMe Inc. provide adequate recognition of the concepts of informed consent and benefit-sharing, especially in light of litigation in this area in the United States. Given the patent thickets surrounding genetic testing, the case study of 23andMe Inc. also highlights questions about patent infringement and patent exceptions. The future reform of patent law, policy, and practice needs to take into account new developments in lifestyle genetics and personalised medicine – as exemplified by 23andMe Inc
23andMe SNP chip genotype data
No full text<p>23andMe genotype data for Mother, Father, Son, Daughter and Aunt. Son is 23andMe version 2 data and the rest of the family are 23andMe version 3 data.</p
Externalizing-23andMe
No full textPublicly available (23andMe removed) externalizing summary statistics from Linner & Mallard et al. (2022; Nat. Neuroscience
Dyslexia GWAS Summary Statistics for top 10K SNPs
No full textReading and writing are crucial life skills but roughly 1 in 10 children are affected by dyslexia, which can persist into adulthood. Family studies of dyslexia suggest heritability up to 70%, yet few convincing genetic markers have been found. Our genome-wide association study of 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls identified 42 independent significant loci: 15 in genes linked to cognitive ability/educational attainment; 27 novel and potentially more specific to dyslexia. Twenty-three loci (13 novel) were validated in independent cohorts of Chinese and European ancestry. Genetic aetiology of dyslexia was similar between sexes, and genetic covariance with many traits was found, including ambidexterity, but not neuroanatomical measures of language-related circuitry. Dyslexia polygenic scores explained up to 6% of variance in reading traits, and might in future contribute to earlier identification and remediation of dyslexia.File header:
assay.name scaffold position effect_allele other_allele effect stderr pvalue avg.rsqr
Notes:
assay.name = in most cases, a dbSNP build 146 rsID
scaffold = chromosome number
effect = log odds
avg.sqr = The average imputation r2 across all batches of imputation results, a measure of overall imputation quality
Corpas Family Comparison 23andMe vs Exome
No full text<p># For each Family Member the SNPs Found in both 23andMe Data & Exome SNP Calls<br>* daughter: 36315 SNPs<br>* father: 39624 SNPs<br>* mother: 40234 SNPs<br>* son: 22233 SNPs (so the v2 chip seems to have an impact)</p>
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<p># SNP Calling Quality<br>Most 'non-concordant' SNPs (not filtered for haploid ones that are given as diploid in VCF or positions where 23andMe just used the opposite strand for the prediction) have a low coverage of < 10. See the attached distribution graphs for details on that.</p>
<p>The 'Calling Sequencing SNPs' document of Illumina (http://res.illumina.com/documents/products/technotes/technote_snp_caller_sequencing.pdf) says that at a coverage of 20x genotypes are only 95% certain, this rises to 99% with 30x coverage. Thus I only looked at non-concordant SNPs with a coverage of at least 30x, because for all others it's pretty certain that non-concordance will mainly arise due to lack in coverage.</p>
<p># Filtering Non-Concordant SNPs<br>Firstly I removed the SNPs where 23andMe SNPs and the Exome SNPs are identical in principle but 23andMe uses the opposite strand for the SNP prediction (e.g. Exome says genotype is AG and 23andMe says genotype is TC) and haploid SNPs (e.g. X/Y chromosomes for males) where the haploid predictions of 23andMe match the diploid exome predictions (for some reason haploid loci are called as homozygous diploid loci in the Exome VCF).</p>
<p>## Closer Look at the Resulting SNP Subset<br>I then had a detailed look at the resulting list of SNPs and compared the non-concordant SNPs in the family context. For most errors it's impossible to say whether the 23andMe data or the Exome data is wrong. This is either because the SNPs for the relatives are non-concordant as well or just missing. And in some cases no clear Mendelian Inheritance Error can be found because both inferred genotypes could result in the observed family tree. There are three exceptions to this:</p>
<p>rs1056806: For the mother the exome SNP calling gives the genotype as TT while 23andMe gives it as CT. The father's genotype is concordantly CC in both data sets and the daughter's genotype is concordantly CC as well. Thus the exome calling for the mother seems to be wrong. Puzzlingly the C allele was observed 19 out of 96 times for the mother's exome data, but still the genotype was called as TT.</p>
<p>rs3749488: The genotype for the father is given as CC in the 23andMe data and as AC in the exome SNP calling. The mother's genotype is given as AC in both data sets. Both children have concordant genotypes of AA. Thus the father's 23andMe genotype call of CC seems to be wrong and the genotype of AC given by the exome data seems to be the right one.</p>
<p>rs1926736: For the daughter the exome SNP calling gives the genotype as AA, 23andMe gives it as AG. For the father and the mother the exome and 23andMe data agree: The father's genotype is GG, mother's genotype is AG. Thus the daughter's genotype in the exome SNP calls seems to be wrong. The coverage seems to be okay with 46x but only one allele was observed, thus this is either a mapping artifact or it's an unlikely case where only a single allele was sequenced.</p>
<p>Besides the Coverage Distribution Graphs I've also attached the list of non-concordant SNPs and the genotypes for each family members as inferred from the 23andMe and the Exome data. Of most interest will be the last 8 columns. For each family member the Exome genotype (including coverage etc) from the VCF are given along with the genotype as inferred by 23andMe. Fields with a red background show non-concordant genotype calls.<br>Fields with a yellow background seem non-concordant, but I guess it's also just a case of where 23andMe used the opposite strand for one allele, e.g. rs11580218: the father's genotype in the exome is given as GA and in 23andMe it's GT. According to dbSNP known alleles are only G & A. So probably for the "T" call they just used the "wrong" strand with respect to dbSNP.<br>Fields with a green background show where the family data can be used to infer which data set gives the wrong call for a given family member.</p>
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23andMe Inc.: Patent Law and Lifestyle Genetics
No full textRefereed Article: Matthew Rimmer, '23andMe Inc.: Patent Law and Lifestyle Genetics' (2012) 22 (1) Journal of Law, Information and Science 132-164
The Business and the Science Behind 23andMe: Chronic Kidney Disease
No full text23andMe is a new and emerging company for the general public to inquire about both their ancestry and potential health risks. The field of genetic testing has become increasingly more popular over the past few years with a high demand market that can vary by region and a variety of demographics. Chronic kidney disease (CKD) is characterized by kidney damage so extensive that the kidneys can no longer properly function to filter waste and excess fluid from the body. 23andMe can test a customer\u27s risk of developing CKD by examining if they are at high risk for PKD1 and APOL1 protein mutations. 23andMe produces high clinical and analytical reproducibility with 5 confidence intervals to choose from. This market has opened doors in both the public and private sectors to unite some of the brightest minds in research
Phenome-wide association studies across large population cohorts support drug target validation
Get PDFPhenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P<0.05) and identify nine study-wide significant novel associations (of 71 with FDR <0.1). We describe associations that may predict ADEs, e.g., acne, high cholesterol, gout, and gallstones with rs738409 (p.I148M) in PNPLA3 and asthma with rs1990760 (p.T946A) in IFIH1. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.Peer reviewe
Learn About Yourself: The Ins and Outs of AAT Deficiency and 23andMe
No full text23andMe focuses on providing consumers access to their DNA and exploring the data within it. With emphasis on the Y chromosome and mitochondrial DNA, 23andMe provides ancestry exploration as well as valid health and trait reports. DNA saliva samples are collected to observe information and produce results in a quick, understandable, and easy consumer-friendly experience
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