Category Archives: Genetics

Genetics

Building trust and saving lives: A community approach to genetic education – Medical University of South Carolina

Changes to DNA, known as mutations, can increase the likelihood of developing cancer. Specifically, people with mutations in their BRCA 1 and 2 genes are substantially more likely to develop hereditary breast and ovarian cancers. But how do people know if they have these mutations?

Genetic testing.

Genetic testing allows doctors to see these microscopic changes. Knowing these mutations exist, doctors will check for signs of breast and ovarian cancers more often.

Yet minorities, especially Black women, are less likely to participate in genetic testing. Even fewer engage in follow-up services, such as recommended interventions, which reduce risk.

To change that, a team of researchers at the Medical University of South Carolina led by Caitlin G. Allen, Ph.D., plans to teach community health workers (CHWs), who often reside in the communities they serve, how to share the importance of genetic screening with their peers. Allen is an assistant professor in the Department of Public Health Sciences at MUSC.

Community health workers act as a bridge between the community and researchers and clinicians and can help to answer questions, provide support services and address a lot of social determinants of health issues, said Allen, who has spent more than a decade working alongside and providing support for CHWs.

-- Dr. Caitlin Allen

As a first step, the team worked with CHWs to learn about their needs and preferences for genetics training materials. They describe these efforts in a November article in the Journal of Cancer Education.

Knowing that some minority communities dont trust researchers and medical staff, Allen and her team recruited CHWs because they are already trusted members of the community. The researchers found that CHWs were already very curious about genetics and eager to learn more.

There was significant interest from CHWs to learn more about cancer and genetics, but the training to support them in building these competencies and genetic literacy didnt exist, explained Allen.

With funding from the American Cancer Society and MUSC Hollings Cancer Center, Allen and her team were able to create this training by holding focus groups with CHWs and doctors, asking them to come to an agreement about which lessons should be included. Once the training materials were developed, the CHWs told the researchers whether they were clear and easy to understand.

Incorporating feedback from these focus groups, Allen and her team finalized their 10-module CHW training called Keeping Each other Engaged Program via IT (KEEP IT). The researchers virtually delivered the 12-hour training to 26 CHWs. The training was effective in improving genetic knowledge and competencies and highly rated by the CHWs. The full outcomes of the KEEP IT training sessions will be published soon.

It was a privilege to take the idea of CHWs teaching their communities about genetics and put it into action, said Allen.

But the researchers are far from being finished. They are applying for funding so they can expand the training across four other Southern states.

Designing and delivering trainings in collaboration with community members is really effective, stressed Allen, and its important to have community perspective across all research.

Reference

Allen CG, Hatch A, Qanungo S, Ford M, Marrison ST, Umemba Q. Development of a Hereditary Breast and Ovarian Cancer and Genetics Curriculum for Community Health Workers: KEEP IT (Keeping Each other Engaged Program via IT) Community Health Worker Training. J Cancer Educ. 2023 Nov 3. doi: 10.1007/s13187-023-02377-7. Epub ahead of print. PMID: 37919623.

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Building trust and saving lives: A community approach to genetic education - Medical University of South Carolina

Genetics

SOPHiA GENETICS and Karkinos Healthcare Forge Strategic Partnership to Advance Cancer Research in India India … – PR Newswire

SOPHiA GENETICS technology helps advance cancer research across India

SOPHiA GENETICS and Karkinos Healthcare join forces to propel cutting-edge genomic solutions for breakthroughs in personalized cancer care in India

BOSTON andROLLE, Switzerland, Jan. 14, 2024 /PRNewswire/ --SOPHiA GENETICS (Nasdaq: SOPH), a cloud-native software company and a leader in data-driven medicine, today announced that Karkinos Healthcare, a purpose-driven cancer care technology network based in India, will partner with SOPHiA GENETICS and adopt the SOPHiA DDM Platform to advance cancer testing and research for blood cancers and solid tumors to underserved areas in low and middle-income countries.

Karkinos Healthcare is a purpose-driven, technology-led oncology platform, focused on early detection, advanced diagnostics, and treatment delivery of common cancers, using its Distributed Cancer Care Network across India. Karkinos Healthcare provides end-to-end solutions for oncology ecosystem, including disease screening, diagnosis,surgery, chemotherapy, radiotherapy andcomprehensive patient navigation through the care continuum, in addition to operating advanced research and development laboratories. The company is on a mission to create 'Community as a Cancer Centre' with an endeavour to serve one million patients annually byaddressing the accessibility andaffordability gaps in cancer care through a digitally curated hub and spoke and further spoke model, and not restrict cancer care to comprehensive centres alone.

"It is our continued goal to improve health outcomes for patients globally by expanding access to precision oncology and equipping local health institutions with the tools and technology needed to practice data-driven medicine," said Dr. Jurgi Camblong, CEO and Co-founder, SOPHiA GENETICS. "By aligning with Karkinos, who share the mutual goal, we can help increase the use of best-in-class cancer testing for rural and underserved communities around the world."

On this strategic partnership, Dr. R Venkataramanan, Founder and CEO, Karkinos Healthcaresaid, "Through collaborative research initiatives, Karkinos Healthcare aims to address the comprehensive genomic landscape identification for Indian population, with a focus on precision medicine. This alliance will have the potential to generate evidence and world-class research for faster and accurate diagnosis and better control and management of cancers, particularly for the underprivileged population of our country."

The SOPHiA DDM Platform is designed to compute a wide array of genomic variants and continually hone machine learning algorithms to detect rare and challenging cases. Karkinos Healthcare will use SOPHiA GENETICS' technology to expand its offerings, advance research and streamline workflow for a variety of blood cancers, including Myeloid cancer and Lymphoma. In addition, the company will analyse solid tumours for a variety of cancer types including ovarian, prostate, breast, pancreas, lung, colorectal, skin, and brain cancers.

The SOPHiA DDM Platform offers tailored NGS-based workflows to streamline processes from sample to report to accelerate analysis. By using the SOPHiA DDM Platform, researchers from Karkinos Healthcare will quickly obtain high-quality and reproducible data that will ultimately accelerate clinical research studies and advance the use of precision medicine.

About SOPHiA GENETICS SOPHiA GENETICS (Nasdaq: SOPH) is a software company dedicated to establishing the practice of data-driven medicine as the standard of care and for life sciences research. It is the creator of the SOPHiA DDM Platform, a cloud-native platform capable of analyzing data and generating insights from complex multimodal data sets and different diagnostic modalities. The SOPHiA DDM Platform and related solutions, products and services are currently used by a broad network of hospital, laboratory, and biopharma institutions globally. For more information, visitSOPHiAGENETICS.COM, or connect onX,LinkedIn,Facebook, andInstagram.Where others see data, we see answers.

Product DisclaimerSOPHiA GENETICS products are for Research Use Only and not for use in diagnostic procedures, unless specified otherwise. The information in this press release is about products that may or may not be available in different countries and, if applicable, may or may not have received approval or market clearance by a governmental regulatory body for different indications for use. Please contact [emailprotected] to obtain the appropriate product information for your country of residence.

SOPHiA GENETICS: Forward-Looking StatementThis press release contains statements that constitute forward-looking statements. All statements other than statements of historical facts contained in this press release, including statements regarding our future results of operations and financial position, business strategy, products, and technology, as well as plans and objectives of management for future operations, are forward-looking statements. Forward-looking statements are based on our management's beliefs and assumptions and on information currently available to our management. Such statements are subject to risks and uncertainties, and actual results may differ materially from those expressed or implied in the forward-looking statements due to various factors, including those described in our filings with the U.S. Securities and Exchange Commission. No assurance can be given that such future results will be achieved. Such forward-looking statements contained in this press release speak only as of the date hereof. We expressly disclaim any obligation or undertaking to update these forward-looking statements contained in this press release to reflect any change in our expectations or any change in events, conditions, or circumstances on which such statements are based, unless required to do so by applicable law. No representations or warranties (expressed or implied) are made about the accuracy of any such forward-looking statements.

About Karkinos HealthcareKarkinos Healthcare is a purpose driven technology-led oncology health care platform for early detection and diagnosis of common cancers. The organisation espouses use of a distributed cancer care network, while working with a network of healthcare institutions and domain experts within the ecosystem, with an aim to provide comprehensive cancer care closer to individuals' homes.

Tata Group, Reliance Industries, Mayo Clinic, and Rakuten Medical Inc. are among the World's leading organizations that have invested in Karkinos Healthcare. The company has also partnered with Tata Memorial Hospital, Guys and St Thomas NHS Foundation Trust (UK), and has inked several research collaborations with leading academic institutions in the United States to stay on the cutting edge of oncology treatment and care.To learn more, visit https://www.karkinos.in/about-us/

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SOPHiA GENETICS and Karkinos Healthcare Forge Strategic Partnership to Advance Cancer Research in India India ... - PR Newswire

Genetics

Genetics Reveal Poor Oral Health in Mesolithic Era – Mirage News

Members of a hunter-gatherer group that lived in south-western Scandinavia during the Mesolithic era approximately 10,000 years ago may have been affected by tooth decay and gum disease, according to a study published in Scientific Reports.

Emrah Krdk, Anders Gtherstrm and colleagues sequenced the DNA found on three pieces of birch tar a substance made from heated birch bark that were excavated in the 1990s from Huseby Klev, Sweden and have been dated to between 9,890 and 9,540 years old. They created profiles of the microbial, plant, and animal species DNA found on each sample and compared these to those previously reported for modern human samples, ancient human dental plaque, and a 6,000 year old chewed birch tar sample

The authors found that the microbial profiles of the birch tar samples were most similar to microbes found in the modern human mouth, in ancient human dental plaque, and in a 6,000 year old chewed birch tar sample. This suggests that the samples from Huseby Klev were chewed by humans. They also found that they contained an increased abundance of several bacteria that are commonly associated with gum disease such as Treponema denticola, Streptococcus anginosus, and Slackia exigua and tooth decay such as Streptococcus sobrinus and Parascardovia denticolens. Based on the relative abundance of microbial species in the birch tar samples and using machine learning models, the authors estimate that the probability that members of the hunter-gatherer group were affected by gum disease is between 70 and 80%. The authors suggest that the wider use of teeth to perform tasks involving gripping, cutting and tearing in ancient hunter-gatherer societies may have increased their risk of coming into contact with microbial species that cause gum disease.

In addition to microbial DNA, the authors identified DNA sequences consistent with those from a range of plant and animal species, including hazelnut, apple, mistletoe, red fox, grey wolf, mallard, limpet, and brown trout. These could reflect the materials that members of the hunter-gatherer group chewed prior to the birch tar samples. The authors speculate that these materials could have included food sources, furs, and bone tools.

The findings highlight the poor oral health of a group of Mesolithic Scandinavian hunter-gatherers and provide insight into their diet, material use, and local environment.

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Genetics Reveal Poor Oral Health in Mesolithic Era - Mirage News

Genetics

Nova Siri Genetics strengthens its presence in Huelva, growing by 34% – FreshPlaza.com

The province of Huelva has become a strategic territory for Nova Siri Genetics, a company that specializes in the research and experimentation of new strawberry and berry varieties. "Huelva is the area in Europe where its activity has grown the most. In fact, in the current 2023-2024 campaign the producing companies have planted 50 million plants of the company's strawberry varieties."

"Even though the area planted with strawberries in the province of Huelva decreased by 5% this campaign, Nova Siri Genetics managed to considerably increase its activity, as these 50 million plants represent a 34% growth compared to the previous 2022-2023 campaign."

"NSG 2023Marimbella, NSG 207Gioelita, and NSG 465Rossetta are -in this order- Nova Siri Genetics most implanted varieties in the province of Huelva. All three are early strawberry varieties that allow producers to advance their supply of this fruit to November and December. These varieties yield quality fruits and outstanding volumes in terms of kilograms per hectare."

"In fact, in the province of Huelva, the Marimbella variety yields more than 50,000 kilograms of strawberries per hectare. It's Nova Siri Genetics program's most cultivated variety in this area of southwestern Spain, with a total of 31 million plants grown for the current campaign."

Joaqun Domnguez, Nova Siri Genetics' commercial manager for Spain and Morocco, highlighted "the rusticity of these varieties, as they are resistant to Botrytis and other diseases caused by the main fungal pathogens in the soil. In addition, these varieties yield strawberries with excellent organoleptic characteristics, such as aroma, flavor, shape, size, consistent pulp, and an elastic epidermis that allows them to have a long shelf life. Finally, their precocity guarantees producers will have fruits at the end of autumn and the beginning of winter."

According to Joaqun Domnguez, Nova Siri Genetics' mission is to provide varieties that meet the needs of producers and consumers. That's why the company is developing in the province of Huelva a program for the participatory selection of varieties, which is a continuation of participatory plant breeding and a key step in establishing the objectives of this action, involving the different participants in the chain (scientists, production companies, consultants, sales representatives, and consumers)."

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Nova Siri Genetics strengthens its presence in Huelva, growing by 34% - FreshPlaza.com

Genetics

Controversial New Research Find That Bisexuals Are a Bunch of Rascals – Futurism

Image by Getty / Futurism

It turns out that there may be some genetic and evolutionary factors afoot when it comes to bisexuality but naturally, there are ethical concerns about such bold statements.

AsScience magazine reports, this new research looking into the genetics of bisexuality suggests more of a propensity for risk-taking and is distinct from the genes that may underly homosexual behavior. If that sentence raises alarm bells, you're not alone.

Published in the journalScience Advances, even the name of the paper itself, "Genetic variants underlying human bisexual behavior are reproductively advantageous," harkens back to the old nature-versus-nurture arguments that most people, queer or otherwise, would rather forget.

Despite the face-value implications, however, the content of the study is pretty fascinating.

Jianzhi Zhang and Siliang Song, the evolutionary geneticist duo out of the University of Michigan who coauthored the paper together, insist that their findings need not be painted with the brush of morality because, as Zhang put it, the association they found between bisexuality and risk-taking behavior "is an empirical observation."

"We hold no moral judgement on risk-taking and believe [it] has pros and cons (depending on the situation), as almost any trait," Zhang toldScience. "This is partly a biological question, so we should understand it."

Zhang and Song examined data from the UK Biobank, the giant genetic database compiled with the help of 23andMe, and deviated in one key way from a groundbreaking 2019 study about the genetics of same-sex behaviors: they decoupled self-reported homosexual and bisexual behaviors, which until now had been lumped together under the "same-sex sex" umbrella.

Using some statistical and algorithmic magic, the UM team found that although the genetic variants between bisexual behavior and homosexual behavior are related, they're still distinct from one another.

What's more, the risk-taking aspect of bisexual behavior was apparent in men, but not in women and, strangely enough, the risk-taking genetic variants also seemed to account for a higher chance of having offspring, too.

The conclusion drawn here is that bisexuality has evolutionary benefits. But as behavioral geneticist Andrea Camperio Ciani of the University of Padova in Italy pointed out to Science, it still doesn't do much to explain what evolutionary purpose, if any, same-sex behavior might carry.

"[Gay people] have been everywhere in every nation," he explained. "Always at a low frequency, but everywhere."

Beyond the murkiness on the evolutionary side of things, there's also the data itself. The paper's results are based on self-reported sexual behaviors rather than orientation or identity. And as Yale geneticist Steven Reilly cautioned Science, the UK Biobank's respondents skew older and may have been describing encounters or behaviors that took place when homosexuality was still illegal and stigma-laden.

Lastly, of course, is the stigma such research could bring about in today's world, where bisexuality is much more accepted than it was in the past but is still very misunderstood and maligned, even in queer communities.

Purdue sociogenomicist Robbee Wedow, who coauthored the 2019 study finding genetic variants associated with homosexuality, went so far as to say that the new research's focus on bisexuality and evolutionary fitness "is not only incorrect, but I would say dangerous."

Zhang, on his end, rejects that characterization outright.

"Many studies that were once considered dangerous propelled the progress of science, technology, and society," the researcher toldScience.

More on queer procreation:Scientists Find Kids With Gay Dads Are Doing Better Than Kids With Straight Dads

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Controversial New Research Find That Bisexuals Are a Bunch of Rascals - Futurism

Genetics

Mayo Clinic Q&A: Weight loss and genetics – Chicago Tribune

DEAR MAYO CLINIC: It seems like no matter what I do, I cant lose weight. Most of my family members struggle with their weight too. Do our genetics play a part in this?

ANSWER: Its important to understand that we are all unique and gain weight for many different reasons. When trying to understand weight gain and why some of us have difficulty losing weight, there are factors such as gut and brain connections, how we control our sensation of hunger and fullness and how long we stay full. Over a decade of studies at Mayo Clinic have helped identify characteristics that can be associated with groups of people called obesity phenotypes.

Each phenotype has a single genetic predisposition (an increased likelihood of developing obesity based on a persons genetic makeup) and interacts differently with their environment. In many environments we see today, there is an excess of food, and were less active than before. Some people may feel hungry between meals, while others only have one big meal a day our genetics drives this. Your genetic makeup determines which phenotype youre going to have. These phenotypes can help guide treatment for weight loss. Each of these genetic phenotypes, or genotypes, identifies the type of obesity and which medication would work best.

The first phenotype is what we call hungry brain. These patients start eating and dont feel full even after consuming large meals with second and third helpings. Usually, this runs in families. The other phenotype is what we call hungry gut. These patients start eating and feel full after their usual portion, but the gut does not send those signals to the brain. Because of that, they feel hungry between meals. Signals from the gut to the brain are hormones, such as glucagon-like peptide-1 (GLP-1). Semaglutide medications such as Wegovy, Ozempic and Rybelsus work on behalf of the GLP-1 hormone. They connect between the gut and the brain, and they signal to the brain that youre full.

Patients who have emotional hunger are another group. Whether having a good or bad day, these patients look to cope with life by eating food. The fourth group is patients with a slow burn or abnormal metabolism where the body does not burn all the calories they consume.

Looking at these four phenotypes can help individualize obesity therapy. How genes correlate with an obesity phenotype can help determine which medications should be prescribed. Each of us also should have a unique diet approach based on our genotype and phenotype. Many diets have mainly focused on obesity-related complications, such as managing Type 2 diabetes or preventing heart risk, but none have been customized to phenotypes. The concept of the phenotype-tailored diet came from multiple studies that showed metabolic benefits during and after the diet plan began. These findings were then matched to each phenotype to define recommended diets.

At Mayo Clinic, we work closely with our colleagues in bariatric surgery through endoscopic procedures to find out, based on our genetics, how we can identify who will be the most responsive to each course of action. We want to bring precision medicine as we have for any other disease, and I think its time we do the same for obesity. Andres Acosta, M.D., Ph.D., Bariatrician, Gastroenterologist, Mayo Clinic, Rochester, Minnesota

(Mayo Clinic Q & A is an educational resource and doesnt replace regular medical care. For more information, visit http://www.mayoclinic.org.)

2024 Mayo Foundation for Medical Education and Research. All rights reserved. Distributed by Tribune Content Agency, LLC.

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Mayo Clinic Q&A: Weight loss and genetics - Chicago Tribune

Genetics

The DNA of privacy and the privacy of DNA – Federal Trade Commission News

Companies selling genetic testing products tout the benefits of DNA-based insights learning more about health, lineage, family tree so that consumers can seek medical attention, customize their diet or exercise regimen, find long-lost relatives, or understand more about their background. But for consumers to realize benefits from DNA-based products or services, consumers need to be able to trust their accuracy and trust that the companys practices related to the DNA of privacy (data minimization, purpose limitations, retention limits, etc.) will protect the privacy of their DNA. Here are some lessons on privacy, data security, truth in advertising, and artificial intelligence (AI) drawn from a trio of FTC enforcement actions involving sellers of genetic testing products: CRI Genetics, 1Health/Vitagene, and Genelink.

Protecting biometric information including genetic data is a top FTC priority. Since announcing itsBiometric Policy Statementin May 2023, the FTC has settled actions against two sellers of direct-to-consumer DNA testing kits. Why are these cases so important? Genetic data reveals sensitive information not only about consumers health, characteristics, and ancestry, but also about their families. While some other data types can be stripped of identifying characteristics, thats not necessarily the case when it comes to genetic information. Where the sensitivity of the data is high, so too is the risk of harm, particularly in this era of increasing biometric surveillance. The FTCs actions in Amazon/Alexa and Ring to protect voice recordings and videos further illustrate this point. To stay on the right side of the law, heed the lessons from these cases.

Secure genetic data. In both 1Health/Vitagene (consumers may know the company as Vitagene) and Genelink, the FTC charged that sellers of genetic-based products had subpar data security. The FTCs Vitagene complaint alleges that the company didnt inventory its genetic data, so it wasnt even aware that it had stored some of it in a cloud storage bucket accessible to the public. In addition, the company allegedly didnt use access controls, didnt encrypt that publicly accessible data, didnt log or monitor access to it, and didnt remedy the problem even after receiving credible warnings. Genelink preceded Vitagene by about nine years and yet there are eerie similarities. According to the Genelink complaint,the company maintained sensitive data in clear text, failed to limit employee and contractor access to sensitive data, failed to assess the risks to that data, and didnt include terms in the contract to require contractors to use safeguards and to allow Genelink to oversee their practices. The data practices described in both complaints are shoddy for any data, but especially for sensitive genetic information, where the risk of harm to consumers from exposure of that data is high. If you collect or store genetic data, youre on notice that the FTC expects security in line with the sensitivity of the data.

Secure customer accounts. Securing genetic data doesnt just mean good network security (although thats a must). It also means securing customer accounts through which a bad actor could access genetic data or other personal information. The more sensitive the data, the more valuable it may be to bad actors which means customer accounts are likely targets for hackers. The Ring matter illustrates that point. According to the complaint, the home security camera company failed to take reasonable steps to secure customer accounts against common hacking techniques, including credential-stuffing attacks. (Credential stuffing involves the use of credentials, such as usernames and passwords, obtained from one breached account to gain access to a consumers other accounts.) The complaint alleges that Ring only used half-measures to prevent these attacks. For example, Ring made multi-factor authentication available to consumers, but didnt require them to use it even though customer accounts were the gateway to highly sensitive information like stored videos and live streams of consumers in private spaces of their homes. If your customer accounts offer data thieves a similar gateway to sensitive data (for example, results from genetic testing), learn from the Ring case and properly secure those accounts.

Dont oversell: Can you support your accuracy claims about genetic testing? Be careful not to exaggerate your claims about your genetic testing product. Theres a line between puffery and deception that you dont want to cross. According to the CRI Genetics complaint, the company among other things overstated the accuracy of their test results (accuracy greater than 99.9%) and falsified reviews. Heres the truth about DNA testing for ancestry: Companies estimate consumers ancestry by comparing consumers DNA with the companies proprietary DNA reference data. Their algorithms predict consumers ancestry, with varying margins of error. DNA testing for ancestry is, therefore at best an estimation of ancestry, not a precise science. The Genelink complaint alleges that the company claimed their genetically customized nutritional supplements could treat diabetes, heart disease, arthritis, insomnia, and other health conditions all without scientific support. When making claims about the accuracy of genetic testing or the purported benefits of DNA-related products, stick with reliable science. If you dont have a reasonable basis to support your claim, dont make it in the first place.

The FTC is watching how companies use and claim to use Artificial Intelligence. DNA algorithms are no exception. Its no secret that the FTC is focused on making sure that consumers can enjoy the benefits of AI without suffering substantial harms like bias, privacy invasions (Amazon/Alexa and Ring), or questionable accuracy (WealthPress, DK Automation, Automators AI). That holds true when it comes to DNA algorithms. In the CRI Genetics matter, the FTC alleged that the patented DNA algorithm the company touted in its ads was not in fact patented and didnt generate the highly accurate results the company claimed. In this age of AI, some companies may be tempted to use loose talk about AI and algorithms, perhaps as a means of conveying technological sophistication. Watch out. If youre promoting your AI or algorithm, make sure your claims dont deceive or otherwise harm consumers.

The FTC has a strong track record of challenging deceptive or unfair dark patterns, including when it comes to obtaining consent for the use and disclosure of genetic data. Recent enforcement actions like Amazon/Prime, Publishers Clearinghouse, and Vonage demonstrate the high priority the FTC places on challenging allegedly illegal dark patterns manipulative designs that coerce consumers into decisions they wouldnt knowingly agree to make. The CRI Genetics matter reinforces this point. According to the complaint, the company used dark patterns confusing pop-ups and directions, bogus rewards, claimed urgency to push consumers into buying more. In the ongoing battle against illegal dark patterns, the orders in both CRI Genetics and Vitagene require the companies to obtain affirmative express consent consent that precludes the use of dark patterns for future uses or disclosures of genetic data. Companies are on notice that they shouldnt be using dark patterns to get consent.

Dont commit a foul when changing the rules of the game. The Vitagene order includes that affirmative express consent requirement because the company had allegedly changed its terms on a key issue but the company didnt get real consent from consumers for this material retroactive change. According to the complaint, changing the rules of the game in the privacy policy was unfair, even though the company hadnt yet implemented the change. The bottom line is that consumers should know what to expect from your data practices. A bait-and-switch approach to collecting personal information (especially genetic data) doesnt fit with the FTC Acts requirements.

Nothing but the truth. According to the FTCs complaint in Vitagene, the company made detailed privacy promises for example, about how it stored genetic data and destroyed genetic samples but didnt deliver on those promises. The company made these promises prominently (a good thing!), including on a page dedicated to genetic privacy. But, according to the complaint, rather than storing genetic data without identifying information, it stored results with names and other personal information. When the time came to delete genetic data, the company couldnt delete it because they didnt even know where some of it was stored meaning that they broke that promise, too. And the company failed to have a process in place through contractual obligations, in particular to ensure that third-party labs destroyed genetic samples after testing. The upshot: If youre selling genetic testing products (or any product, for that matter), you owe consumers nothing less than the truth.

The consequences for ignoring these warnings can be significant. In both recent genetic testing matters, the companies ended up paying substantial financial settlements, either as civil penalties under California state law (CRI Genetics) or for consumers redress (Vitagene). Furthermore, the orders in both cases required the companies to delete or destroy certain valuable biometric data or materials. These remedies were on top of other order provisions, such as prohibitions on misrepresentations, required notice to consumers of the FTCs action, mandates to obtain affirmative express consent for the future use or disclosure of genetic data, and a mandated security program with independent assessments. Its clear that the consequences of non-compliance with the FTC Act and other laws can be significant. Your best bet is to stay on the right side of the law by following these lessons.

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The DNA of privacy and the privacy of DNA - Federal Trade Commission News

Genetics

Development of a human genetics-guided priority score for 19365 genes and 399 drug indications – Nature.com

Plenge, R. M., Scolnick, E. M. & Altshuler, D. Validating therapeutic targets through human genetics. Nat. Rev. Drug Discov. 12, 581594 (2013).

Article CAS PubMed Google Scholar

Cook, D. et al. Lessons learned from the fate of AstraZenecas drug pipeline: a five-dimensional framework. Nat. Rev. Drug Discov. 13, 419431 (2014).

Article CAS PubMed Google Scholar

Dowden, H. & Munro, J. Trends in clinical success rates and therapeutic focus. Nat. Rev. Drug Discov. 18, 495496 (2019).

Article CAS PubMed Google Scholar

Nelson, M. R. et al. The support of human genetic evidence for approved drug indications. Nat. Genet. 47, 856860 (2015).

Article CAS PubMed Google Scholar

Ochoa, D. et al. Human genetics evidence supports two-thirds of the 2021 FDA-approved drugs. Nat. Rev. Drug Discov. 21, 551 (2022).

Article CAS PubMed Google Scholar

King, E. A., Davis, J. W. & Degner, J. F. Are drug targets with genetic support twice as likely to be approved? Revised estimates of the impact of genetic support for drug mechanisms on the probability of drug approval. PLoS Genet. 15, e1008489 (2019).

Article PubMed PubMed Central Google Scholar

Ghoussaini, M., Nelson, M. R. & Dunham, I. Future prospects for human genetics and genomics in drug discovery. Curr. Opin. Struct. Biol. 80, 102568 (2023).

Article CAS PubMed PubMed Central Google Scholar

Fang, H. et al. A genetics-led approach defines the drug target landscape of 30 immune-related traits. Nat. Genet. 51, 10821091 (2019).

Article CAS PubMed PubMed Central Google Scholar

Duffy, A. et al. Tissue-specific genetic features inform prediction of drug side effects in clinical trials. Sci. Adv. 6, eabb6242 (2020).

Article CAS PubMed Google Scholar

Nguyen, P. A., Born, D. A., Deaton, A. M., Nioi, P. & Ward, L. D. Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects. Nat. Commun. 10, 1579 (2019).

Article PubMed PubMed Central Google Scholar

Yao, J., Hurle, M. R., Nelson, M. R. & Agarwal, P. Predicting clinically promising therapeutic hypotheses using tensor factorization. BMC Bioinformatics 20, 69 (2019).

Article PubMed PubMed Central Google Scholar

Han, Y. et al. Empowering the discovery of novel target-disease associations via machine learning approaches in the open targets platform. BMC Bioinformatics 23, 232 (2022).

Article CAS PubMed PubMed Central Google Scholar

Ochoa, D. et al. Open Targets Platform: supporting systematic drug-target identification and prioritisation. Nucleic Acids Res. 49, D1302D1310 (2021).

Article CAS PubMed Google Scholar

Landrum, M. J. et al. ClinVar: improving access to variant interpretations and supporting evidence. Nucleic Acids Res. 46, D1062D1067 (2017).

Article PubMed Central Google Scholar

Cook, C. E. et al. The European Bioinformatics Institute in 2016: data growth and integration. Nucleic Acids Res. 44, D20D26 (2015).

Article PubMed PubMed Central Google Scholar

Stenson, P. D. et al. The Human Gene Mutation Database (HGMD): optimizing its use in a clinical diagnostic or research setting. Hum. Genet. 139, 11971207 (2020).

Article PubMed PubMed Central Google Scholar

Hamosh, A. et al. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucleic Acids Res. 30, 5255 (2002).

Article CAS PubMed PubMed Central Google Scholar

Sveinbjornsson, G. et al. Weighting sequence variants based on their annotation increases power of whole-genome association studies. Nat. Genet. 48, 314317 (2016).

Article CAS PubMed Google Scholar

Karczewski, K. J. et al. Systematic single-variant and gene-based association testing of thousands of phenotypes in 394,841 UK Biobank exomes. Cell Genom. 2, 100168 (2022).

Article CAS PubMed PubMed Central Google Scholar

Pan-UKB team. https://pan.ukbb.broadinstitute.org (2020).

Mountjoy, E. et al. An open approach to systematically prioritize causal variants and genes at all published human GWAS trait-associated loci. Nat. Genet. 53, 15271533 (2021).

Article CAS PubMed PubMed Central Google Scholar

Ferkingstad, E. et al. Large-scale integration of the plasma proteome with genetics and disease. Nat. Genet. 53, 17121721 (2021).

Article CAS PubMed Google Scholar

Denny, J. C. et al. Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data. Nat. Biotechnol. 31, 11021111 (2013).

Article CAS PubMed PubMed Central Google Scholar

Kuhn, M. et al. The SIDER database of drugs and side effects. Nucleic Acids Res. 44, D1075D1079 (2016).

Article CAS PubMed Google Scholar

Hingorani, A. D. et al. Improving the odds of drug development success through human genomics: modelling study. Sci. Rep. 9, 18911 (2019).

Article CAS PubMed PubMed Central Google Scholar

Stein, D. et al. Genome-wide prediction of pathogenic gain- and loss-of-function variants from ensemble learning of a diverse feature set. Preprint at bioRxiv https://doi.org/10.1101/2022.06.08.495288 (2022).

Estrada, K. et al. Identifying therapeutic drug targets using bidirectional effect genes. Nat. Commun. 12, 2224 (2021).

Article CAS PubMed PubMed Central Google Scholar

Chen, B. & Altman, R. B. Opportunities for developing therapies for rare genetic diseases: focus on gain-of-function and allostery. Orphanet J. Rare Dis. 12, 61 (2017).

Article CAS PubMed PubMed Central Google Scholar

Kok, B. P. et al. Discovery of small-molecule enzyme activators by activity-based protein profiling. Nat. Chem. Biol. 16, 9971005 (2020).

Article CAS PubMed PubMed Central Google Scholar

Kobayashi, K. et al. Class B1 GPCR activation by an intracellular agonist. Nature 618, 10851093 (2023).

Article CAS PubMed PubMed Central Google Scholar

Okuyama, R. Chronological analysis of first-in-class drugs approved from 2011 to 2022: their technological trend and origin. Pharmaceutics 15, 1794 (2023).

Article CAS PubMed PubMed Central Google Scholar

Bodenreider, O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res. 32, D267D270 (2004).

Article CAS PubMed PubMed Central Google Scholar

Pendlington, Z. M et al. EBISPOT/EFO-UKB-mappings. GitHub. https://github.com/EBISPOT/EFO-UKB-mappings (2019).

Bento, A. P. et al. The ChEMBL bioactivity database: an update. Nucleic Acids Res. 42, D1083D1090 (2014).

Article CAS PubMed Google Scholar

Wishart, D. S. et al. DrugBank 5.0: a major update to the DrugBank database for 2018. Nucleic Acids Res. 46, D1074D1082 (2018).

Article CAS PubMed Google Scholar

Davies, M. et al. ChEMBL web services: streamlining access to drug discovery data and utilities. Nucleic Acids Res. 43, W612W620 (2015).

Article CAS PubMed PubMed Central Google Scholar

Gaulton, A. et al. The ChEMBL database in 2017. Nucleic Acids Res. 45, D945D954 (2016).

Article PubMed PubMed Central Google Scholar

Santos, R. et al. A comprehensive map of molecular drug targets. Nat. Rev. Drug Discov. 16, 1934 (2017).

Article CAS PubMed Google Scholar

Cunningham, F. et al. Ensembl 2022. Nucleic Acids Res. 50, D988D995 (2021).

Article PubMed Central Google Scholar

Khler, S. et al. The Human Phenotype Ontology in 2021. Nucleic Acids Res. 49, D1207d1217 (2021).

Article PubMed Google Scholar

Kuhn, R. M., Haussler, D. & Kent, W. J. The UCSC genome browser and associated tools. Brief. Bioinform. 14, 144161 (2012).

Article PubMed PubMed Central Google Scholar

Aguet, F. et al. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 13181330 (2020).

Article CAS Google Scholar

Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434443 (2020).

Article CAS PubMed PubMed Central Google Scholar

Stekhoven, D. J. & Bhlmann, P. MissForestnon-parametric missing value imputation for mixed-type data. Bioinformatics 28, 112118 (2011).

Article PubMed Google Scholar

R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2022).

Duffy, A. & Do, R. Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications. Zenodo https://doi.org/10.5281/zenodo.10095684 (2023).

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