UBC family medicine prof resigns, claiming antisemitism in faculty and student body CBC.ca
Here is the original post:
UBC family medicine prof resigns, claiming antisemitism in faculty and student body - CBC.ca
All posts by medical
How to Prioritize Preventative Health Care This Year – University of Colorado Anschutz Medical Campus
The beginning of the year often elevates health-focused resolutions, but one of the most beneficial goals may be one that keeps eluding your calendar: an annual check-up.
Preventative medicine has the ability to help people support their goals of staying healthy and help physicians catch any health concern early so that we can actually do more for them, says Cleveland Piggott, MD, MPH, associate professor of family medicine at the University of Colorado School of Medicine. When we catch illness later in its course, we're often more limited in what we can do.
Preventive health care screenings, vaccinations, and check-ins with a primary physician can save tens of thousands of lives each year, according to the U.S. Centers for Disease Control and Prevention, yet surveys continuously show that many Americans are putting it off.
There are several ways Piggott says people can put their health first this year by keeping up with regular preventative care and prioritizing important conversations with a family doctor.
The COVID-19 pandemic presented a major disruption in preventative health care for many, Piggott says. With the closure of some offices and fear of the coronavirus itself, many canceled or postponed visits, and may still be doing so.
Especially toward the later part of the pandemic phase, we found that people were presenting sicker, and there were illnesses that we could have caught and helped earlier, he says. This lapse in care made some elements of the pandemic worse, as we saw a huge drop off in vaccinations, especially in pediatric populations, for example. People couldnt get the preventative care that they needed to really stave off some of those illnesses.
Now, with more normal health care operations in place, Piggott says its a good time to commit to regular appropriate care, screenings, and vaccinations.
People associate an annual visit with bloodwork and recommended immunizations, but its also about talking through health goals and how we can support patients, especially when there may not be quick fixes, he says. We also try to support people with social determinants of health. That can mean pointing them toward resources if theyre struggling with food or housing insecurity and reminding them about other forms of care, including dental and vision check-ups.
The first step is making an appointment. Piggott recommends setting an annual reminder to schedule a doctors visit to keep from pushing it down the road.
Some of my patients make preventative health care part of their birthday month routine so they dont forget it, he says.
Its also important to pay attention to any reminders or messages coming from a provider. Doctors offices often also keep track of annual reminders.
Preventative health care can help doctors detect disease early, often allowing doctors more treatment and care options.
One example of this is colon cancer, Piggott says. Its generally a slow-growing cancer that, if caught early, has a good prognosis. Another is depression. If you haven't been feeling quite like yourself for a while, physicians have ways to support you, from getting access to a therapist to developing an exercise routine or prescribing necessary medications.
Building a relationship with a primary care doctor can also serve an important role in preventative health. Having a history with a provider can help them know when something is normal or not.
For those new or returning to preventative care this year, Piggott suggests doing some preparation work before the visit. Making a list of questions or concerns can be particularly helpful for both the patient and the doctor.
I think we've all been in moments where we have all these questions we want to talk to someone about and it floats out of our mind right when we are supposed to bring it up, he says.
Additionally, Piggott says to prioritize that list in order of most importance. A doctor may not be able to devote the thoroughness needed to a health concern if there are more than two or three concerns, but is happy to find a time to talk about them at a future visit. It can also be challenging or overwhelming as a patient as too many recommendations or changes from a doctor can be hard to follow through on.
Preventative care check-ins are a great time to learn and ask clarifying questions, especially as evidence and recommendations for screenings can change.
Your provider might not do labs or certain procedures at every preventative visit, for example, because of new evidence informing updated recommendations, Piggott explains. Evidence based preventative care in the context of a relationship with a trusted doctor is an important and often overlooked way to maintain health and improve your quality of life.
See more here:
Column: Improve Medicaid payments for primary care in Virginia – The Virginian-Pilot
An ounce of prevention is worth a pound of cure. Despite this, we spend more than $4 trillion a year (18% of our GDP) on health care treatments with less than 6% of that amount going into primary care, which focuses on prevention of illness. Primary care providers include family physicians, internists, pediatricians, OB-GYN doctors, nurse practitioners and physician assistants that are the first stop for most people accessing our health care system.
Primary care in the United States is under tremendous stress. Office overhead expenses run 60-70%. Insurers require increased documentation in electronic health records and prior authorization requirements are frustrating and time consuming. There is an aging workforce and it is difficult to recruit new physicians into this challenging line of work. Many primary care doctors have retired or left private practice and joined large hospital-based systems.
Virginia expanded Medicaid coverage in 2018. Medicaid now insures nearly 1 in 4 Virginians, dramatically increasing the number of Virginians who have health insurance. There is a little discussed problem with Virginias Medicaid payment system however; the payment amount for services is only 72% of that for Medicare and even less than that compared to private insurance payments. Despite this, 76% of primary care providers continue to see Medicaid patients and 58% are taking new Medicaid beneficiaries.
I learned firsthand the financial problems that result from taking low Medicaid payments as the medical director of two large family medicine residency training practices over 17 years. More than a third of our patients had Medicaid and this percentage increased after Virginias 2018 Medicaid expansion. We continued to see more Medicaid patients who needed comprehensive care, but took significant financial losses for doing so. This led to eliminating essential staff positions, making it much more difficult to continue our mission of providing primary preventive care and treating chronic illnesses.
Many Medicaid patients have more severe chronic illnesses than those with private insurance, and thus it takes longer to see them and provide the complex care that they need. This contributes significantly to the stress of primary care doctors, since they are responsible for the many problems these patients have. Other insurance programs have a system for compensating providers with higher reimbursement for treating those with more severe illness and rewarding higher quality care with better payment. Medicaid has no effective system for doing this; payments remain 72% of the average Medicare reimbursement, despite many previous legislative efforts to get these payments to parity with Medicare.
Gov. Glenn Youngkin recently proposed his $84 billion budget for FY 2024 and has proposed tax cuts as noted by The Virginian-Pilot & Daily Press Editorial Board on Dec. 27 (A tax reform opportunity). There was a massive budget surplus in the last two years and much debate about how that money should be spent on many worthy causes. A compromise between tax cuts and spending in important areas was finally reached between Democrats and Republicans this past summer. This debate will go forward in the 2024 legislative session, which begins on Wednesday.
It would be a huge boost to our primary care workforce if the legislature were to act to provide Medicaid payments for primary care that are equal to those of Medicare. Estimates put the cost of this at $178 million dollars annually, which is only 0.2% of the total annual Virginia budget. Doing this would provide health care security to our less fortunate citizens by ensuring continued access to primary care services. Millions of future health care dollars would be saved by providing prevention and early treatment of chronic disease instead of treating much more expensive advanced illnesses. What could be a better investment in the future health of Virginians?
Dr. Bob Newman is a clinical professor of family medicine at Eastern Virginia Medical School in Norfolk. He is the author of Patients Compass, which is a guide to navigating the U.S. health care system, available online at yourpatientcompass.com.
Read the original post:
Column: Improve Medicaid payments for primary care in Virginia - The Virginian-Pilot
Rural America’s Obstetrical Care Crisis: The Vital Role of Family Physicians – BNN Breaking
Rural Americas Obstetrical Care Crisis: The Vital Role of Family Physicians
In the agricultural heartland of Cairo, Georgia, family physician Zita Magloire is a beacon of hope for pregnant women like Kenadie Evans. In a country grappling with high maternal and infant mortality rates, especially in states like Georgia and Louisiana, Magloire and her dedicated team at Cairo Medical Care deliver hundreds of babies every year. The clinic, nestled across from Archbold Grady Hospital, serves as a lifeline for an agricultural community, offering prenatal care and delivery services in an area where over half of all rural counties lack hospital delivery services.
The closure of many labor and delivery units across rural America is a chilling testament to the myriad challenges these regions face. High costs, declining populations, low Medicaid reimbursements, and staffing shortages have crippled healthcare services, leaving expectant mothers with few options for safe delivery.
In a bid to combat this healthcare void, the Department of Health and Human Services recently announced a substantial investment in rural programs. These include family medicine residencies equipped with obstetrical training, aimed at bolstering the ranks of rural healthcare providers. The American Academy of Family Physicians (AAFP) has found that family practice doctors are a crucial part of rural deliveries, with a recent survey indicating they deliver babies in the majority of rural hospitals.
Nationwide, provider teams are stepping in to keep rural obstetric units active. Federal grants are being utilized to train midwives who can contribute to these teams in rural areas. While family medicine doctors in rural locales face challenges such as low reimbursement, high liability costs, and the risk of burnout from being on call constantly, rural residency training programs are being enhanced to increase the teams of family physicians capable of providing obstetric care. Magloire, a product of rural residency training in Kansas, underscores the importance of family physicians in providing comprehensive care, from pregnancy to a gamut of other health concerns, to the communities they serve.
Read the original:
Rural America's Obstetrical Care Crisis: The Vital Role of Family Physicians - BNN Breaking
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
Follow this link:
Controversial New Research Find That Bisexuals Are a Bunch of Rascals - Futurism
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.
View original post here:
Mayo Clinic Q&A: Weight loss and genetics - Chicago Tribune
Nutrigene Launches Personalised Development Program to Intersect Genetics and Learning through DNA – JCN Newswire
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.
Continue reading here:
The DNA of privacy and the privacy of DNA - Federal Trade Commission News
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).
Originally posted here:
Development of a human genetics-guided priority score for 19365 genes and 399 drug indications - Nature.com