Categories
Commentary COVID-19

Debunked: RFK Jr. Claims COVID is ‘Ethnically Targeted’

RFK Jr. speaking at press event in NYC. / NYPost

Recent statements from 2024 Democratic presidential candidate Robert F. Kennedy Jr. have drawn great public attention. Speaking at a press event in New York City, he claimed that COVID-19 “disproportionately attacks certain races,” particularly Caucasians and Black people, with Ashkenazi Jews and Chinese being seemingly more immune. Kennedy attributed these disparities to genetic variations of the host cell receptor, ACE2, a key player in the virus’s infectious cycle. He insinuated that this is proof that SARS-CoV-2, the virus that causes COVID-19, was a biological weapon designed to target certain ethnicities. But how sound are these alarming claims?

First, let’s look at the specific study Kennedy linked to on Twitter to validate his claim. The paper investigated the correlation between allele frequencies of certain ACE2 variants and their predicted effects on its ability to bind the SARS-CoV-2 spike protein, a crucial step in the infectious cycle of the virus. For instance, the p.Met383Thr and p.Asp427Tyr variants, which the article alleges are linked to worse COVID outcomes, have frequencies of just 0.003% and 0.01%, respectively. Their rarity suggests that they are unlikely to meaningfully affect large population groups. Not only are these variants incredibly rare, but they are also based on alleles associated with adverse outcomes for SARS-CoV-1, not SARS-CoV-2, the virus causing the COVID-19 pandemic. Hence, the information from this study should not be directly applied to the current pandemic and certainly cannot prove an ethnic targeting of the virus.

Another critical study that disproves Kennedy’s claim revolves around ACE2 variants but examines them in relation to SARS-CoV-2 susceptibility, unlike the former study. Even in this research, the ACE2 variants that could affect susceptibility to SARS-CoV-2 are extremely rare, with maximum prevalence values ranging from 0.00003 to 0.006. For example, an ACE2 variant that was found to increase spike protein binding was found at a frequency of only 3 in 10,000 Latino/Admixed American samples. Consequently, the low occurrence rates of these variants indicates that their impact on broad racial or ethnic groups is statistically insignificant when it comes to widespread racial or ethnic susceptibility.

Upon close examination, it’s clear that Kennedy’s claims lack robust scientific backing. While it’s true that COVID-19 has impacted different communities in different ways, it’s not due to any supposed “genetic targeting” inherent in the virus. Instead, this disparity arises from a multitude of factors, including access to healthcare, occupation types, living conditions, systemic racial disparities in healthcare, and perhaps biological variations unrelated to host cell receptor ACE2.

The assertion that COVID-19 is “ethnically targeted” is not only scientifically unsound but also has the potential to sow confusion and fear among the public. As we continue to grapple with this global health crisis, let’s keep the discourse grounded in verifiable science and promote unity rather than divisive misinformation.

References
  • Hou, Y., Zhao, J., Martin, W., Kallianpur, A., Chung, M. K., Jehi, L., Sharifi, N., Erzurum, S., Eng, C., & Cheng, F. (2020). New insights into genetic susceptibility of COVID-19: An ACE2 and TMPRSS2 polymorphism analysis. BMC Medicine, 18(1), 216. https://doi.org/10.1186/s12916-020-01673-z
  • Levine, J. (2023, July 15). RFK Jr. Says COVID was “ethnically targeted” to spare Jews. New York Post. https://nypost.com/2023/07/15/rfk-jr-says-covid-was-ethnically-targeted-to-spare-jews/
  • MacGowan, S. A., Barton, M. I., Kutuzov, M., Dushek, O., Van Der Merwe, P. A., & Barton, G. J. (2022). Missense variants in human ACE2 strongly affect binding to SARS-CoV-2 Spike providing a mechanism for ACE2 mediated genetic risk in Covid-19: A case study in affinity predictions of interface variants. PLOS Computational Biology, 18(3), e1009922. https://doi.org/10.1371/journal.pcbi.1009922
Categories
Oncology

How AI Is Revealing New Targets for Cancer Drugs

Introduction

Targeted drug therapy has proven to be a highly advantageous approach to cancer treatments, presenting high efficiency and low patient drug resistance. 

Yet, there are drawbacks to the use of targeted drug therapy for cancer, including a lack of identified druggable genomic targets that extend across the patient population. Artificial intelligence algorithms can help researchers better understand carcinogenesis and identify new cancer targets. 

Artificial Intelligence (AI) is a field combining computer science and extensive data sets to perceive, understand, and solve problems.

Two major branches of AI applied biologically are machine learning-based and network-based. Machine learning is an application of AI wherein a computer can learn without direct instruction through mathematical models and pattern recognition. Network-based AI sorts and compares data, providing and compensating different perspectives. 

The Food and Drug Administration (FDA) and the international community have presented an increased interest in trustworthy and ethical AI adoption and innovation.

Applications

The development of multiomics technology is a factor that has bolstered the process of identifying novel anti-cancer targets. Multiomics is an approach to biological analysis that consists of forming data sets out of “omics”, which in the case of cancer are epigenetics, genomics, proteomics, and metabolomics. AI can analyze these data sets to investigate for anti-cancer targets. 

BioRender image by You Et al. Artificial intelligence in cancer target identification and drug discovery. https://doi.org/10.1038/s41392-022-00994-0

Epigenetics

Unlike the changes in the nucleotide sequence characteristic of genetic mutation, epigenetics is similar to an “on-and-off” switch for the expression of specific genetic attributes without altering the genome. Cancer can be caused by both a genetic mutation or an epigenetic signal gone awry. 

A major problem facing epigenetics cancer research is finding specific gene patterns that predict which patients will respond to a cancer treatment. The study of the reversal of epigenetic modifications through AI can give insight into how exactly healthy cells become cancerous and which genetic marker within a patient will respond to cancer-treating drugs.

Genomics

The study of genomics involves the mapping of an entire genome including its structure, function, and evolution, through genome-wide assays such as sequencing. A network-based AI is capable of finding similarities in specific genetic sequences and patterns in their phenotypic expression and interactions. Cancerous biomarkers can be identified through genomic data sets, identifying which genes medical professionals should consider oncogenes of interest.

Proteomics

Proteomics refers to proteins and their interactions within the body. Protein-protein interaction (PPI) research classifies a certain type of protein as “indispensable” and associates them as a major site of disease-causing mutations and drug targeting. In a 2017 study, Ravindran et al. found by analyzing the human PPI data from cancer patients that there are 56 indispensable genes in nine cancers, 46 of which were associated with getting cancer for the first time. This protein interaction data can be harnessed through AI to reveal novel cancer-associated interactions and their potential drug targets. 

Metabolomics

Metabolomics is the study of metabolites: the substrates, intermediates, and products of the human metabolic pathway. A hallmark of cancer cells is that they work to alter these metabolites in order to support their rapid growth, providing energy to their biosynthetic pathways and changing their redox balance. Cancer can be detected through biological AI network analysis due to the presence of certain biomarker metabolites within biofluids, cells, and tissues of the body.

Conclusion

All aforementioned “omics” data can be presented for review in the form of multiomics integration analysis. Varied and interconnected data in a network format allows researchers to study carcinogenesis and drug targeting from an overarching perspective in a multifaceted group of patients. 

While treatment of cancer remains a formidable challenge, rapid technological advances in data collection and analysis through the use of artificial intelligence combined with robust information exchange may prove to be increasingly beneficial to the way cancer drugs are created and tested, leading to potential a safer and healthier world.

References
  • Breakthroughs Staff. (2017, December 12). Treating Cancer by Using Epigenetics, the ‘Software’ of Our Genes | Pfizer. Pfizer News. https://www.pfizer.com/news/articles/treating-cancer-using-epigenetics-%E2%80%98software%E2%80%99-our-genes
  • Guenthoer, J., Lilly, M., Starr, T. N., Dadonaite, B., Lovendahl, K. N., Croft, J. T., Stoddard, C. I., Chohan, V., Ding, S., Ruiz, F., Kopp, M. S., Finzi, A., Bloom, J. D., Chu, H. Y., Lee, K. K., & Overbaugh, J. (2023). Identification of broad, potent antibodies to functionally constrained regions of SARS-CoV-2 spike following a breakthrough infection. Proceedings of the National Academy of Sciences, 120(23), e2220948120. https://doi.org/10.1073/pnas.2220948120
  • Huang, S., Wang, Z., & Zhao, L. (2021). The Crucial Roles of Intermediate Metabolites in Cancer. Cancer Management and Research, 13, 6291–6307. https://doi.org/10.2147/CMAR.S321433
  • Ravindran, V., V., S., & Bagler, G. (2017). Identification of critical regulatory genes in cancer signaling network using controllability analysis. Physica A: Statistical Mechanics and Its Applications, 474, 134–143. https://doi.org/10.1016/j.physa.2017.01.059
  • U.S. Food and Drug Administration. (2022). Using Artificial Intelligence & Machine Learning in the Development of Drug & Biological Products. https://www.fda.gov/media/167973/download
  • You, Y., Lai, X., Pan, Y., Zheng, H., Vera, J., Liu, S., Deng, S., & Zhang, L. (2022). Artificial intelligence in cancer target identification and drug discovery. Signal Transduction and Targeted Therapy, 7(1), Article 1. https://doi.org/10.1038/s41392-022-00994-0
Categories
Public Health

Animal Tranquilizer ‘Xylazine’ Is Making the Fentanyl Crisis Even Worse

In recent years, the devastating impact of the fentanyl crisis has been felt by many Americans. The opioid epidemic, led by this potent synthetic drug, has claimed thousands of lives and shows no signs of abating. But now, a new threat lurks in the shadows, poised to exacerbate an already dire situation — a veterinary sedative known as xylazine.

First synthesized in the 1960s, xylazine is a non-opioid sedative, analgesic, and muscle relaxant used primarily in veterinary medicine for large animals such as horses1. However, it has started to creep into illicit drug markets, often used as an adulterant for opioids like heroin and fentanyl2. The rise of this trend is concerning, and it’s crucial to shed light on this development as it continues to evolve.

Xylazine vial. / Randlab Veterinary Medications
Chemical structure of xylazine. / PubChem

Xylazine, when used in humans, can induce effects similar to those of opioids — a deep sense of relaxation, sedation, and pain relief1. This might explain its allure for those entrenched in substance misuse, but these effects come at a steep price. Unlike traditional opioids, xylazine is not reversed by naloxone (Narcan), the standard emergency treatment for opioid overdoses3. This significantly complicates matters for first responders, who may be unaware that xylazine is present and find that their typical lifesaving interventions are ineffective.

Moreover, xylazine possesses several harmful side effects, including hypotension, bradycardia, respiratory depression, and, in some cases, even death4. Coupled with fentanyl — a substance already notorious for its fatal potency — the presence of xylazine is a ticking time bomb.

The issue of xylazine adulteration in the opioid supply is gaining recognition, yet its severity remains underestimated. According to a 2023 report in the New England Journal of Medicine, xylazine was found in more than 90% of illicit drug samples tested in Philadelphia in 20215. The report found that xylazine is typically found as an adulterant in polydrug mixtures, usually containing simulants like cocaine and amphetamines or opioids like heroin or fentanyl. Alarmingly, the report estimates that the number of xylazine-involved drug-poisoning deaths in the United States increased by 13 times from 2018 to 2021 (an increase from 250 to 3500 deaths).

This rapidly growing and evolving crisis calls for a broad, multi-faceted response involving policymakers, healthcare providers, researchers, and communities. Actions include tightening regulation of veterinary substances, amplifying harm reduction services, and research and development of new overdose drugs that work against xylazine.

The already formidable challenge of the fentanyl and opioid crises is deepened by the introduction of xylazine, adding another lethal layer to the issue. To protect those grappling with substance misuse, it’s crucial to adapt our strategies to this emerging reality. Through a combination of awareness, education, vigilance, and research, we can start to tackle the profound impact of xylazine on the opioid crisis.

References
  1. Ruiz-Colón, K.; Chavez-Arias, C.; Díaz-Alcalá, J. E.; Martínez, M. A. Xylazine Intoxication in Humans and Its Importance as an Emerging Adulterant in Abused Drugs: A Comprehensive Review of the Literature. Forensic Sci. Int. 2014, 240, 1–8. https://doi.org/10.1016/j.forsciint.2014.03.015.
  2. Kacinko, S. L.; Mohr, A. L. A.; Logan, B. K.; Barbieri, E. J. Xylazine: Pharmacology Review and Prevalence and Drug Combinations in Forensic Toxicology Casework. J. Anal. Toxicol. 2022, 46 (8), 911–917. https://doi.org/10.1093/jat/bkac049.
  3. National Institute on Drug Abuse. Xylazine. National Institutes of Health. https://nida.nih.gov/research-topics/xylazine (accessed 2023-05-25).
  4. Andrew McAward. Xylazine, an Emerging Adulterant. American College of Emergency Physicians. https://www.acep.org/talem/newsroom/oct-2021/xylazine-an-emerging-adulterant (accessed 2023-05-25).
  5. Gupta, R.; Holtgrave, D. R.; Ashburn, M. A. Xylazine — Medical and Public Health Imperatives. N. Engl. J. Med. 2023, 0 (0), null. https://doi.org/10.1056/NEJMp2303120.
Categories
Biomedical Research Genetics

First CRISPR-based Gene Therapy Could be Approved in 2023

Photo by Thavis 3D on Unsplash.com

CRISPR-based gene therapies have yet to be approved by the FDA, despite their relative affordability and ease when compared to traditional gene therapies. This may change in 2023, as CRISPR Therapeutics and Vertex Pharmaceuticals announced that their biologics licensing applications (BLAs) to the U.S. Food and Drug Administration (FDA) were completed, including a request for priority review, which would shorten the FDA’s traditional twelve-month review of the application to eight months. This timeline opens the possibility for the first CRISPR gene-edited therapy to be available for interstate commerce within the year.

Background

CRISPR/Cas9 complexes were initially discovered in the natural immune systems of bacteria to protect them from viral invaders. The CRISPR component is a sequence complementary to a specific “target” sequence in a patient’s genome. It is sometimes referred to as the Guide RNA, as it guides the entire complex to the place within the genome where editing will occur. The Cas9 enzyme is the protein commonly depicted as a pair of metaphorical scissors, as it cuts DNA to allow for the insertion/deletion of intended genetic material. In the medical field, CRISPR genetic editing can be harnessed to potentially edit the genomes of individuals affected by currently incurable genetic diseases.

The CRISPR/Cas9 complex binds to and cuts the target sequence. / Javier Zarracina via vox.com

CRISPR/Cas9 is much more accessible than other FDA-approved gene therapies, due to its relative affordability and ease of use. Yet the FDA has shown caution when it comes to its approval. Major limitations of CRISPR-based medicines include:

  • The potential for off-targeting, wherein the complex incorrectly recognizes and binds to a sequence similar to the target sequence.
  • The triggering of the body’s immune response by CRISPR/Cas9, as it originates from bacteria.
  • The multi-faceted ethical concerns that come with genetic editing.

Methods and results

Despite concerns, researchers with CRISPR Therapeutics and Vertex Pharmaceuticals are in the final stages of clinical trials and are up for FDA approval with their CRISPR/Cas9 therapy for genetic blood disorders, called exagamglogene autotemcel (exa-cel).

Patients with sickle cell disease (SCD) and transfusion-dependent beta-thalassemia (TDT) who are participating in these trials have stem cells collected from their own blood. These cells are then edited with CRISPR/Cas9 outside of the body. Once the edited cells are introduced back into the body the patients are treated in accordance with traditional hematopoietic stem cell transplant (HSCT) procedures to establish high levels of fetal hemoglobin (HbF) production. HbF is the protein that carries oxygen throughout the bloodstream during fetal development.

The addition of HbF to a patient with SCD allows for a reduction or potential elimination of vaso-occlusive crises, wherein sickled red blood cells block blood flow to specific tissues, depriving them of oxygen and triggering an extremely painful immune response.

Within patients with TDT, increased levels of HbF reduce or eliminate the life-long dependence on blood transfusions that come with the characteristic severe anemia of the disease.

A doctor drawing blood from a patient. / Nguyen Hiep via Unsplash.com

CRISPR Therapeutics and Vertex Pharmaceuticals are in stage III of clinical trials, assessing both adults and children with SCD/TDT. They presented the adult data from 75 patients (31 with SCD and 44 with TDT) at the European Hematology Association Congress in December 2022.

All of the 31 patients with severe SCD that had been experiencing recurrent vaso-occlusive crises saw an elimination of the crises at their follow-up after exa-cel infusion (follow-up ranging from 2.0 to 32.3 months).

Of the 44 blood-transfusion-dependent patients with TDT, 42 were transfusion-free after exa-cel infusion (follow-up ranging from 1.2 to 37.2 months) and two were at the 75% and 85% marks in transfusion-reduction.

These CRISPR-based therapies show solid potential to change the idea of “incurable” blood diseases.

This research supports the biologics licensing applications (BLA) of CRISPR Therapeutics and Vertex Pharmaceuticals. A BLA is a request to the FDA to introduce a biological product, in this case the exa-cel gene therapy, to the interstate market. Within the BLA, there is a request for Priority Review, which would shorten the FDA’s traditional twelve-month review of the application to eight months, potentially allowing for the first CRISPR gene therapy to be FDA-approved within 2023.

Although the exa-cel CRISPR gene therapy is not approved just yet, it is an exciting innovation for CRISPR research and patients affected by “incurable” genetic diseases.

References
  • Frangoul, H., Altshuler, D., Cappellini, M. D., Chen, Y.-S., Domm, J., Eustace, B. K., Foell, J., de la Fuente, J., Grupp, S., Handgretinger, R., Ho, T. W., Kattamis, A., Kernytsky, A., Lekstrom-Himes, J., Li, A. M., Locatelli, F., Mapara, M. Y., de Montalembert, M., Rondelli, D., … Corbacioglu, S. (2021). CRISPR-Cas9 gene editing for sickle cell disease and β-thalassemia. New England Journal of Medicine, 384(3), 252–260. https://doi.org/10.1056/nejmoa2031054
  • Kingwell, K. (2023, April 3). First CRISPR therapy seeks landmark approval. Nature News. https://www.nature.com/articles/d41573-023-00050-8
  • Ran, F. A., Hsu, P. D., Wright, J., Agarwala, V., Scott, D. A., & Zhang, F. (2013). Genome engineering using the CRISPR-cas9 system. Nature Protocols, 8(11), 2281–2308. https://doi.org/10.1038/nprot.2013.143
  • Vertex and CRISPR therapeutics complete submission of rolling biologics license applications (Blas) to the US FDA for exa-Cel for the treatment of sickle cell disease and transfusion-dependent beta thalassemia. Vertex Pharmaceuticals. (2023, April 3). https://investors.vrtx.com/news-releases/news-release-details/vertex-and-crispr-therapeutics-complete-submission-rolling
  • Vertex and CRISPR therapeutics present new data on more patients with longer follow-up treated with exagamglogene autotemcel (exa-cel) at the 2022 European Hematology Association (EHA) Congress. Vertex Pharmaceuticals. (2022, June 11). https://investors.vrtx.com/news-releases/news-release-details/vertex-and-crispr-therapeutics-present-new-data-more-patients
Categories
COVID-19 Public Health

COVID Disease Severity Lower Than Ever, Most People Infected Unaware of Status

woman blowing nose
Photo by Karolina Grabowska on Pexels.com

As the omicron BA.5 subvariant has become dominant, many countries are heading into their third wave of Omicron cases. Japan reports its largest-ever surge in cases, recording over 200,000 new cases in one day.

Though omicron BA.5 has become the most dominant subvariant of COVID (accounting for 88% of new cases in the US) and is highly contagious, CDC data shows disease severity at its lowest point ever.

Intensive Care Unit (ICU) admission among hospitalized COVID-19 patients. (cdc.gov)

Among hospitalized COVID patients, about 1 in 10 are admitted to the ICU as of July 2022. This figure was as high as 1 in 3 in March 2020, and 1 in 5 as recently as December 2021.

Mortality among hospitalized COVID-19 patients. (cdc.gov)

Similarly, mortality among hospitalized COVID patients has decreased appreciably from 1 in 5 in March 2020 to 1 in 40 in July 2022.

These decreases in COVID disease severity follow the emergence of the omicron variant in November 2021 and its ever-growing share of new infections. The omicron variant, while of high concern and contagion, does not appear to be of proportionally high consequence compared to earlier variants.

The most common symptoms of COVID include cough, fever, and chills. Many report symptoms resembling a common cold with symptoms like upper respiratory congestion. Most people (56%) who are infected with the omicron variant are not aware of their positive status according to a recent Cedars-Sinai study.

Multiple factors could explain omicron’s lower severity, including widespread vaccination or immunity gained from prior exposure and infection. It is also possible that omicron has mutations that decrease severity while favoring infectivity.

Categories
Genetics

Antisense Therapy Explained: How Blocking mRNA Can Treat Genetic Disorders

Photo by Warren Umoh on Unsplash

Antisense therapy has proven to be effective at treating previously untreated genetic disorders including Duchenne muscular dystrophy and familial hypercholesterolemia. The therapy has also demonstrated promising results in Phase III clinical trials for amyotrophic lateral sclerosis (ALS).

What is antisense therapy, and how are antisense oligonucleotides used to treat genetic disorders?

Contents

Background

Genetic Disorders and Proteins

Genetic disorders are diseases caused by abnormal changes in our DNA sequence (mutations). Many diseases have a genetic basis, with mutations either being a direct cause or one of many contributors to a disease’s proliferation.

Some people are born with genetic disorders, acquiring mutations from one or both parents, while others acquire them during their lifetime due to mistakes made by their own cells or exposure to viruses, radiation, or mutagenic chemicals. Most mutations do not result in genetic disorders.

The reason why mutations can affect biological processes is because our DNA provides our cells with the blueprints necessary to build proteins, which are complex molecules responsible for carrying out the chemical reactions that occur within our bodies.

Humans are believed to have 25,000 unique proteins (some copied trillions of times throughout our bodies) that have very specific tasks and functions pertaining to growth, maintenance, structure, metabolism, immune defense, and much more. It follows that a mutation, which creates an error in the genetic instructions to create a specific protein, can have profound impacts on our health.

Genetic disorders that cause the creation of harmful proteins are notoriously difficult to treat. New genes can be introduced into cells to result in the creation of non-mutated proteins, but it is not yet possible to completely stop the production of specific proteins.

This limitation even applies with the recently discovered CRISPR-Cas9 gene editing technology, which can add, remove, inhibit, and activate genes–but not in all cells of the body, meaning some cells will still produce the harmful target protein. Therefore, gene therapy that could inhibit the expression of harmful mutated genes would benefit patients with such disorders.

Antisense Therapy

How It Works

When cells use our DNA’s instructions to build new copies of a protein, it must first be processed into a form that can be read by the ribosome, which is the site of protein synthesis in our cells. Messenger RNA (mRNA) is the final form into which a part of the DNA sequence is processed before the ribosome uses its instructions to build new proteins.

Antisense oligonucleotides (ASOs) are strands of DNA or RNA that are complementary to an mRNA strand that encodes for a mutated protein. Due to this complementary nature, the ASO and the faulty mRNA strand will bind together. This prevents the ribosome from ever translating the specific mutated mRNA strand into the harmful, mutated protein that is the basis of the target genetic disorder.

Implications and Discussion

Many genetic disorders are caused by single mutated proteins that have harmful effects. Some of the most serious neurodegenerative diseases like Alzheimer’s disease, Parkinson’s disease, and amyotrophic lateral sclerosis (ALS) are caused by harmful mutated proteins.

Using ASOs to stop these proteins from being built by our cells can offer significant therapeutic effects in patients with this kind of genetic disorder.

For example, a mutation in the gene that encodes for the huntingtin protein causes the protein to take on an elongated shape. When metabolized, these mutated huntingtin proteins bind together and accumulate into increasingly large deposits in the brain, eventually becoming large enough to affect normal brain function. This is the basis for Huntington’s disease. Using ASOs to decrease expression of the mutated Huntingtin protein could provide therapeutic effects.

Antisense therapies could also treat diseases by inhibiting non-mutant proteins. For hypertriglyceridemia (excess triglycerides), ASOs could be used to inhibit the production of the APOC3 gene which encodes for a protein that regulates triglyceride metabolism.

Certain cancers could also be targeted by ASOs, as they could be used to block the production of proteins that facilitate the growth of a cancerous or precancerous mass of cells.

Solely using the antisense oligonucleotide is around 50% effective at preventing synthesis of a target protein. However, when combined with an enzyme that degrades the complex between the mRNA and ASO, this synthesis-blocking efficacy reaches 95%. This can slow the progression of or provide lasting relief from symptomatic disorder.

Limitations

Antisense therapy can not be used for all genetic disorders. Only those which are caused by a single protein mutated into a harmful form could theoretically be treated by the therapy. Also, stopping the production of an implicated protein could have unexpected side effects due to the discontinuation of normal functions of the protein. In one available ASO therapy, nusinersen (Spinraza), patients experienced varied side effects including increased risk of respiratory infection, congestion, constipation, and stunted growth in children–potentially related to the decreased presence of the target protein.

Another limitation of oligonucleotides is that it is very difficult to deliver them to the interior of our cells. However, surrounding them with fatty particles, like what is used to surround the mRNA in COVID-19 vaccines, can protect them from degradation and help them enter our cells. Though, it can still prove difficult to deliver antisense agents to places like the brain, where a drug must make it through the difficult-to-permeate ‘firewall’ that is the blood-brain barrier. For nusinersen (Spinraza), which has a target protein in the central nervous system, the antisense agent must be injected directly into the spinal canal.

In general, antisense therapy research faces an uphill battle. Since the prospect of using ASOs as drugs was first conceived by Harvard scientists in 1978, less than 10 antisense therapies have been approved by the FDA–the first was approved in 1998. Many antisense therapies have failed in the early phases of clinical trials due to low efficacy. Ionis Pharmaceuticals is the most notable biotechnology company researching antisense therapy, with nine current antisense drug candidates reaching Phase III trials as of June 2022.

Whether ASOs will play a wide role in the treatment of genetic disorders has yet to be determined, though recent innovations in drug delivery systems as well as dozens of such therapies being in advanced clinical trials makes them more promising than ever.

References
Categories
Cardiology

Neural Network Outperforms Physicians at Predicting Cardiac Arrest Risk

Photo by Sander Sammy on Unsplash

Intro

A study published by researchers from Johns Hopkins University highlights new artificial intelligence tools that could help physicians preemptively identify cardiac arrest in patients with the use of artificial intelligence. This new technology could change the way healthcare professionals approach preventative cardiac care, potentially saving patients from fatal outcomes.

Background

Cardiac arrest is one of the leading causes of death, causing hundreds of thousands of deaths per year in the United States. It is caused by a sudden, often arbitrary failure of the heart and can be attributed to factors such as genetics, diet, arrythmia (abnormal heartbeat), and underlying heart problems. They can be the result of chronic cardiovascular conditions but can also occur in healthy individuals. Despite the vast research regarding the disease, scientists are still not completely sure how cardiac arrest arises in patients. Cardiac arrest is nearly impossible to predict with accuracy, making it one of medicine’s deadliest and most confusing conditions.

Currently, physicians determine a patient’s likelihood of cardiac arrest by analyzing their vitals and heart scarring. Testing of vitals entails quantitative analysis of a patient’s blood, including but not limited to cholesterol and sugar levels. Heart scars are tiny marks in the heart which cause cardiovascular disease, and ultimately, cardiac arrest. However, heart scars are incredibly hard to detect because they are microscopic in size. The team of researchers from Johns Hopkins University sought to develop a solution that could accurately predict cardiac arrest risk.

Methods & Results

The team created an artificial intelligence (AI) program built on a neural network that can predict a patient’s probability of developing a cardiac arrest in the next ten years with statistically significant accuracy. The AI program views close-up images of patients’ cardiac tissues, and combined with the patient’s history, determines the probability of a cardiac arrest. The model was able to outperform human predictions of cardiac arrest, and the research team plans to implement the technology as a valuable tool available to physicians.

The research team modeled the AI after a neural network, which is a computer system modeled after the human brain. That is, “neural” pathways are strengthened by successful predictions of correlations in a given data set, enabling computers to make highly accurate predictions of increasingly complex and abstract concepts by applying its knowledge from these data sets.

The AI was programmed to conduct a personalized, patient-specific survival assessment, which analyzes a patients’ underlying conditions and vitals. Next, the team used contrast-enhanced cardiac scar images from and taught the AI to detect aspects of the image that are invisible to the naked eye by using neural network technology. Currently, cardiologists are only able to analyze parts of scar images such as volume, mass, shape, etc. These enhanced images are evaluated by the AI in quantitative ways that human doctors could simply never achieve. The AI was then tested on real patients and data from previous years to see if the neural network could use this data to reliably extrapolate it onto new data.

The researchers found that their algorithm could accurately predict cardiac arrest in real patients to a better extent than physicians. They also tested the AI at 60 different health centers around the US, indicating that this model could be replicated at other hospitals.

Discussion

The researchers concluded that the AI could be of major use to physicians. They plan to continue development of the program for both cardiac arrest and other heart-related diseases. The technology could also improve the accuracy of other diagnostics that rely solely on visual observation. These findings have grand implications on the future of healthcare, indicating a new role of specialized software and artificial intelligence. It may not be long before this novel application of artificial intelligence becomes widespread among physicians, enabling improved patient care by revealing the previously unnoticed.

References
Categories
Commentary Genetics

Dog Behavior Unrelated to Breed? Researchers Respond to Controversy, Misleading Media Coverage

brown and white american pit bull terrier with brown costume
Photo by Gilberto Reyes on Pexels.com

Key Points

– A dog genomics study that found a smaller-than-expected relationship between dog breed and behavior has become widely controversial.
– Critics of the study’s methodology were not satisfied with its rationale for the use of dog-owner surveys to determine behavioral traits due to the possibility of rater bias.
– A well-known psychologist and dog behaviorist believes the study’s data actually proves that breed does, in fact, predict behavior to an appreciable extent–and that the researchers came to an erroneous conclusion.
– Media coverage of the study, even by the journal in which it was published, used absolute language that severely downplayed or outright denied any correlation that was established between breed and behavior.
– The researcher’s most significant finding that distinct genes were associated with individual behavior “at finer resolution than ever before” was largely overlooked.

Contents

Introduction

A recent dog genomics study from UMass Chan School of Medicine researchers claims to challenge popular breed stereotypes, concluding that dog breed is a poor predictor of individual behavior. According to the study, which was the feature article in the April 29 issue of Science, just 9% of variation in dog behavior can be explained by breed.

The study received widespread acclaim, making headlines in publications including The New York Times and The Associated Press. Many dog lovers were pleased with the results that showed a high degree of individuality in dogs. In fact, advocates for pit bull terriers largely rejoiced, as the study seemed to disprove negative stereotypes of the breed that might keep people from adopting them.

The CEO of Best Friends Animal Society said in a press release that “these findings could have far-reaching positive impacts in animal welfare,” and that the study’s findings “could be especially positive for pit bull type dogs, Rottweilers, Dobermans, German Shepherds and Chows, which often have an unfair stigma attached to their breed.”

Headlines of media reports of the study, including those from popular science publications, made generalizing claims that dog behavior is unrelated to breed.

They’re All Good Dogs, and It Has Nothing to Do With Their Breed

The New York Times

Massive study of pet dogs shows breed does not predict behaviour

Nature

Dog Breed Doesn’t Affect Behavior, According to New Genetic Research

Smithsonian Magazine

Even in Science, where the study was published, editors added the following generalization to the summary:

…dog breed is generally a poor predictor of individual behavior and should not be used to inform decisions relating to selection of a pet dog.

Science

While the study did receive positive acclaim, it also provoked significant controversy. Critics called into question the claims of the media as well as the methodology and conclusions of the study. After all, it is widely believed that breed is the most important factor in determining a dog’s behavior and temperament.

Is the criticism justified? Are the media’s generalizing claims supported by the study? First, it is important to understand the methods used by the researchers to come to their conclusion.

OneResearch dives headfirst into the media coverage, methodology, and critiques of the popular study, featuring quotes from an interview with the lead researcher.

Methodology of the Study

To determine whether dog breed could predict behavior, the research team sequenced the DNA of thousands of dogs, including pure-breds and mutts, and surveyed their owners with questions about their pet’s behavior.

The researchers used the survey responses to measure eight factors:

  • Human sociability (less sociable to highly sociable)
  • Arousal level (aroused to composed)
  • Toy-directed motor patterns (toy-directed to not toy-directed)
  • Biddability [responsiveness to human direction] (biddable to independent)
  • Agonistic threshold (assertive to diffident)
  • Dog sociability (less sociable to highly sociable)
  • Environmental engagement (engaged to not engaged)
  • Proximity seeking (affectionate to aloof)

Then, correlations were calculated to determine to what extent breed explains the values of these factors in individual dogs. They also measured physical traits like size, ear shape, and fur length as well as motor pattern behaviors like howling, retrieving, and pointing.

Another aspect of the study, which will be discussed later in this article, sought to link distinct genes with behaviors.

Discussion of Methodology

Rater Bias

Perhaps the most common critique of the study is the use of pet owner surveys to determine dog behavior. Specifically, the possibility of rater bias did not go unnoticed to skeptics of the study.

Voluntary self reporting is unscientific. Anyone who owns a pitbull is going to know the stereotypes and resist them. Questions about aggression they’ll decide to interpret how they want in their responses.

Reddit comment

Of course, nobody would assess the behavior of schoolchildren by asking their mommies, so the whole enterprise strikes me as less than scientific.

Gene Lyons for the Vallejo Times-Herald

Rater bias is addressed within the study. First, the authors claimed that by using mutts and determining their breed composition via DNA sequencing, breed-stereotype biases of surveyed owners should not largely affect the results. This claim was supported by other data within the study which shows that people are inaccurate at guessing the breed composition of mutts. Though, pure-bred dogs were also used in the study.

The authors admit to the limitation that pet owner survey responses “are susceptible to rater bias, including the influence of breed stereotypes.” Also, the authors prefaced findings regarding the relationship between breed and human sociability factor with a disclaimer that owner survey data “may be influenced by breed stereotypes and other factors, and differences are not necessarily genetic in origin.”

Kathleen Morrill, a Ph.D. candidate at UMass Chan Medical School, is the first author of the study. Morrill told OneResearch in a written interview that rater bias “can never be fully mitigated,” elaborating further:

Rather, we expect to overcome noise generated from rater bias by larger and larger samples. Strong effects are the first to appear at any given sample size. Real but small effects become more and more evident and supported at larger sample sizes.

…nor does rater bias need to be fully accounted for us to achieve our initial goal for the project: to genetically map behavioral traits.

Kathleen Morrill for OneResearch

It was not clear how larger samples would decrease the effect of rater bias. When seeking to genetically map behavioral traits, it seems that only traits not affected by rater bias could be reliably mapped.

Survey Validation

Further concerns regarding the survey focused on the validation of the questions for the context of determining large-scale trends in dog behavior and temperament. Readers wondered how they determined which questions to ask, and how accurately those questions could quantify personality traits and behaviors.

In a Reddit AMA (Q&A), Morrill addressed this concern.

Owner surveys are a widely accepted method of assessing a dog’s behavior in its home environment and allow us to achieve the scale necessary to study traits that derive from the interaction of genetics and environment. They are generally considered to be reliable, and previous work comparing survey data and professional assessments confirm this. They are widely used in veterinary medicine. Dog behaviorists will often implement these prior to in-person consultations, because a dog can behave differently in a clinical context.

Kathleen Morrill via Reddit

Though owner surveys are considered to be reliable in the context of veterinary medicine, they may not be as reliable when seeking to determine large-scale, long-term personality and behavioral trends of groups rather than making simple assessments about individuals.

A columnist for the Vallejo Times-Herald was not convinced.

Limiting a behavioral study to suburban backyard behavior tells you very little about what dogs really are.

Gene Lyons for the Vallejo Times-Herald

In terms of deciding which questions to ask, Morrill said that they chose to use previously validated questionnaires, including the Dog Personality Questionnaire (DPQ), Dog Impulsivity Assessment Scale (DIAS), Quality of Life assessment (CHQLS-15), and Canine Cognitive Dysfunction Rating (CCDR). The researchers also used questions added by dog behavior consultants.

The use of such surveys remains controversial in biological and medical research, in general, due to the myriad of biases that can compromise data. These specific surveys were not validated for the novel purpose used in the study. It can’t be determined with the available data whether this affected the results of the study.

Still, survey use is at least insightful as a starting point for generating new hypotheses that can be tested more thoroughly in follow-up validation studies. This is supported by previous use of digital phenotyping in genetic studies of human diseases.

The Dog Personality Questionnaire, developed to assess individual dog’s personality and temperament, is a good starting point for assessing the personality and temperament of individual dogs, as our project sought to do.

Kathleen Morrill for OneResearch

Results & Conclusions of the Study

The study found that for all eight factors, breed explained more of the behavioral variance than size, sex, or age. However, only 3% to 25% of variance in factor scores could be explained by breed, averaging only 9% across all tested factors. The majority of breeds scored within one standard deviation of the average for all behavioral factors, with few breeds over- or underrepresented in the highest-scoring quartiles.

Behavioral factors show high variability within breeds, suggesting that although breed may affect the likelihood of a particular behavior to occur, breed alone is not, contrary to popular belief, informative enough to predict an individual’s disposition.

Morrill et al.

The researchers hypothesized that this surprising conclusion could be due to the lack of breeding for function in favor of appearance during the past few centuries since modern dog breeds were established.

Interestingly, when grouping breeds by their historically given working roles according to characterizations by the American Kennel Club, more behavioral correlations could be drawn. For example, breeds known for herding were found to be more interested in toys, more biddable, more engaged, and more aloof. Working breeds were more dog social. Toy breeds were more independent and less dog social.

Heritability explained more behavioral variance than breed. The authors found that certain behaviors were up to 67% heritable, averaging 25% across behaviors. Motor pattern behaviors like howling, retrieving, and pointing were among the most heritable behaviors, while human sociability was the most heritable factor. 46% of the behavioral questions from the survey could be explained mostly by heritability.

Physical traits were found to be much more heritable than behavioral traits, as most measured physical traits exceeded 85% heritability.

Discussion of Conclusions

Dr. Stanley Coren Article

As quoted above from the study, the authors concluded that even though breed can affect the likelihood of certain behaviors to occur, breed alone does not provide enough information to reliably predict behavior. The study’s conclusion expanded upon past research that noted “mixed consistency” between empirical evidence and widely-recognized breed standards.

A prominent critique of this conclusion was published in Psychology Today by Dr. Stanley Coren, a psychology professor and neuropsychological researcher who is well known for his books about dog behavior.

Dr. Coren alleged that the researchers “misread” their own data. Using the study’s data, he found that breed is a “pretty good” indication of behavioral differences between groups of dogs, but that it is not a guarantee for the behavior of any particular individual.

To support his own conclusion from the data, Dr. Coren mentioned the following statistics from the study’s supplemental materials:

  • 62% of golden retrievers will fall into the highest quartile for human sociability
  • 72% of border collies fall into the top quartile for biddability (responsiveness to human direction)

While Dr. Coren noted that 16% of border collies will actually fall into the lowest quartile for biddability, he said that the data means that your odds are still “better than 4 to 1” that any given border collie will be highly intelligent and trainable. Thus, he believes that breed can, in fact, be a useful indicator of a dog’s behavior for prospective dog owners.

Dr. Jessica Hekman, who co-authored the study, expressed an idea similar to Dr. Coren’s in a statement to the American Kennel Club.

…you’ll definitely improve your chances of getting the right dog for you if you are also thoughtful about what breed you bring home.

Dr. Jessica Hekman for American Kennel Club

Since Dr. Coren concluded from the data that breed can be a useful predictor of a dog’s behavior, why did the study conclude otherwise?

Kathleen Morrill, first author of the study, answered questions from OneResearch about Dr. Coren’s article.

The data [visualization] tool explored by Dr. Coren indeed supports that for assertions of one or two facets of canine behavior, breed can be informative. Though, it depends on the breed and the behavior, as the relationship is far from extensive.

Kathleen Morrill for OneResearch

Morrill then brought attention to a figure in the study that shows instances in which age is “just as informative” as breed. She mentioned how the data shows that the benefits that breed offers when determining behaviors “quickly dissolve given a wider array of behaviors asserted.”

She then invoked an excerpt from the study itself–the first conclusion drawn in the Discussion, which highlights the inconsistency and “modest value” of using breed to predict behaviors in individual dogs. It states that for heritable and more breed-differentiated traits like biddability, breed can make predictions “somewhat more accurate” for purebred dogs. Though, for other factors, like agonistic threshold, they found breed to be “almost uninformative.”

Aggressive Breeds

Internet comments on news websites reporting on the study widely criticized the paper’s conclusion due to their belief that breed strongly determines behavior. Among countless anecdotes, many commentors questioned how the study could find that breed did not explain behavior despite certain breeds dominating the charts for the most bites–implying that these breeds are highly or disproportionately prone to aggression compared to others.

Pit bulls are reportedly the top breed responsible for fatal dog attacks on humans. A 2020 study from a level 1 trauma center also found that for dog bite incidents, pit bulls were much more likely than other breeds to bite without provocation and to go off property to attack. Dog bite data collected by the government of New York City shows that pit bull bites are by far the most commonly reported.

These facts caused internet users to doubt the study’s conclusions that breed can’t predict individual dog’s disposition and that breed did not explain agonistic threshold, which the study’s authors defined as “how easily [a] dog is provoked by a frightening, uncomfortable, or annoying stimulus.”

Dr. Benjamin Hart, animal behaviorist and professor emeritus at the UC Davis School of Veterinary Medicine, told SFGate that pit bulls often show no signs of aggression before an attack.

It’s quite common for a pit bull to show no signs of aggression. People will call it a nice dog, a sweet dog, even the neighbors–and then all of a sudden something triggers the dog, and it attacks a human in a characteristic way of biting and hanging on until a lot of damage is done.

Dr. Benjamin Hart for SFGate

Alarmingly, this means that owner surveys could never indicate the possibility that certain breeds are predisposed to such spontaneous dangerous behaviors. Notably, the researchers did not attempt to account for such behavior.

Morrill said that aggression was not measured because it is not a unitary behavior and can’t be well-defined scientifically, or even colloquially. Also, she explained that agonistic threshold is distinctly a fear response unrelated to predation, meaning spontaneous aggressive behaviors could not have been well accounted for, anyway.

When asked if the study had anything to say about the role of genetics or breed in predatory biting leading to severe or fatal injuries, Morrill responded succinctly, “No.”

Thus, the widely held beliefs regarding dangers of the pit bull terrier cannot be discounted by the study, regardless of conclusions that breed is not usually a reliable indicator of individual behavior.

Discussion of Media Coverage

Best Friends Animal Society Press Release

Best Friends Animal Society, an animal welfare nonprofit, is perhaps the largest advocacy group for stigmatized dog breeds. The nonprofit strongly believes that “all dogs are individuals,” and according to their latest press release, “this study proves it.” BFAS lobbies government bodies to end breed-specific legislation and prevent insurance from denying homeowners coverage due to “dangerous dog” ownership, disgustingly likening this “discrimination” to racism (see: Human races are not like dog breeds: refuting a racist analogy).

They use this study to claim that there is no such thing as a dangerous dog breed in order to support their positions against breed-specific legislation. Importantly for BFAS and its donors, this study should not influence breed-specific legislation.

We did not seek to address the validity of breed-specific legislation and its effectiveness for meeting public health goals to minimize dog bites and attacks on people. We don’t study dangerous interactions or dog bites.

Kathleen Morrill for OneResearch

Morrill did note that the limited predictive value of breed for inferring individual behavior could still have some relevance to breed-specific legislation. Nevertheless, the reason why pit bull terriers attack at much higher rates than other breeds was not elucidated by the study, possibly because it could not be measured using survey-based methodology. Additionally, the basis of the pit bull terrier’s relatively frequent and severe attacks is likely to be independent from the tested personality factors.

It follows that neither supporters nor detractors of breed-specific legislation should look to this study to support their position.

Breed Completely Unrelated to Behavior?

Absolute statements that breed has nothing to do with behavior are widespread across media coverage of the study. As established within the study and this article, this is not the case.

The study itself mentions not only through data but explicitly in the very beginning of the discussion that there is at least a correlation between breed and certain behaviors–but these correlations might not be strong enough to reliably predict behavior from breed. As Dr. Coren pointed out, the data shows that any given border collie has a 4 to 1 chance of scoring high in biddability. Still, as Morrill said, this is a narrow use case for predicting behaviors from breed.

Regardless, the media’s portrayal of the study’s results as showing that breed has no effect on behavior is not supported by the study. Morrill agreed with this in a statement to OneResearch.

Any headline that suggests no effects on behavior would be a misrepresentation. Headlines with scale qualifiers like “little effect” walk the delicate line of nonspecific enough to be technically in line with our findings and attention-grabbing to a large audience, whether they agree with the scale of “little” or not.

Kathleen Morrill for OneResearch

Misleading statements were not limited to headlines, either.

Breed means very little in predicting the behavior and personality of an individual dog, the researchers found. That appears to be especially true for traits that are most commonly associated with a dog’s personality, qualities such as cuddliness, friendliness toward strangers and aggression.

The Washington Post

Of course, aggression was not measured by the study. In fact, the word “aggression” is not written at all in the text.

The summary of the study that appears before its text on Science concludes that “dog breed is generally a poor predictor of individual behavior and should not be used to inform decisions relating to selection of a pet dog.” Dr. Hekman clarified to the Cog Dog Radio podcast that this take was written by Science editors, not the authors of the study.

I don’t want to speak for anybody else but myself, but I disagree with that statement. And I have no power to have it taken down.

Dr. Jessica Hekman for Cog Dog Radio

Media Coverage Overview

Dr. Elinor Karlsson, another key researcher and co-author of the paper, said that she was “for the most part quite happy” with the media coverage. “Our assertion that breed is not a reliable predictor of behavior in dogs was pretty clearly stated in our paper.” Dr. Karlsson clarified that even if breed is not a reliable predictor, there can still be differences between breeds. Also, traits can be heritable without being different between breeds. The study does not say that behavior lacks genetic basis.

Dr. Karlsson said she would expect more behaviorally distinct results from working dogs instead of the pet dogs used in the study, since they were more recently bred for performance rather than aesthetics.

Unfortunately, some sensationalist journalists and special interest groups misrepresented the results of the study to establish a narrative that no dog behaviors can be explained or predicted by breed. Popular science coverage is highly prone to cherry picking of data as journalists offer incomplete evidence to draw conclusions that scientists often don’t have the opportunity to correct or dispute before it’s too late.

The Buried Lede

Morrill expressed similar dismay that publications covering her study did not focus on–or even mention, in most cases–one of her most important findings.

The buried lede of our publication–one which didn’t get nearly as much media attention–is that we do successfully find genes associated with individual behavior, at finer resolution than ever before, largely thanks to all the mixed-breed dogs. 

Kathleen Morrill for OneResearch

The researcher’s ability to pinpoint these genes marks an apparent methodological success that could have implications on the study of human genetics. Improvements in methodology could perhaps reveal more genes associated with distinct individual behaviors.

In human genetics, we are always thinking about genes through the lens of “What goes wrong?”–it’s all very disorder-focused.

Kathleen Morrill for OneResearch

Morrill mentioned how, in laboratory settings, researchers must “break” genes and then measure the behavioral effects in order to understand their functions.

In dog genetics, we gain a new perspective on genetic variation and its behavioral effects, which is often more subtle. In this way, we can learn more about the biological functions of genes and gene regulators.

For example, we map common genetic variation that correlates with howling frequency in dogs. This variation exists nearby a gene that, in people, mutations in the same gene causes developmental disorders. In laboratory animals, mutations in that gene cause defects in the cortical regions of the brain pertaining to speech development. But, in dogs? We might get a better sense for how vocalization varies — it’s less all-or-nothing.

Kathleen Morrill for OneResearch

This finding also has implications on studies of human genetics and subsequent medical applications.

Human susceptibility to neuropsychiatric conditions is shaped by many genes and gene regulators, and large interactive effects of genes, environment, and life experiences. We have a limited understanding of the normal functions of genes that we do find associated with human disorders, and we’re also severely under-equipped to treat and manage neuropsychiatric conditions, like obsessive compulsive disorder or severe agoraphobia, with existing psychotropic medications. Comparative medicine and genomics in dogs has highlighted many genetic contributions to disease already, and will offer the opportunity to treat canine and human disorders in tandem.

Kathleen Morrill for OneResearch
Categories
COVID-19

CRISPR Test Detects All Variants of COVID-19, Could Run on Mobile Phones

close up phography of a grey iphone xi
Photo by Torsten Dettlaff on Pexels.com

During the pandemic, laboratories across the world worked hard to improve current diagnostic testing methods. The main method, quantitative polymerase chain reaction (qPCR) turns a small quantity of DNA into a larger amount and uses fluorescent dyes to indicate the presence or absence of viral genetic material. However, this method falls short in the following ways:

  1. It requires expensive equipment and reagents, along with trained personnel.
  2. It requires temperature cycles, so it cannot be performed at a single temperature.
  3. It takes time. Depending on the initial amount of target present, a qPCR test can take as long as 90 minutes.

At the University of Florida, PhD student Long T. Nguyen, working under Dr. Piyush Jain, has developed a rapid, single temperature COVID-19 diagnostic test that provides results in under 30 minutes. Amazingly, the test distinguishes between five COVID variants, achieves amplification, and RNA to DNA conversion all in one “pot.” Finally, the results can be read on a mobile phone.

The system they used is based on a detection system found in bacteria. Bacteria contain natural immune systems called CRISPR Cas, which function to create both a memory of past viral infections, along with a defense system once these viruses come back. Cas is a protein which is sometimes described as “a pair of molecular scissors,” capable of cutting DNA or RNA fragments, while CRISPR contains complementary sequences to attacking viruses and acts as a “molecular GPS,” helping Cas find a certain target. For this reason, it is also called a Guide RNA.

DNA sequence matching the guide RNA and being cut by a Cas protein into two slices. / Javier Zarracina via vox.com

Some Cas proteins locate their target and only make cuts around the target DNA/RNA; this is called cis cleavage. Others go on a “cutting frenzy.” After finding the target and cutting, the Cas protein starts cutting up other DNA or RNA fragments surrounding it, termed trans cleavage. Cas9 proteins, famous for genetic engineering, employ cis cleavage and only cut DNA. Cas12 and Cas13 proteins utilize trans cleavage, cutting DNA and RNA respectively. All bacteria have adapted their own systems, with slight variations, allowing scientists to harness each’s individual powers.

Cas12 and Cas13 proteins are at the forefront of diagnostic research. Their cutting frenzy may not be great for gene editing, but recent innovation has found that FQ reporters, or fluorescent quenchers, can be used to detect a signal with light. These reporters are dampened by a piece of RNA or DNA located between the fluorescent and quencher. Once cut, they glow and show a light on a fluorescent reader. If a Cas12 or Cas13 protein detects its target, it will cut the target then rapidly start cutting the FQ reporters nearby.

CRISPR RNA, shortened as crRNA, can be “programmed” to target any part of a target sequence. Specifically for the virus that causes COVID-19, there is a highly conserved region called the N gene. Since this same sequence is found across all variants, it can indicate the presence of the virus, but does not distinguish between mutated strains. The Jain lab identified mutated regions on each of the five variants: Alpha, Beta, Gamma, Delta, and Omicron, and created crRNAs which were complementary to each of these mutated regions. 

The N gene encodes for the nucleocapsid region on the COVID-19 virus. It is found in all variants of COVID-19.(Kubina & Dziedzic, 2020)

They then had to choose the optimal Cas protein, which could withstand higher temperatures. This was necessary because amplification occurs at high temperatures, ranging from 55-70°C. BrCas12b comes from a thermophilic bacterium found in hot springs and was the optimal choice.

They combined this Cas protein, along with a crRNA and finally, a master mix of RT-LAMP (Reverse Transcription Loop Mediated Isothermal Amplification). This is a very complex sounding term, but it can be broken down fairly easily. Reverse transcription is the process of converting RNA into DNA. Isothermal means it works at a single temperature and amplification implies the amount of DNA increases greatly. This amplification also provides a checkpoint. Researchers were able to first see if the patient sample was amplified; if so, COVID must be present. Then, using the CRISPR Cas system, they can determine exactly what variant is present. 

Image showing all of the components used in the Jain lab’s one-pot detection. (Nguyen et al., 2022)

Detection is completed in under 30 minutes and patient samples with a higher viral load (i.e., they had more SARS-CoV-2 virions present in their sample), exhibited 100% accuracy with about 95% sensitivity in distinguishing variants. The figure below, from Long et. al shows the incredible accuracy which comes from this detection. The colored titles, “Alpha, Beta, etc.” are the variant present in the patient sample, while the x-axis shows the crRNA used. For instance, it was expected that if a patient contained the Beta strain, only the Beta crRNA would show high signal.

Detection results for variants, showing high sensitivity. (Nguyen et al., 2022)

Most studies combining RT-LAMP with a CRISPR reaction have extremely low sensitivity and difficulty distinguishing a positive sample. The use of specifically BrCas12b, a less studied Cas protein, allowed the Jain lab to circumvent many of the problems others have had combining the two. The applicability of this research extends far beyond COVID-19 detection. Any RNA or DNA detection could be done utilizing this research, simply by changing the sequence located on the crRNA.

Moreover, the Jain lab aims to create portable and cheap methods for testing. They proposed an inexpensive lens which can be attached to any mobile phone camera. In a dark setting, the lens, which costs less than $5 can shine light of a specific wavelength on a sample with the added CRISPR Cas reagent and glow in the presence of COVID-19.

Potential for at-home testing using a specialized lens. Positive samples will glow in the dark once subjected to the light. (Nguyen et al., 2022)
References
  • Kubina, R., & Dziedzic, A. (2020, June 26). Molecular and serological tests for COVID-19. A comparative review of SARS-Cov-2 coronavirus laboratory and point-of-care diagnostics. MDPI. https://doi.org/10.3390/diagnostics10060434
  • Nguyen, L. T., et al. (2022, March 1). A Thermostable Cas12b from Brevibacillus Leverages One-pot Detection of SARS-CoV-2 Variants of Concern. eBioMedicine, The Lancet Discovery Science. https://doi.org/10.1016/j.ebiom.2022.103926
Categories
Neurology

Social Media Use During Pandemic Linked to Increased Tic Severity in Adolescents with Tourette’s

person holding iphone showing social networks folder
Photo by Tracy Le Blanc on Pexels.com

A study being conducted at the University of Florida is investigating a correlation between the use of social media during the COVID-19 pandemic and a change in tic severity for adolescents with Tourette syndrome.

Background

Tourette syndrome is a type of tic syndrome often present at a young age even as early as 2 years old. Tics are sudden movements, jolts, or sounds that those with tic syndromes feel the urge or are compelled to do. Often times it is compared to the urge of a sneeze where the person will feel great discomfort if they do not perform the tic. That being said, tics have the urge to be suppressed but not without causing discomfort to the individual.

Often times, people confuse and associate Tourette’s syndrome with coprolalia. Coprolalia is a specific type of phonic or vocal tic in which people shout obscene language. This specific type of tic is very rare and only affects around 10% of those diagnosed with Tourette’s Syndrome.

Study

After analysis of a patient population of surveys completed by adolescent individuals (n=20) with ages ranging from 11 to 21 years old, the researchers found statistically significant data showing that social media use, and increased social media use during the pandemic, causes an increase in tic severity and frequency.

  • 90% reported using social media more frequently during the pandemic
  • 65% reported using social media for an average of 6 hours per day
  • 50% reported that social media negatively impacted their tics
  • 85% reported that their tic frequencies worsened during the pandemic

This study was recently highlighted by both the University of Florida and the American Academy of Neurology (AAN) for its findings related to the implications of the pandemic on the mental health of adolescents. The researchers plan to add new participants to the study to strengthen the data and gain new insights.

This research is important as it can help to identify possible stressors for those with tics and work towards providing relief from tic symptoms for those with Tourette’s.

This article is based on the following sources

– American Academy of Neurology. (2022, February 28). Study: Tic severity linked with social media use for teens during pandemic. https://www.aan.com/PressRoom/Home/PressRelease/4961
– Centers for Disease Control and Prevention. (2020, May 13). Five Things You May Not Know About Tourette Syndrome. https://www.cdc.gov/ncbddd/tourette/features/tourette-five-things.html
– Mayo Clinic. (2018, August 8). Tourette syndrome – Symptoms and causes. https://www.mayoclinic.org/diseases-conditions/tourette-syndrome/symptoms-causes/syc-20350465
– Tourette Association of America. (2016, May 21). Understanding coprolalia: A misunderstood symptom. https://tourette.org/resource/understanding-coprolalia/
– University of Florida News. (2022, March). Heavy social media use may be linked to increase in tic severity. https://news.ufl.edu/2022/03/social-media-use-and-tic-severity/