High folic acid supplementation associated with higher rates of COVID-19 infections and mortality

 People in the United Kingdom with folic acid prescriptions were 1.5 times more likely to get COVID-19. They were also 2.6 times more likely to die from COVID-19 compared to the control group. Those are the findings of a new study from UC Davis Health and the University of Alabama at Birmingham.

The research, published in the journal BMJ Open, also found that having a prescription for the antifolate drug methotrexate mitigated the negative impact of folic acid on COVID-19 when folic acid and methotrexate were given together.

The research team studied a large cohort of patients enrolled in the UK BioBank, a major biomedical database containing health information from half a million people.

"We examined whether COVID-19 diagnosis and death were related to the large doses of folic acid -- five times the safe upper limit -- prescribed to patients for a variety of medically approved indications. We found that the risk of becoming infected and dying from COVID-19 was significantly greater in the group treated with folic acid," said Ralph Green, an expert on B vitamins. Green is a distinguished professor in the UC Davis Department of Pathology and Laboratory Medicine and co-senior author of the study.

Folic acid and COVID-19

Folic acid is a synthetic form of vitamin B9, also known as folate. Low levels of B9 are associated with health conditions such as an increased risk of heart disease, stroke and birth defects.

Folic acid is prescribed for several conditions, including sickle cell disease, high-risk pregnancies, and people receiving anti-seizure medications. Folic acid is also prescribed to help offset some side effects for patients taking methotrexate.

Methotrexate is used to treat certain types of cancer and some autoimmune diseases. The drug is an "antifolate," meaning it interferes with folate, which cancer cells require for proliferation.

Green was inspired by research published last year in Nature Communications that suggested the SARS-CoV-2 virus, which causes COVID-19, hijacks the host's folate for viral replication. This suggests that the virus might be sensitive to both folate and folate inhibitors like

To find out if folic acid was associated with an increased risk of COVID-19 and if methotrexate was associated with a decreased risk, the researchers looked at folic acid and methotrexate prescription data from 2019 to 2021 in 380,380 participants in the UK Biobank.

They identified 26,033 individuals with COVID-19, of whom 820 died from COVID-19. People with a methotrexate prescription were diagnosed with COVID-19 at a similar rate to the general study population.

However, people with a folic acid prescription were diagnosed with COVID-19 infections at a higher rate (5.99%) and had a much higher COVID-19 mortality rate (15.97%) than the control group.

"Our findings could have implications for patients who take supplementary folate to prevent complications of other pharmacological therapies," said Angelo L. Gaffo, co-senior author and an associate professor of medicine in the Division of Rheumatology at the University of Alabama at Birmingham. "Although taking folate in these cases is clearly indicated, clinicians should be cautious about excessive folate intake. Of course, our results will require replication."

The researchers note that due to the makeup of the UK BioBank data, the current findings are limited to people 45 years of age and older who are predominantly from White European ethnicities of the UK population.

The study did not look at the serum folate levels of the participants. They note that further investigations are needed to explore the impact of folate status and folic acid intake on susceptibility to SARS-CoV-2 infection and its fatal complications.

"The defined safe upper limit of folic acid is one milligram. Until we have more information, it would be prudent to avoid extremely high doses of folic acid unless it is medically indicated. High folic acid would be of greater concern in unvaccinated individuals," Green said.

Additional co-authors include Ruth K. Topless of University of Otago, Sarah L. Morgan of University of Alabama at Birmingham, Philip C. Robinson of University of Queensland, Tony R. Merriman of the University of Otago and University of Alabama at Birmingham.

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Story Source:

Materials provided by University of California - Davis Health. Original written by Lisa Howard. Note: Content may be edited for style and length.

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Journal Reference:

1. Ruth Topless, Ralph Green, Sarah L Morgan, Philip Robinson, Tony Merriman, Angelo L Gaffo. Folic acid and methotrexate use and their association with COVID-19 diagnosis and mortality: a case–control analysis from the UK Biobank. BMJ Open, 2022; 12 (8): e062945 DOI: 10.1136/bmjopen-2022-062945

https://www.sciencedaily.com/releases/2022/08/220831131158.htm

COVID radar: Genetic sequencing can help predict severity of next variant

 As public health officials around the world contend with the latest surge of the COVID-19 pandemic, researchers at Drexel University have created a computer model that could help them be better prepared for the next one. Using machine learning algorithms, trained to identify correlations between changes in the genetic sequence of the COVID-19 virus and upticks in transmission, hospitalizations and deaths, the model can provide an early warning about the severity of new variants.

More than two years into the pandemic, scientists and public health officials are doing their best to predict how mutations of the SARS-CoV-2 virus are likely to make it more transmissible, evasive to the immune system and likely to cause severe infections. But collecting and analyzing the genetic data to identify new variants -- and linking it to the specific patients who have been sickened by it -- is still an arduous process.

Because of this, most public health projections about new "variants of concern" -- as the World Health Organization categorizes them -- are based on surveillance testing and observation of the regions where they are already spreading.

"The speed with which new variants, like Omicron have made their way around the globe means that by the time public health officials have a good handle on how vulnerable their population might be, the virus has already arrived," said Bahrad A. Sokhansanj, PhD, an assistant research professor in Drexel's College of Engineering who led development of the computer model. "We're trying to give them an early warning system -- like advanced weather modeling for meteorologists -- so they can quickly predict how dangerous a new variant is likely to be -- and prepare accordingly."

The Drexel model, which was recently published in the journal Computers in Biology and Medicine, is driven by a targeted analysis of the genetic sequence of the virus's spike protein -- the part of the virus that allows it to evade the immune system and infect healthy cells, it is also the part known to have mutated most frequently throughout the pandemic -- combined with a mixed effects machine learning analysis of factors such as age, sex and geographic location of COVID patients.

Learning to Find Patterns

The research team used a newly developed machine learning algorithm, called GPBoost, based on methods commonly used by large companies to analyze sales data. Via a textual analysis, the program can quickly home in on the areas of the genetic sequence that are most likely to be linked to changes in the severity of the variant.

It layers these patterns with those that it gleans from a separate perusal of patient metadata (age and sex) and medical outcomes (mild cases, hospitalizations, deaths). The algorithm also accounts for, and attempts to remove, biases due to how different countries collect data. This training process not only allows the program to validate the predictions it has already made about existing variant, but it also prepares the model to make projections when it comes across new mutations in the spike protein. It shows these projections as a range of severity -- from mild cases to hospitalizations and deaths -- depending on the age, or sex of a patient.

"When we get a sequence, we can make a prediction about risk of severe disease from a variant before labs run experiments with animal models or cell culture, or before enough people get sick that you can collect epidemiological data. In other words, our model is more like an early warning system for emerging variants" Sokhansanj said.

Genetic and patient data from the GISAID database -- the largest compendium of information on people who have been infected with the coronavirus -- were used to train the algorithm. Once the algorithms were primed the team used them to make projections about the Omicron subvariants post-BA.1 and BA.2.

"We show that future Omicron subvariants are likelier to cause more severe disease," Sokhansanj said. "Of course, in the real world, that increased disease severity will be mitigated by prior infection by the previous Omicron variants -- this factor is also reflected in the modeling."

Keeping up with Covid

Drexel's targeted approach to predictive modeling of COVID-19 is a crucial development because the massive amount of genetic sequencing data being collected has strained standard analysis methods to extract useful information quickly enough to keep up with the virus's new mutations.

"The amount of spike protein mutations has already been quite substantial and it will likely continue because the virus is encountering hosts that have never been infected before," said Gail Rosen, PhD, a professor in the College of Engineering, who heads Drexel's Ecological and Evolutionary Signal-processing and Informatics Laboratory.

"Some estimates suggest that SARS-CoV-2 has only 'explored' as little as 30-40% of the potential space for spike mutations," she said. "When you consider that each mutation could impact key virus properties, like virulence and immune evasion, it seems vital to be able to quickly identify these variations and understand what they mean for those who are vulnerable to infection."

Rosen's lab has been at the forefront of using algorithms to cut though the noise of genetic sequencing data and identify patterns that are likely to be significant. Early in the pandemic the group was able to track the geographic evolution of new SARS-CoV-2 variants by developing a method for quickly identify and labeling its mutations. Her team has continued to leverage this process to better understand the patterns of the pandemic.

Vision Among Variables

Up until now, scientists have predominantly used genetic sequencing to better identify mutations alongside lab experiments and epidemiological studies. There has been little success in linking specific genetic sequence variations to virality of new variants. The Drexel researchers believe this is due to progressive changes in vaccination and immunity over time, as well as variations in how data is reported in different countries.

"We know that each successive COVID-19 variant thus far has resulted in slightly milder infections because of increases in vaccination, immunity and health care providers having a better understanding of how to treat infections. But what we have discovered through our mixed effects analysis is that this trend does not necessarily hold for each country. This is why our model considers geographic location as one of the variables taken into consideration by the machine learning algorithm," Sokhansanj said.

While disparities and inconsistencies in patient and public health data have been a challenge for public health officials throughout the pandemic, the Drexel model is able to account for this and explain how it affected the algorithm's projections.

"One of our key goals was making sure that the model is explainable, that is, we can tell why it's making the predictions that it's making," Sokhansanj said. "You really want a model that allows you to look under the hood to see, for example, the reasons why its predictions may or may not agree with what biologists understand from lab experiments -- to ensure the predictions are built on the right structure."

A Better View

The team notes that advances like this underscore the need to provide more public health resources to vulnerable areas of the world -- not only for treatment and vaccination, but also for collecting public health data, including sequencing emerging variants.

The researchers are currently using the model to more rigorously analyze the current group of emerging variants that will become dominant after Omicron BA.4 and BA.5.

"The virus can and will continue to surprise us," Sokhansanj said. "We urgently need to expand our global capacity to sequence variants, so that we can analyze the sequences of potentially dangerous variants as soon as they show up -- before they become a worldwide problem."

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Story Source:

Materials provided by Drexel University. Note: Content may be edited for style and length.

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Journal Reference:

1. Bahrad A. Sokhansanj, Gail L. Rosen. Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning. Computers in Biology and Medicine, 2022; 149: 105969 DOI: 10.1016/j.compbiomed.2022.105969

https://www.sciencedaily.com/releases/2022/09/220901135909.htm

In Nordic study, children born after frozen-thawed embryo transfer had higher cancer risk

 A new study of more than 8 million children in Nordic countries suggests the possibility that children born after use of a fertility procedure known as frozen-thawed embryo transfer may have a higher risk of cancer than children born through other means. Nona Sargisian of the University of Gothenburg, Sweden, and colleagues present these findings on September 1 in the open-access journal PLOS Medicine.

Assisted reproductive technology (ART) allows an embryo to be created from a human egg and sperm in a laboratory. A doctor may immediately transfer the embryo to the uterus, or, in a practice that is increasing worldwide, the embryo might be frozen and later thawed before implantation. Prior research suggests that children born after frozen-thawed transfer may have higher short-term risk of certain medical issues than children born after fresh embryo transfer. However, potential long-term medical risks have been less clear.

To boost understanding, Sargisian and colleagues analyzed medical data from 7,944,248 children in Denmark, Finland, Norway, and Sweden. 171,744 were born after the use of ART, and 7,772,474 were conceived spontaneously without the use of assisted reproductive technology. Among those born after the use of ART, 22,630 were born after frozen-thawed transfer.

Statistical analysis of the data from national health registriesshowed that children born after frozen-thawed embryo transfer were at higher risk of cancer than children born after fresh embryo transfer and those without ART. When analyzed as a single group (i.e., those born after frozen-thawed transfer and fresh embryo transfer), however, the use of any type of ART did not have an increased risk of cancer. The most common types of cancer seen in this study were leukemia and tumors of the central nervous system.

The researchers emphasize that their findings should be interpreted with caution, since although the study was large, the number of children born after frozen-thawed embryo transfer who later developed cancer was low (48 cases), which could limit the statistical strength of the analysis.

Nonetheless, the findings may raise concerns about frozen-thawed embryo transfer. Future research will be needed to confirm a possible link between the procedure and increased risk of cancer, as well as any biological mechanisms that may underlie such risk.

Coauthor Ulla-Britt Wennerholm adds, "A higher risk of cancer in children born after frozen-thawed embryo transfer in assisted reproduction, a large study from the Nordic countries found. The individual risk was low, while at a population level it may have an impact due to the huge increase in frozen cycles after assisted reproduction. No increase in cancer was found among children born after assisted reproduction techniques overall."

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Story Source:

Materials provided by PLOS. Note: Content may be edited for style and length.

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Journal Reference:

1. Nona Sargisian, Birgitta Lannering, Max Petzold, Signe Opdahl, Mika Gissler, Anja Pinborg, Anna-Karina Aaris Henningsen, Aila Tiitinen, Liv Bente Romundstad, Anne Lærke Spangmose, Christina Bergh, Ulla-Britt Wennerholm. Cancer in children born after frozen-thawed embryo transfer: A cohort study. PLOS Medicine, 2022; 19 (9): e1004078 DOI: 10.1371/journal.pmed.1004078

https://www.sciencedaily.com/releases/2022/09/220901151601.htm

Former chief Frieden: 3 ways to fix CDC

 The CDC's new plan to accelerate its response to health threats, simplify public messaging and improve data capabilities is a step in the right direction, but more work must be done to address the root cause of the agency's three largest problems: slowness, impracticality and lack of strategic thinking, former CDC director Tom Frieden, MD, wrote in an Aug. 31 piece for The Atlantic.

CDC director Rochelle Walensky, MD, announced the agency's plan for reforms Aug. 17, acknowledging that it had failed to respond effectively to the COVID-19 pandemic. Dr. Frieden said the improvements are greatly needed and long overdue, but fail to acknowledge external factors — such as chronic underfunding and loss of public trust — that will still cause issues even if the CDC's proposed reforms succeed.

He outlined three reforms that could make the CDC more effective at identifying and responding to health threats:

1. Congress should give the CDC a more stable and sufficient budget that includes flexible emergency funding options.

"We spend at least 300 times more on our military defense than we do on our health defense," Dr. Frieden wrote. "Why should the CDC, tasked with the health defense of the nation, be different?"

2. The CDC should "exponentially increase [its] collaboration with state, city and local health departments" to give agency members valuable, hands-on experience before they take on roles at CDC headquarters.

3. Finally, the CDC must work to rebuild trust with the general public. To achieve this goal, the White House and HHS must give the CDC and its experts the freedom to speak directly with the media about current health issues.

Read the full article here.

https://www.beckershospitalreview.com/public-health/former-cdc-chief-3-ways-to-fix-the-agency.html

Hospitals that share public health data will get better Medicare rates

 Hospitals are eligible for increased financial incentives if they share data with public health authorities as part of a new CMS rule, Pew reported Aug. 31.

Under the provision that goes into effect Oct. 1, hospitals taking part in the Medicare Promoting Interoperability Program will avoid cuts in Medicare payments if they electronically report information about patients' illnesses, injuries and care to state or local public health agencies, according to the story.

Pew said the initiative could help with earlier identification of public health threats such as COVID-19 or monkeypox.

With the new rule, hospitals will earn points toward the calculation of Medicare reimbursement rates if they move toward using EHRs to share data with public health departments, sending real clinical information beginning in 2024 and reporting it to CMS, Pew reported.

https://www.beckershospitalreview.com/ehrs/hospitals-that-share-public-health-data-will-get-better-medicare-rates.html

Elizabeth Holmes requests court toss her conviction

 Theranos founder Elizabeth Holmes asked the court to toss her fraud conviction on Thursday in a last-ditch effort to avoid jail time, Bloomberg reported.

Holmes’s lawyer, Amy Saharia, claimed that the 38-year-old did not misrepresent her blood-testing startup Theranos to investors and did not know she was misrepresenting the company, according to Bloomberg.

Saharia also contended that prosecutors did not meet the standard for proving Holmes had criminal intent to commit fraud. Bloomberg noted that asking the court to toss a conviction is a common and often unsuccessful play by those convicted of white-collar crimes.

A federal jury found Holmes guilty of four counts of wire fraud in January. Holmes attracted numerous wealthy individuals to invest in her now defunct company, which claimed to be able to run multiple diagnostic tests with a single drop of blood.

Theranos COO Ramesh “Sunny” Balwani, Holmes’s second-in-command, was convicted of 12 counts of wire fraud in July for defrauding investors and patients, according to the Washington Post. 

https://thehill.com/regulation/court-battles/3624476-theranos-founder-elizabeth-holmes-requests-court-toss-her-conviction/

Poxel: Positive Results from Phase 2 NASH Trial

 

• The Phase 2 trial for the treatment of NASH met its primary efficacy endpoint; PXL065-treated patients achieved statistically significant improvements in the relative decrease in liver fat content measured by magnetic resonance imaging estimated proton density fat fraction (MRI-PDFF) at 36-weeks for all doses.
• Key secondary measures in PXL065-treated patients included a statistically significant improvement in Pro-C3, a biomarker of fibrogenesis.
• PXL065 was observed to be safe and well tolerated with no dose dependent increase in body weight and no increased lower extremity edema vs. placebo. Safety profile is consistent with reduced PPARg-mediated side effects vs. published results of pioglitazone.
• Histology results pending in September, along with the positive initial readout, will inform the next steps of PXL065 in NASH, including the potential for Phase 3 development.

https://www.businesswire.com/news/home/20220829005747/en/Poxel-Announces-Positive-Results-from-Phase-2-NASH-Trial-DESTINY-1-for-PXL065-A-Novel-Proprietary-Deuterium-Stabilized-R-Stereoisomer-of-Pioglitazone