Category: 8. Health

Mouth and tongue lesions are often one of the first symptoms of human immunodeficiency virus (HIV). HIV weakens your immune system, which can leave you susceptible to sores and infections.

If left untreated, oral health issues can cause pain and other health complications.

Aphthous ulcers are small, yellow or gray sores with a red border. They usually appear on the tongue, cheeks, or inside the lips. Mouth ulcers can make talking and eating painful, especially if they’re located under the tongue.

Mouth ulcers are often a symptom of a weak immune system and stress. An estimated 50% of people with HIV experience mouth and tongue ulcers because of their weakened immune systems. Dry mouth caused by HIV and HIV medications can also increase your risk of mouth sores.

Sores will eventually heal on their own. Mild ulcers can be treated with over-the-counter (OTC) numbing creams that help relieve pain and promote healing. More severe sores are treated with prescription corticosteroid mouthwashes or pills.

Oral thrush is a type of yeast infection that causes patches of creamy white or yellow bumps that coat the tongue. These patches can be painless, or they may burn and bleed. Oral thrush can also affect the tonsils, throat, cheeks, gums, and roof of the mouth. 

Oral thrush is the most common mouth infection that affects people living with HIV. It’s normal for yeast (a type of fungus) to live in your mouth. However, if you have a weakened immune system due to HIV, it’s easier for this fungus to grow too much, leading to infection. Because saliva in the mouth has antibodies to fight infections, HIV-related dry mouth also increases your risk of oral thrush.

Prescription antifungal lozenges, pills, or mouthwashes can treat oral thrush. However, oral thrush often returns if your immune system is too weak.

Oral hairy leukoplakia (OHL) causes white, hair-like patches on the sides of the tongue. It can also appear on the insides of the cheeks and lower lip. These patches can be painless or cause mild pain. In more severe cases, you may lose your sense of taste and experience hot and cold sensitivity.

People with Epstein-Barr virus (EBV)—a common herpes virus—can develop oral hairy leukoplakia. EBV typically infects people with extremely weak immune systems, especially those with HIV. EBV infections are also more common in people with untreated HIV.

Oral hairy leukoplakia patches often go away randomly, but there is no cure for the underlying Epstein-Barr virus. Treatment for OHL may include prescription anti-retroviral medications to help reduce patches and lower EBV in your body. Topical solutions, like podophyllin resin and retinoids, can also be applied to the tongue to remove patches. 

Herpes simplex virus type 1 (HSV-1) can cause swollen, painful sores and blisters on the tongue. Blisters are also common on the lips and the roof of the mouth. Herpes blisters start as small clusters of white or yellow fluid-filled bumps that eventually burst into one larger red sore. 

Oral herpes affects nearly 20% of people with HIV. Living with a weak immune system increases your risk of having more oral herpes outbreaks, which can also spread more easily.

Herpes sores are very contagious and can spread from kissing or sharing utensils. There is no cure for oral herpes, but prescription antivirals can help reduce healing time and future outbreaks.

Oral warts look like small, hard, skin-colored bumps or flat, white growths that resemble cauliflower. These painless warts often appear on the tongue, lips, and inside of the mouth. On the tongue, warts usually look gray or white and grow on the sides of the tongue or the lingual frenulum (the fold underneath your tongue).

Oral warts are caused by different strains of the human papillomavirus (HPV). People with HIV are more likely to get HPV infections and oral warts because of their weakened immune system.

People who are aging with HIV or are doing highly active antiretroviral therapy (HAART) are also at an increased risk of oral warts. Oral warts can be removed surgically or frozen off with cryosurgery. However, warts can come back. 

Oral melanin hyperpigmentation looks like flat, brown patches on the tongue, lips, gums, cheeks, or roof of the mouth. This discoloration is caused by increased melanin (skin pigment) in the mouth.

If you have HIV, the antiretroviral therapy (ART) medication Retrovir (zidovudine), also known as AZT, can cause oral hyperpigmentation as a side effect. HIV-related oral hyperpigmentation doesn’t usually cause problems or require treatment. However, if you’re worried about the appearance of hyperpigmentation, talk with your healthcare provider. You may be able to switch to a different ART medication.

Maintaining good oral hygiene can help prevent HIV tongue and mouth conditions. Some dentist-approved tips include:

• Keep your mouth clean: Brush your teeth for two minutes and floss twice daily to remove food, plaque, and harmful bacteria in your mouth. 
• Visit your dentist regularly: See your dentist at least every six months for cleanings. If you don’t have a dentist, ask your healthcare provider or clinic for a referral. 
• Take your HIV medication: It’s important to take antiretroviral therapy medications as directed and on schedule to reduce HIV in your body and help your immune system recover.
• Avoid dry mouth triggers: Limit things that can lead to dry mouth, like smoking tobacco, drinking alcohol, and eating salty foods.
• Stay hydrated: Drink water often, use a humidifier at bedtime, and consider using toothpaste or mouthwash designed to help dry mouth.

If you have HIV, it’s important to see your provider if you experience any changes in your mouth or tongue. Mouth sores, dry mouth, and oral infections are often indicators that HIV is progressing and the immune system is becoming weaker. Some HIV medications can also make dry mouth worse, so your provider may recommend a different treatment.

If left untreated, oral health complications make you more susceptible to bacterial infections and septicemia (blood poisoning), which can be fatal with a weakened immune system. HIV-related tongue ulcers and dry mouth can cause pain that makes it hard to talk, chew, and swallow. Tongue lesions can also wear down taste buds and cause loss of taste.

Other warning signs of HIV progression that warrant a medical visit include:

• Fatigue
• Fever
• Chills
• Sore throat
• Mouth ulcers
• Rash
• Muscle aches
• Swollen lymph nodes
• Night sweats

The HIV Services Locator is a helpful tool to find qualified healthcare providers in your area.

People with HIV are more likely to have ulcers, oral thrush, dark spots, herpes, and warts that affect the tongue and mouth. Because HIV weakens your immune system and can cause dry mouth, oral health conditions are common.

Practicing good oral hygiene, taking your HIV medications, and visiting your dentist regularly are essential to help prevent complications. 

A new study published in PLOS Pathogens reveals how monkeypox virus (MPXV) and its relatives outsmart the body’s early immune defenses. Infectious disease researchers from Wuhan University and the Wuhan Institute of Virology have discovered that a viral protein called OPG147 plays a key role in helping the virus hide from immune detection during the critical first hours of infection.

OPG147 is part of the machinery that allows poxviruses to enter cells, but this study shows it has a second job: disarming the host’s immune alarm system. The research sheds new light on how MPXV and related poxviruses—including vaccinia virus (VACV), used in smallpox vaccines—avoid triggering a strong antiviral response. These findings could help scientists develop better treatments and safer, more effective vaccines.

The disease caused by monkeypox virus is now officially called mpox, following a 2022 renaming by the World Health Organization to reduce stigma and improve public communication. While mpox refers to the illness, monkeypox virus (MPXV) remains the accepted scientific name for the virus itself.

What Is the MITA/STING Pathway—and Why Does It Matter?

Our bodies rely on innate immunity to recognize infections before symptoms even begin. One of the key systems in this early defense is the MITA/STING pathway. When a virus infects a cell and releases its DNA, a sensor called cGAS detects the foreign material and produces a molecule that activates MITA (also called STING, for STimulator of INterferon Genes). This sets off a chain reaction that results in the production of interferons and other antiviral proteins that help control the infection.

In short: MITA/STING is the body’s built-in alarm system for DNA viruses. Without it, the immune system may not respond quickly enough to stop the virus from spreading.

How the Virus Silences the Alarm

The study shows that OPG147 from monkeypox virus—and similar proteins in other poxviruses—can directly interfere with MITA/STING. OPG147 doesn’t block the initial detection of the virus. Instead, it quietly sabotages the steps needed for MITA/STING to activate a full immune response:

• OPG147 blocks a chemical process called ISGylation that helps MITA become fully active.
• It prevents MITA from forming the structures it needs to send out immune signals.
• It traps MITA inside the cell’s endoplasmic reticulum, stopping it from moving to the places where it would normally raise the alarm.

By interfering with these processes, OPG147 allows the virus to establish infection without alerting the immune system right away.

A Weak Spot in the Virus’s Armor

To test how important OPG147 is for the virus, researchers created a mutated version of vaccinia virus where OPG147 could no longer interact with MITA. They found that this altered virus:

• Triggered stronger immune responses in human cells and in mice.
• Produced lower levels of virus in the body.
• Caused milder disease and less tissue damage.
• Did not lose its ability to replicate, meaning the mutation specifically weakens the virus’s ability to evade immunity—not its basic life cycle.

These results show that OPG147 is a key virulence factor—critical for helping the virus cause disease.

Why This Matters for Public Health and National Security

Although mpox is no longer a rare disease, it continues to pose a public health and global security challenge, especially for immunocompromised individuals and in regions with limited access to vaccines and treatments. In addition, orthopoxviruses remain a concern for potential biosecurity threats.

This research identifies OPG147 as a potential weak point that could be targeted by new antiviral drugs or used to develop safer, more effective vaccines. For public health agencies and global health security planners, this study provides valuable insights into how poxviruses evade immune detection—a crucial piece of knowledge for surveillance, outbreak response, and vaccine development.

A New Direction for Vaccine and Antiviral Strategies

What makes OPG147 especially interesting is that it works differently from other known poxvirus immune blockers. While some viral proteins destroy the molecules that signal an immune response, OPG147 directly jams the signaling machinery, making it harder for the immune system to detect the infection in time.

This strategy shows just how sophisticated viruses can be in evading immune defenses—and it suggests that combining treatments that target multiple viral evasion proteins may offer stronger protection.

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Zhou X, Liu Z, Shi W, et al. The conserved poxvirus membrane entry-fusion apparatus component OPG147 targets MITA/STING for immune evasion. PLOS Pathogens. June 11, 2025.

In a recent analysis led by Ryan Hankins, MD, urologist at MedStar Georgetown University Hospital in Washington, DC, researchers explored a compelling new angle on the use of rectal spacers during prostate cancer radiotherapy. While rectal spacers have long been used to reduce rectal toxicity from radiation therapy, emerging evidence suggests their benefits may extend further, including a potential impact on erectile dysfunction (ED) outcomes.

“We use rectal spacers to help prevent [adverse events] from radiation therapy for prostate cancer. The spacers [were] developed to help with rectal toxicity, primarily to prevent rectal toxicity from radiation therapy. We are seeing now that there may be other benefits,” Hankins explains in an interview with Targeted Oncology^TM.

The study utilized a massive dataset drawn from Medicare and included 247,250 patients with prostate cancer who received radiation therapy between 2015 to 2022. Rather than focusing on individual patient-level data, the team opted for a county-level approach to maximize the reach and scale of the study.

“These are large data sets that are readily available, so this is based on diagnoses that are reported, or really government-reported diagnosis codes, and so we can dive into large data sets to see if we can find associations with improvement in these [adverse events],” he shares.

The analysis revealed a notable association: counties with higher utilization of rectal spacers during prostate cancer radiotherapy showed lower rates of ED diagnoses. While the data is observational and further research is needed to confirm causality, the findings point toward a potentially broader protective role for rectal spacers.

REFERENCE:

Hankins RA, Sato R, Mehta P, Bhattacharyya S, Ezekwekwu E, Collins S. Real-world U.S. county-level analysis of erectile dysfunction diagnosis following radiation therapy for localized prostate cancer: The impact of rectal spacer utilization. J Urol. 2025;213(5S):e1327. doi:10.1097/01.JU.0001110184.48142.9e.03

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A breakthrough at the Massachusetts Institute of Technology (MIT) could soon make sophisticated medical diagnostics as cheap and accessible as a blood glucose test. A research team has developed a 50-cent electrochemical sensor that can detect specific disease genes, and crucially, can be stored for up to two months at room temperature.

The technology uses a DNA-coated electrode and leverages a CRISPR-based enzyme, Cas12. When the sensor encounters a target gene from a virus or cancer cell, the enzyme activates and begins to shred the DNA on the electrode. This action creates a distinct electrical signal, confirming a positive result. While promising, a key challenge has been the fragility of the DNA coating, which previously limited the sensors’ shelf-life to only a few days.

The MIT team, led by Professor Ariel Furst, solved this by applying a simple, inexpensive coating of polyvinyl alcohol (PVA), a common polymer. The PVA acts like a protective tarp, stabilizing the delicate DNA and allowing the sensors to be stored and shipped without refrigeration. After two months in storage at temperatures up to 150 °F (65.56 °C), the team confirmed the sensors could still accurately detect a gene associated with prostate cancer.

Our focus is on diagnostics that many people have limited access to, and our goal is to create a point-of-use sensor. People wouldn’t even need to be in a clinic to use it. You could do it at home. — Professor Ariel Furst.

The versatility of the platform means it can be adapted to test for a wide range of infectious diseases, such as HIV and HPV, and various cancers using samples like urine or saliva. A group from Furst’s lab is now launching a startup through MIT’s delta v accelerator to begin testing the durable sensors with patient samples in real-world environments.

Did you know? H. pylori, a bacterium that has infected more than 50% of the global population, is the leading cause of stomach cancer. It is even classified as a Group 1 carcinogen. The good news is H. pylori infection is treatable — and early diagnosis can significantly lower the risk of cancer. NewPos Self-test Kit (curr. $19.99 on Amazon) can help you do just that.

I have always been fascinated by technology and digital devices my entire life and even got addicted to it. I have always marveled at the intricacy of even the simplest digital devices and systems around us. I have been writing and publishing articles online for about 6 years now, just about a year ago, I found myself lost in the marvel of smartphones and laptops we have in our hands every day. I developed a passion for learning about new devices and technologies that come with them and at some point, I asked myself, “Why not get into writing tech articles?” It is useless to say I followed up the idea — it is evident. I am an open-minded individual who derives an infinite amount of joy from researching and discovering new information, I believe there is so much to learn and such a short life to live, so I put my time to good use — learning new things. I am a ‘bookworm’ of the internet and digital devices. When I am not writing, you will find me on my devices still, I do explore and admire the beauty of nature and creatures. I am a fast learner and quickly adapt to changes, always looking forward to new adventures.

According to McGill University, TissueTinker is using 3D bioprinting to revolutionize cancer drug testing by replacing outdated methods like animal trials and 2D cell cultures. Traditional models fail to mimic the complexity of human tumours, contributing to a staggering failure rate—over 90%—for cancer drugs that pass preclinical tests but flop in human trials.

TissueTinker, a recent McGill Innovation Fund (MIF) awardee, tackles this problem head-on. The startup creates miniaturized tumour models using 3D printing technology—specifically, bioink—to replicate both healthy and diseased human tissue side by side. These printed tumours are as small as 300 microns, the “sweet spot size,” according to co-founder Benjamin Ringler. “It’s large enough that it’s still valuable for testing purposes, but small enough to minimize resources.”

More than just small, these tumours are smart. Researchers can customize them to simulate specific tumour environments, gaining targeted insights into cancer behavior. “The ability to customize the tumour really allows researchers to gain deep, targeted insights into how cancer behaves at a micro level,” Ringler explained. This adaptability improves the predictive power of early-stage testing, reducing wasted investment in drugs that would otherwise fail in clinical trials.

“Because the testing environment more readily simulates the human body, researchers can better assess and understand whether or not their drug works before reaching clinical trial stages,” Ringler added. With development costs topping $1–2 billion per drug, this level of precision is not just a scientific advancement—it’s a financial necessity.

TissueTinker is scaling its technology, backed by the McGill Innovation Fund. “The MIF has provided tailored support, offering specific advice and helping us think critically about not just our next step, but our many steps down the road,” said Ringler. Alongside co-founders Madison Santos and Isabelle Dummer—experts in biomedical engineering and cell therapy—the team plans to expand their tumour model library and eventually license the platform.

“We’re not just solving a problem; we’re rethinking the way we approach cancer drug development,” said Ringler.

Thousands of differentially methylated CpGs characterize individual FTLD-TDP pathological subtypes

RRBS was performed to generate DNA methylation profiles from pairs of frozen post-mortem FCX and CER from FTLD-TDP patients (FTLD-TDP types A, B and C, GRN mutation carriers and C9orf72 repeat expansion carriers) and neuropathologically normal controls (Fig. 1A). After QC, 5,819,868 CpGs in FCX and 5,936,364 in CER were included in the analyses. 90% of the total number of retained CpGs overlapped between both tissues, with similar distributions with respects to genomic region, CpG island and regulatory element context (Fig. 1B). Differential methylation analysis was then performed at the CpG site level in both tissues, between each individual pathological subgroup and controls (Supp. Tables 2 and 3). Across all groups, we found 6,453 differentially methylated CpG sites (FDR < 0.05) in FCX and 7,018 in CER. In both brain regions, the majority of differentially methylated CpGs were in a gene body (61.1% in FCX and 54.1% in CER), followed by gene promoters (27.1% in FCX and 34.7% in CER), 3’-UTRs (5.9% in FCX and 4.1% in CER), 5’-UTRs (4.2% in FCX and 5.5% in CER), and a small proportion of intergenic CpGs (1.6% in both FCX and CER; Fig. 1C). In each tissue we found approximately the same number of CpGs to be hypo- and hypermethylated in FTLD-TDP patients, when compared to controls (Fig. 1D). Interestingly, the vast majority of differentially methylated CpGs we identified were unique to a disease subtype, with less than 10% of sites shared between two or more individual patient subgroups in both FCX (381 CpGs representing 6%; Fig. 1E) and CER (424 sites representing 6%; Fig. 1F). Of the overlapping CpGs in FCX, only six were found to be differentially methylated only in genetically unexplained groups of patients (TDP-A, TDP-B and TDP-C), annotated to CDH15, FN3KRP, HS1BP3, CYP2W1, NDUFAF6, TP53INP1 and ZIC3, whereas only two CpGs (within PLCB3 and UBE2A) were found differentially methylated across all pathological subtypes. In CER, no CpG sites were found in common between only genetically unexplained subgroups or all patients. Although we found that CpG positions were not commonly shared between disease groups, we did identify overlaps when analyzing the intersection of annotated genes from all differentially methylated CpGs. We found that 28.2% of genes overlapped between the different groups in FCX (1,327 genes; Supp. Figure 2 A) and 29.4% in CER (1,592 genes; Supp. Figure 2B). In FCX, the largest overlap was observed between TDP-A and all other disease subtypes, the majority being shared with TDP-GRN and TDP-B. Furthermore, we identified 25 genes in FCX and 20 in CER harboring differentially methylated CpG sites only within the sporadic patient groups (none of which was in common between both tissues), and 41 genes in FCX and 16 in CER where differentially methylated CpG sites were found across all patient groups, of which four were detected in both brain regions (HDAC4, PRDM16, PTPRN2 and RASA3, Supp. Tables 2 and 3). When analyzing the genes containing the most differentially methylated CpGs (≥ 5 CpGs) within each pathological subgroup, we found that in FCX, the TDP-A group had the highest number of such genes (N = 16), followed by TDP-GRN (N = 5), TDP-C (N = 5), TDP-B (N = 2) and finally TDP-C9 (N = 1) (Supp. Table 2). In CER however, we found the TDP-C9 group to have the highest number of such genes (N = 12), followed by TDP-A (N = 8), TDP-C (N = 7), and lastly TDP-GRN (N = 1) with none in TDP-B (Supp. Table 3). We next sought to investigate shared epigenetic mechanisms between patients, by combining groups of patients and comparing those to controls (genetically unexplained group ‘ABC’ including TDP-A/B/C and group ‘TDP’ including all TDP patients). We found that group ‘ABC’ only contributed 54 unique CpG sites in FCX and 108 in CER, representing 24 and 58 unique genes in FCX and CER, respectively (Supp. Tables 2 and 3). Group ‘TDP’ further contributed only a few additional unique CpGs with 13 in FCX and 8 in CER, representing 10 unique genes in FCX and 5 in CER, further supporting the specificity of findings to pathological subtypes, rather than shared disease mechanisms (Supp. Tables 2 and 3). Finally, to determine whether our findings are also brain region specific, we compared FCX to CER and found that only 64 CpG sites are common between brain regions across all disease groups (Supp. Tables 2 and 3). In terms of genes harboring differentially methylated CpGs, we also found a limited overlap between tissues, with 406 genes in TDP-A, 141 in TDP-B, 200 in TDP-C, 151 in TDP-GRN and 301 in TDP-C9, supporting the specificity of disease-associated methylation patterns not only to pathological subtypes but also to the brain region.

RRBS identifies differentially methylated CpGs in known FTLD genes

Next, we employed a targeted approach to investigate the presence of differentially methylated CpGs (FDR < 0.05) in both FCX and CER within known FTLD genes [8], including CHCHD10 [55], CHMP2B [56], CSF1R [57], C9orf72 [58, 59], FUS [60], GRN [61, 62], hnRNPA1 [63], hnRNPA2B1 [63], LRRK2 [64], MAPT [65], OPTN [66], SQSTM1 [67], TARDBP [5], TBK1 [66], TIA1 [68], UBQLN2 [69], VCP [70], as well as the recently implicated UNC13A [71,72,73], TNIP1 [73] and ANXA11 [74, 75]. We also included three additional genes previously reported to be differentially methylated in FTLD patients: SERPINA1 specifically in the C9orf72 repeat extension carrier group [76], and NFATC1 and OTUD4 which were reported across different FTLD pathological subtypes [29]. Overall, only few differentially methylated CpGs were found in these genes (Table 2); however, in the case of GRN and C9orf72 the previously identified differentially methylated regions in these genes were poorly covered in our study. Furthermore, and despite none of them overlapping with the previously reported CpG in intron 9, we did find that NFATC1 harbored numerous differentially methylated CpGs across multiple patient subgroups (Supp. Figure 3A). Of the differentially methylated CpGs in NFATC1 that we identified in the FCX, several showed high regulatory potential due to their location within the gene (promoter and both 5’- and 3’-UTRs). Given the previously reported finding that the expression of NFATC1 is increased in FCX from FTLD patients, we investigated NFATC1 expression in our previously generated bulk RNA sequencing dataset [10] and also found higher expression of NFATC1 in FCX from FTLD-TDP patients, when compared to controls (Supp. Figure 3B). We next tested the correlation between methylation levels at each differentially methylated CpG site in FCX and NFATC1 expression, in all FTLD-TDP patients for which both datasets were available, and found that methylation levels at the 5’-UTR CpG negatively correlated with the expression level of NFATC1 (r= -0.29; P = 0.0034; Supp. Figure 3C) suggesting that in addition to the previously reported intronic CpG, this 5’-UTR CpG may also play a role in regulating NFATC1 in FCX.

Promoter level differential methylation analysis identifies 12 promoter loci in FCX and 8 in CER

The single-base resolution of our data allows the investigation of individual CpG sites, much like array-based studies where methylation is profiled at single CpG sites and with only a few sites being profiled per gene; however, CpGs are most often clustered within CpG islands located in genomic areas with likely functional significance. As such, we sought to investigate whether aberrant methylation patterns are observed in CpG islands, in the brain of FTLD-TDP patients. For this, CpG sites were grouped into regions, and differential methylation analysis at the region level was performed. First, we included only loci located within gene promoters (defined by location ± 500 bp from the TSS) and performed differential methylation analysis in FCX and CER separately. We identified 12 differentially methylated regions (DMRs) in FCX and eight in CER, annotated to the promoters of 15 and 13 genes, respectively (Tables 3 and 4). In both tissues, we identified both hypo- and hypermethylated loci (67% hypo- and 33% hypermethylated in FCX; 50% hypo- and 50% hypermethylated in CER). None of the loci overlapped between brain regions and interestingly, promoter DMRs were mostly identified in genetically unexplained FTLD-TDP patients (subtypes TDP-A, TDP-B and TDP-C in FCX; subtype TDP-C in CER). Finally, in FCX only two loci were found in common between patient groups (TRIM34 and LINC01954) whereas in CER no shared loci were identified.

Genome wide region level analysis identifies hundreds of differentially methylated loci in FCX and CER

Next, we expanded our analyses beyond promoters to genome wide level, while still performing group comparisons in each brain region separately. From these analyses we identified hundreds of differentially methylated DMRs, with a total of 131 in FCX and 215 in CER across all patient groups, annotated to 123 and 203 genes, respectively (Fig. 2A and B; Supp. Fig. 4A and B; Supp. Tables 4 and 5). Of these, we found a similar proportion of hyper- and hypomethylated loci in both tissues, with most loci being hypomethylated (Fig. 2C; Supp. Tables 4 and 5). Regarding the genomic context of these loci in both tissues, the overwhelming majority was located within a gene body (75% in FCX and 80% in CER), followed by gene promoters (12% in FCX and 11% in CER), 3’-UTRs (9.5% in FCX and 6% in CER), and a small proportion in intergenic regions (2% in FCX and 1% in CER) and within 5’-UTRs (1.5% in FCX and 2% in CER; Fig. 2D; Supp. Tables 4 and 5). Akin to our findings from the CpG-level analyses, most DMRs are unique to pathological subtypes and thus, combining patient subgroups for analysis only contributed a limited amount of additional DMRs with three in FCX (annotated to PSMA6 in group ABC, and to NDUFA10 and SEMA3C in group TDP) and four in CER (annotated to FHL2, PDGFRA, and BLCAP in group ABC, and DHDDS in group TDP). In FCX, the strongest finding overall was a hypomethylated gene body DMR within GFPT2 (which spans exons 14 and part of the adjacent introns) in several group comparisons (TDP-B, TDP-C, TDP-GRN, group ABC, and group TDP; Supp. Table 4). Interestingly, and although not as strong as in FCX, GFPT2 is one of only five genes where DMRs were found in both FCX and CER (TDP-B; Table 5). We selected this locus to validate our RRBS finding, focusing on TDP-C which showed the strongest effect (logFC= -2.27; FDR = 1.2E-03; Supp. Figure 4C). We selected one highly methylated sample (> 80% methylation), one lowly methylated sample (< 20% methylation), as well as two samples with intermediate methylation per group (N = 4 TDP-C and N = 4 neuropathologically normal controls) based on methylation values across the region, measured by RRBS. Bisulfite sequencing (BS) targeted to the GFPT2 DMR showed at most a 10% difference in methylation level (range 1–10%) as compared to RRBS, with none of the samples changing their categorical classification of high/intermediate/low methylation, providing support and validation to our RRBS findings (Supp. Figure 4D).

Additionally, between the two DMR analyses (promoter and genome-wide), we identified only three loci in common, with one in FCX (overlapping PARVG/PARVB; Table 3 and Supp. Table 4), and two in CER (overlapping DHX33/DHX33-DT and a known CpG island within OTX2/OTX2-AS1; Table 4 and Supp. Table 5).

Finally, we investigated whether an impaired epigenetic machinery could represent a potential mechanism underlying the widespread DNA methylation changes we observed in FTLD-TDP patients. Using our previously generated bulk RNA sequencing dataset [10] we assessed expression levels of a subset of genes encoding for DNA methylation ‘writers’ or methyltransferase enzymes (DNMT1 responsible for methylation maintenance, and DNMT3A/B responsible for de novo methylation), as well as DNA methylation ‘erasers’ (TET1, TET2 and TET3, which are key players in the first step of the demethylation process), in FTLD-TDP patients and neuropathologically normal controls. Results from these analyses highlight expression changes in FCX in genes from both groups of DNA methylation regulators, namely DNMT1 (higher in FTLD-TDP; P = 4E-03) and TET3 (lower in FTLD-TDP: P = 2.7E-05), whereas in CER we found changes in TET1 (lower in FTLD-TDP; P = 1.3E-02) (Supp Fig. 5A). Furthermore, besides global changes across all FTLD-TDP patients, we also observed specific expression patterns of the assessed genes to some pathological subtypes (Supp Fig. 5B), suggesting that to some extent, differential expression of epigenetic machinery components may contribute to the methylation changes we observe with both pathological subtype and brain region specificity.

Enrichment analysis identifies distinct processes in TDP pathological subtypes

To gain insight into potential underlying functions or pathways in genetically unexplained FTLD-TDP patients (sporadic patient groups TDP-A, TDP-B, TDP-C and combined ‘ABC’) where we identified the most changes, we next performed Gene Ontology (GO) analyses focusing on the “Biological Process” (BP) and “Molecular Function” (MF) categories and using the differentially methylated genes from all analysis in each pathological group as input in FCX and CER separately (Supp. Tables 6 and 7). In the BP category, we identified 53 clusters of related terms in FCX and 52 in CER. In the MF category, we identified substantially less clusters with seven in FCX and eight in CER (Supp. Tables 6 and 7).

In the BP category, although we observed overall a large overlap of identified clusters (several related enriched terms that cluster together; Supp. Table 6), the top 3 processes are largely non-overlapping between pathological subtypes as well as tissue types (Fig. 3A). In TDP-A, terms related to nervous system and synapse development and regulation were the most significant in both FCX and CER (cluster 43; top GO term “Nervous system development”; 3.82E-10 in FCX and 7.11E-06 in CER). We further detect enrichment in FCX for terms related to regulation of phosphorylation, glycolysis, and protein modification (cluster 15; top GO term “Protein autophosphorylation”; P = 4.29E-06). Of note, and albeit not in the top 3, we identified two clusters that are not only unique to FCX but also to a specific pathological subtype. These included cluster 2 in TDP-A including terms related to DNA damage repair (top GO term “Recombinational repair”, P = 0.039), and cluster 37 in TDP-B including terms related to cholesterol biosynthesis (top GO term “Regulation of cholesterol biosynthetic process”, P = 0.011) (Supp. Table 6; Supp Fig. 6). In CER from TDP-B, we found the strongest enrichment in terms related to regulation of signaling pathways and transduction (cluster 31, top Go term “Regulation of signal transduction”; P = 6.64E-04). In TDP-C, we found an enrichment in terms related to protein localization and membrane receptor clustering in FCX (cluster 55; top GO term “Protein localization to membrane”; P = 1.01E-04), and to regulation of DNA-templated transcription in CER (cluster 1; top GO term “Positive regulation of transcription by RNA Polymerase II”; P = 2.27E-06). Across all groups in FCX, terms related to ion transport were highly enriched (cluster 51), whereas in the combined ABC group, we detected the strongest enrichment in terms related to protein and histone deubiquitination processes (cluster 52; top GO term “Protein K48-linked deubiquitination”; P = 3.25E-04).

Finally, in the MF category, we observed a large overlap of enriched clusters between pathological subtypes and across tissues (Supp. Tables 6 and 7). Importantly, we found two clusters in common between all TDP subtypes in both brain regions, namely terms related to binding to DNA and transcriptional regulatory regions (cluster 3), as well as ion channel and calcium transporter activity (cluster 13) (Fig. 3B; Supp Fig. 6).

Methylation levels at several DMRs correlate with gene expression levels

Given that altered gene expression is the most common and well-studied consequence of aberrant methylation, we next interrogated our previously generated bulk brain transcriptomic dataset [10] to assess correlations between methylation levels within all DMRs (from both promoter and genome-wide analyses) and the expression of the associated gene(s) for which expression was measured in FCX or CER. When several overlapping DMRs were identified within the same gene, they were merged into one single DMR with the coordinates of the largest region, whereas if several non-overlapping DMRs were identified within the same gene, they were treated as independent DMRs with correlations calculated for each. To increase statistical power, correlations were calculated including all study individuals (ALL; FTLD-TDP and controls combined) (Fig. 4; Supp. Tables 8 and 9). We found correlations between methylation and expression of the annotated gene for nine DMRs in FCX (CCDC169-SOHLH2, CAMTA1, DYSF, ICMT, LINC02139, NDUFA10, PDZD4, SPAG7 and WBP2NL; Fig. 4A) and 14 in CER (ARMC2, ATP2B3, BARHL1, BBS9, CSAG1, DEF8, MTAP, MYO15B, OTX2, PLD5, PLXNA3, PM20D1, PWWP3A and SORCS2; Fig. 4B). Interestingly, for four genes in FCX, we found that the correlations became stronger when including only FTLD-TDP patients, namely CAMTA1, PDZD4, WBP2NL, and DYSF, suggesting that disease environment may play a role in the methylation effect (Supp. Table 8). Next, for each of the 23 genes, we investigated whether differential expression was observed in the pathological subtypes where the DMR was identified, which was the case for nine genes: (i) five in FCX, namely CAMTA1 (lower expression in the TDP-A group; P = 1.9E-10); PDZD4 (lower expression in the TDP-GRN group; P = 4.12E-08); SPAG7 (lower expression in the TDP-GRN group; P = 5.6E-04); NDUFA10 (lower expression in all FTLD-TDP combined; P = 9.6E-04); and WBP2NL (higher expression in the TDP-A group; P = 0.011) (Fig. 5A); and (ii) four in CER, with three in the TDP-C group, namely ATP2B3 (lower expression in TDP-C; P = 5.9E-05); PLD5 and OTX2 (higher expression in TDP-C; P = 4.0E-03 and P = 0.034, respectively), and BBS9 in the TDP-C9 group (higher expression in TDP-C9; P = 2.1E-03) (Fig. 5B). No differential expression was observed for the other genes within the groups where the DMR was identified, compared to controls. In addition, for some genes we observed differential expression in pathological subtypes beyond those where the DMR was identified (Supp. Figure 7), suggesting that additional factors besides DNA methylation may modulate the expression of these genes. One such factor could be altered expression of epigenetic machinery components that regulate transcription via epigenetic modulation. To explore this hypothesis, we investigated whether the expression of a subset of genes encoding for methyl-CpG binding proteins (MBPs; namely MBD1, MBD2, MBD3 and MECP2), which bind to methylated DNA and recruit additional factors to modulate gene expression, was altered in FLTD-TDP patients. Results from these analyses show that in FTLD-TDP patients, MBD2 expression is increased in both FCX and CER (P = 1.6E-02 and P = 3.6E-03, respectively), as well as MBD3 in CER (P = 4.7E-03), as compared to neuropathologically normal controls (Supp Fig. 8), suggesting that differential expression of such components may play a role in the limited correlation between differentially methylated genes and their expression.

CAMTA1 expression is mediated by both methylation changes and TDP-43 levels

Its pivotal role in several processes such as regulating long-term memory [77] as well as neuronal development, maturation and survival [78], together with evidence of being a TDP-43 target [11, 79,80,81], made CAMTA1 an especially interesting and relevant finding in the context of FTLD-TDP pathology. As such, we selected this locus for further follow up. A closer inspection of the 185 bp CAMTA1 DMR revealed that it is located within intron 6 of CAMTA1 (NM_015215) in chromosome 1p36 (Supp Fig. 9A), and harbors several hypomethylated CpGs in the TDP-A group compared to controls (Supp. Figure 9B). First, to validate our CAMTA1 DMR finding, we investigated whether we could detect differential methylation at the CAMTA1 DMR, measured with an alternative technique to RRBS. For this, FCX DNA samples from TDP-A (N = 25) and control (N = 28) individuals overlapping with the RRBS study, were sequenced using ONT long-read sequencing, which also profiles CpG methylation. With ONT long-read sequencing we also confirmed the lower methylation levels in the TDP-A group compared to controls (logFC = -0.366; P = 0.0176; Fig. 6A). Next, also using ONT long-read sequencing, we sought to replicate this finding using an independent cohort of TDP-A (N = 80) and control (N = 22) samples, which corroborated the finding showing a hypomethylated DMR in TDP-A patients compared to controls (logFC = -0.276; P = 0.0363) (Fig. 6B). When combining the discovery and replication cohorts, a similar effect was observed (logFC = -0.27; P = 3.76E-03; Supp Fig. 9C). Next, using ONT sequencing data in the full cohort, we analyzed individual CpG sites within the CAMTA1 DMR to determine the most relevant CpGs driving the hypomethylation signal. We observed lower methylation in the TDP-A group at all CpGs measured in the locus, with CpG numbers 6, 7, 8 and 11 showing the strongest effect (Fig. 6C), suggesting that these sites have the highest predictive value as proxy for the methylation levels within the region. Finally, to confirm previous reports of CAMTA1 being a TDP-43 target, we used an additional transcriptomic dataset from TARDBP KD hiPSC-derived cortical neurons [50], which revealed a positive correlation between the expression of CAMTA1 and TARDBP genes, albeit just below significance using the limited data points available (r = 0.74, P = 0.057; Supp. Figure 9D), suggesting that CAMTA1 is indeed a TDP-43 target. To disentangle the relationship between the effects of TDP-43 dysfunction and methylation on the levels of CAMTA1, we next compared CAMTA1 levels within the group of TDP-A patients using stratification by methylation level, based on RRBS values across the CAMTA1 DMR (N = 20; comparing 10 samples with the highest methylation to 10 samples with the lowest methylation levels). This again showed lower CAMTA1 expression in the lower methylation group compared to the higher methylation group (P = 7.5E-03; Fig. 6D), suggesting that methylation changes at this DMR affect CAMTA1 expression independently and cumulatively to TDP-43 dysfunction.

Aberrant methylation at the CAMTA1 DMR alters expression of additional genes in the 1p36 locus

Mining the UCSC Genome Browser [82] revealed that this intronic DMR, which is not within a known CpG island, overlaps with an open chromatin region (defined by the DNaseI hypersensitivity clusters track from ENCODE V3), as well as several transcription factor binding sites (defined by the Transcription factor ChiP-seq clusters track from ENCODE V3), suggesting a high regulatory potential (Supp. Figure 10). Analyzing additional datasets aimed at profiling genome-wide regulatory elements (Roadmap Epigenomics [83], GeneHancer [84]) further revealed that the DMR overlaps an enhancer element (GH01J006404; GeneHancer) of which CAMTA1 is a predicted target (Supp. Figure 10). Broadening the analysis to the intron that harbors the DMR revealed a region rich in enhancer elements predicted to target several genes within the locus. Specifically in brain tissue [85], evidence supports the existence of enhancer elements in several brain regions predicted to target the neighboring gene VAMP3 (Supp. Figure 10). Given that methylation changes may alter chromatin conformation and thus affect the functioning of regulatory elements, we investigated whether aberrant methylation at the CAMTA1 DMR alters the expression of additional genes in the locus, besides CAMTA1. Testing all genes within 1 MB from the DMR, we found that methylation levels within the region correlate with the expression of VAMP3 (r_TDP = -0.3, P_TDP = 6.2E-03) and PARK7 (r_TDP=0.25, P_TDP=0.022) in FCX; however, only within TDP patients (Supp Table 10; Fig. 7A). When comparing TDP-A to controls, we found that only VAMP3 is differentially expressed in FCX (increased in the TDP-A group; P = 1.1E-03; Fig. 7B; Supp Fig. 11A) and that expression changes are also observed in additional pathological groups (Supp. Figure 11B). Furthermore, when investigating the effect of methylation on gene expression, within TDP-A patients stratified by methylation levels, we found that VAMP3 is differentially expressed between the two groups, with higher VAMP3 expression in the low methylation group (P = 0.015; Fig. 7C). Finally, querying the CLIPdb module of the POSTAR3 database [81] revealed no TDP-43 binding sites within VAMP3 in brain tissue, which is corroborated by our own transcriptomic dataset from TARDBP KD neurons (Supp. Figure 11C), suggesting that VAMP3 is not a TDP-43 target and that expression changes might be, at least in part, modulated by methylation changes at the CAMTA1 DMR. Taking ours and others’ findings together, we propose a working model for the CAMTA1 DMR and locus where on the one hand, in healthy brains, CAMTA1 levels are maintained both via nuclear TDP-43 (i.e. promoting adequate CAMTA1 splicing and expression through direct binding to the 5’-UTR), as well as correct gene body methylation. On the other hand, aggregation and subsequent accumulation of TDP-43 in the cytoplasm leads to TDP-43 loss-of-function and lower TDP-43-dependent CAMTA1 levels. In addition, and independently from TDP-43 dysfunction in TDP-A patients, hypomethylation within the CAMTA1 gene body alters chromatin availability and/or function of regulatory elements in the locus, further reducing CAMTA1 expression while activating nearby genes such as VAMP3. Dysfunction of both CAMTA1- and VAMP3-dependent mechanisms may contribute to neurodegeneration and the pathology observed in TDP-A patients. (Fig. 8).

A study of young people in Hong Kong found that individuals with higher levels of depressive symptoms and those prone to impulsive reactions were slightly more likely to skip breakfast. Breakfast skipping was also associated with anxiety, but the strength of this association was negligible. The research was published in Frontiers in Psychiatry.

Breakfast is the first meal of the day, typically eaten in the morning after a night’s sleep. People around the world eat different foods for breakfast depending on culture, tradition, and availability. In many Western countries, breakfast includes eggs, toast, cereal, fruit, or yogurt. In East Asia, breakfast often consists of rice, soup, pickled vegetables, or steamed buns. Some people prefer a light breakfast like a smoothie or coffee, while others opt for a hearty meal.

Breakfast is considered important because it helps replenish energy and provides essential nutrients after a long overnight fast. Studies have shown that eating breakfast can improve concentration, memory, and academic performance in children. It may also help regulate metabolism and support healthy weight management. Skipping breakfast has been associated with an increased risk of overeating later in the day and poorer overall diet quality. For many, breakfast is also a time to begin the day with a moment of calm or connection with family.

Study author Stephanie Ming Yin Wong and her colleagues aimed to explore patterns of breakfast consumption among youth in Hong Kong and to investigate the associations between breakfast skipping, impulsivity, and symptoms of depression and anxiety.

They analyzed data from the Hong Kong Youth Epidemiological Study of Mental Health (HK-YES), the first territory-wide household-based mental health study in Hong Kong specifically targeting young people aged 15 to 24. Data were collected between 2019 and 2022. Fifty-eight percent of participants were female.

This analysis included data from 3,154 participants, with an average age of 20 years. Participants answered questions about their breakfast habits and completed assessments of impulsivity (using the Barratt Impulsiveness Scale–11), depressive symptoms (Patient Health Questionnaire–9), anxiety symptoms (Generalized Anxiety Disorder Scale–7), and overall functioning (measured by self-reported productivity loss due to mental health problems and an interviewer-rated Social and Occupational Functioning Assessment Scale).

Results showed that 85% of participants consumed breakfast either daily or intermittently, while 15% regularly skipped breakfast. Individuals who skipped breakfast tended to be slightly more impulsive, particularly in terms of attentional control and self-control. They also reported slightly more severe depressive symptoms and marginally higher anxiety symptoms. Compared to peers who ate breakfast, those who skipped it reported just under one additional day of reduced productivity per month and slightly poorer social and occupational functioning.

“Breakfast skipping is associated with elevated depressive symptoms in young people, with impaired attentional control being an important mechanism in this relationship. Encouraging young people to build regular breakfast habits may be incorporated as part of future lifestyle interventions for mental disorders and be further emphasized in public health policies,” the study authors concluded.

The study sheds light on the links between breakfast-related habits and mental health. However, it should be noted that the reported associations were all very weak and detectable only because the sample was very large. Additionally, the study was exclusively conducted on residents of Hong Kong. Results on other cultural groups may differ.

The paper, “Breakfast skipping and depressive symptoms in an epidemiological youth sample in Hong Kong: the mediating role of reduced attentional control,” was authored by Stephanie Ming Yin Wong, Olivia Choi, Yi Nam Suen, Christy Lai Ming Hui, Edwin Ho Ming Lee, Sherry Kit Wa Chan, and Eric Yu Hai Chen.

Neurogenesis — a process whereby new neurons are created — is said to continue throughout one’s life, even as the rate is considered to slow down with age | Image used for representational purpose only
| Photo Credit: Getty Images/iStockphoto

In an interview on vaccine recommendations, health care professionals expressed growing concerns about the changing landscape of medical information dissemination. Laura Knockel, PharmD, BCACP, clinical associate professor at Iowa College of Pharmacy, emphasized the critical importance of relying on professional organizations and trusted health care providers for accurate vaccine information, stressing the rigorous safety testing of vaccines and the potential risks of misinformation. She warned that changes in vaccine recommendations could impact insurance coverage, patient access, and ultimately public health, particularly for vulnerable populations like low-income children. Further, she underscored the need for continued patient education, transparent communication, and a commitment to evidence-based medical guidance in an increasingly complex health care environment.

Drug Topics®: How will the trust of federal health entities be impacted for health care providers?

Laura Knockel, PharmD, BCACP: I think health care providers are going to struggle with where to go for accurate information. The first place we always looked was the CDC and the ACIP pages for that accurate information, but if we think just recently the COVID-19 recommendations changed, it was by done by a couple individuals on a video via a social media post rather than the traditional committee discussion, very transparent decision, and I’m really kind of concerned that that’s going to continue that way. So we need to find where to go to get that actual, accurate information. So I think leaning on professional organizations, the American Academy of Pediatrics [and] Infectious Diseases Society of America, are 2 good examples. A lot of these organizations have started to bulk up their vaccine resources or create specific vaccine resources for their clients, and it does seem to be accessible to the public. There may be some things behind a firewall, but I do think that their concern for getting out that correct, accurate, evidence-based recommendation is overriding their want to have it for their members only. So I really think that’s going to be one of the places that I’m going to lean on are those organizations.

Drug Topics: How can a pharmacist explain these changes to a patient worried about vaccine safety, especially if they heard conflicting messages?

Knockel: I’m encouraging patients to talk to trusted health care professionals and to not get their advice from social media or the internet or other strangers, focusing on the fact that vaccines have been studied before, during, and after FDA approval. I mean, they’re more rigorously tested than any other medications because we give them to healthy people, so we have a very, very low tolerance for risk for adverse events. So just really focusing on the fact that our vaccine safety program in the US is very robust even after FDA approval, and so hopefully that will help override some of the conflicting messages that they may be hearing.

Drug Topics: How do ACIP recommendations affect broader aspects of vaccine access and utilization, such as insurance reimbursement or public health programs?

Knockel: So right now, insurers are required to provide ACIP recommended vaccines at no cost to their patients, but if we narrow or remove a vaccine recommendation, that could lead to patients having to pay out of pocket for vaccines, which can cost hundreds of dollars per vaccine, and if a vaccine isn’t covered by insurance, a patient may be less likely to receive it. So if there’s not that demand from patients to have it, manufacturers may choose to stop making that vaccine, and so there’s just a real, huge vaccine access issue there if they aren’t even making the vaccine anymore, more of a public health look. If we look at Vaccines for Children, or VFC, it’s a federal program that provides free vaccines to low-income, underinsured children, and the ACIP specifically makes recommendations, and they vote on what vaccines should be covered by this VFC program. So if they change their recommendations for that, that’s only going to exacerbate these health inequalities that we have. So those are just 2 examples of putting up barriers to vaccination, when really we should be doing the opposite, making them more accessible and making them more convenient for our patients to receive.

Drug Topics: Is there anything else you would like to add?

Knockel: I guess my one piece would be what’s happening with vaccine policy at the federal level is irresponsible at best, and I would say extremely dangerous at worst, and can be overwhelming, especially when pharmacists have so many other demands on their time to try to keep track of all these updates that keep coming out. It’s almost like drinking from a fire hose, but I really think we need to stay up to date. Focus on educating the public and letting the patient, our patients, know the value of vaccines, and hopefully we can continue to keep our patients healthy.

READ MORE: Immunization Resource Center

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