Category: 8. Health

Cancer research often reveals unexpected ways to fight disease by rethinking the cell’s environment. A new approach from the University of Cambridge suggests halting glioblastoma, the deadliest brain cancer, by freezing the very molecules that enable its spread.

Instead of killing cells outright, this strategy changes the conditions around them, turning aggressive invaders into quiet neighbors.

Glioblastoma is the most common brain cancer and one of the hardest to treat. Patients often survive less than 15 months after diagnosis, with only 15 percent living beyond five years. Surgery and radiotherapy can slow progress but rarely prevent recurrence.

Cancer cells left behind infiltrate healthy brain tissue, spreading silently through microscopic channels. Current drugs also struggle to penetrate the dense tumor mass, leaving few effective options.

Cancer uses hyaluronic acid

At the heart of this discovery is hyaluronic acid (HA), a sugar-like polymer that shapes much of the brain’s supporting structure.

Cancer cells rely on HA’s flexibility to latch onto surface receptors, especially CD44, which drives their movement. By chemically locking HA in place, scientists stripped away its flexibility. This effectively reprogrammed glioblastoma cells into dormancy, preventing them from invading new tissue.

Study co-author Melinda Duer is a professor in the Yusuf Hamied Department of Chemistry at the University of Cambridge.

“Fundamentally, hyaluronic acid molecules need to be flexible to bind to cancer cell receptors,” said Professor Duer.

“If you can stop hyaluronic acid being flexible, you can stop cancer cells from spreading. The remarkable thing is that we didn’t have to kill the cells – we simply changed their environment, and they gave up trying to escape and invade neighbouring tissue.”

Freezing flexibility stops cancer

The Cambridge study confirmed that HA’s behavior is not just about molecular size but about motion. High-molecular-weight HA, usually linked with healthy tissue, can still promote cancer invasion when diluted.

At lower concentrations, HA molecules move freely, adopting shapes that fit tightly into CD44 binding sites. This triggers powerful invasion signals.

At higher concentrations, HA molecules entangle with each other, limiting flexibility and dampening those signals.

Molecular motion and signals

Nuclear magnetic resonance spectroscopy revealed that HA’s ability to twist into specific conformations within nanoseconds determines whether it binds strongly to CD44.

When flexible, HA activates pathways that push cells to migrate. When immobilized, HA blocks these signals.

This explains why swelling in the brain after surgery, which dilutes HA, can encourage cancer to return at the surgical site.

Protein responses to hyaluronic acid

Proteomic analysis of glioblastoma cells highlighted how HA concentration reshapes their internal machinery.

In flexible environments, cells developed star-shaped structures and invasive protrusions, supported by actin-bundling proteins and enzymes that degrade tissue.

In stiffer environments, those invasive proteins disappeared. Instead, cells activated survival pathways, entered a dormant state, and upregulated proteins linked to quiescence, including Notch-2.

This switch showed how extracellular conditions can push cancer cells either into attack mode or into stillness.

Freezing molecules stops cancer

Researchers tested this idea further by creating a chemically modified HA that crosslinks tightly into the extracellular matrix. This version lost flexibility and, when added to cell cultures, completely stopped invasion.

Cells responded in the same way as in dense HA conditions, showing altered protein expression and increased dormancy signals. This provided strong evidence that flexibility itself, not size, is the decisive factor in driving cancer spread.

The findings give a new explanation for glioblastoma’s notorious tendency to regrow after surgery. Fluid build-up, or oedema, dilutes HA at the surgical site, making it more flexible and more capable of binding CD44.

This diluted environment inadvertently encourages cancer cells to invade again. By freezing HA in place, scientists hope to counteract this effect and stop recurrence before it starts.

Freezing may help treat cancer

“This could be a real opportunity to slow glioblastoma progression,” said Duer. “And because our approach doesn’t require drugs to enter every single cancer cell, it could in principle work for many solid tumours where the surrounding matrix drives invasion.

“Cancer cells behave the way they do in part because of their environment. If you change their environment, you can change the cells.”

The work now moves into animal testing before any patient trials. Still, the implications extend beyond brain cancer. Many tumors rely on signals from their surrounding environment to spread.

By targeting flexibility in key molecules like HA, researchers may uncover a new class of treatments that turn cancer’s supportive scaffolding into a trap. Instead of chasing runaway cells, this method locks the very ground beneath them.

The study is published in the journal Royal Society Open Science.

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• New research suggests not all plant-based diets are healthy.
• Some plant-based diets may be bad for heart health.
• Experts suggest focusing on certain elements when eating a plant-based diet.

Many medical organizations recommend following a plant-forward diet, but new research points out that all plant-based foods are not created equal. In fact, some may even be bad for your heart health.

The study, which was published in the American Journal of Preventive Cardiology, found a clear link between eating an unhealthy plant-based diet and a key biomarker linked to having a heart attack. For the study, researchers analyzed data from more than 7,700 people who participated in the 1999-2004 National Health and Nutrition Examination Survey (NHANES). (Yes, that’s data from more than 20 years ago—but experts say the findings still apply.) All of the participants were at least 20 years old and had no history of heart disease at the start of the study.

During the study period, the participants reported what they ate over a 24-hour period and gave blood samples to allow the researchers to look for biomarkers of heart disease. The researchers discovered that people who followed a healthy plant-based diet had a 49% lower risk of having higher levels of cardiac troponin I. (Cardiac troponin I is a sign of cardiac muscle damage and is linked to heart attack risk.)

C. elegans strains

C. elegans strains were cultured at 20 °C on standard Nematode Growth Medium seeded with OP50 Escherichia coli⁷⁰. On day 1 of adulthood, worms were transferred to plates containing OP50 E. coli (or HT115 E. coli for RNAi experiments) supplemented with 100 μg ml⁻¹ 5-fluoro-2′-deoxyuridine to prevent progeny development, except in lifespan assays. All experiments were conducted using hermaphrodite worms, and the age of the worms is indicated in the corresponding figures and figure legends.

WT (N2) and AM141 (rmIs133[unc-54p::Q40::YFP]) strains were obtained from the Caenorhabditis Genetics Center (CGC), supported by the National Institutes of Health Office of Research Infrastructure Programs (P40 OD010440). RB751 (eps-8(ok539)) was generated by the C. elegans Gene Knockout Consortium and acquired from the CGC. AM23 (rmIs298[F25B3.3p::Q19::CFP]) and AM716 (rmIs284[F25B3.3p::Q67::YFP]) strains were gifted by Richard I. Morimoto²⁴. MAH602 (sqIs61[vha-6p::Q44::YFP + rol-6(su1006)]) was provided by Malene Hansen⁷¹. ZM5838 (hpIs223[rgef-1p::FUS^WT::GFP]), ZM5844 (hpIs233[rgef-1p::FUS^P525L::GFP]) and ZM5842 (hpIs228[rgef-1p::FUS^R522G::GFP]) were provided by Peter St. George-Hyslop⁴⁵. CK405(Psnb-1::TDP-43^WT,myo-2p::dsRED) and CK423 (Psnb-1::TDP-43^M337V,myo-2p::dsRED) were provided by Brian C. Kraemer³³.

From these strains, we generated NFB2862 (Psnb-1::TDP-43^WT,myo-2p::dsRED;juIs76[unc-25p::GFP + lin-15(+)]II) and NFB2863 (Psnb-1::TDP-43^M337V,myo-2p::dsRED;juIs76[unc-25p::GFP + lin-15(+)]II). NFB2858 (rmIs298[F25B3.3p::Q19::CFP];otIs549[unc-25p::unc-25(partial)::mChopti::unc-54 3′ untranslated region (UTR) + pha-1(+)];him-5(e1490)V), NFB2859 (rmIs284[F25B3.3p::Q67::YFP];otIs549[unc-25p::unc-25(partial)::mChopti::unc-54 3′ UTR + pha-1(+)];him-5(e1490)V), NFB2860 (hpIs223[rgef-1p::FUS^WT::GFP];otIs549[unc-25p::unc-25(partial)::mChopti::unc-54 3′ UTR + pha-1(+)];him-5(e1490)V) and NFB2861 (hpIs233[rgef-1p::FUS^P525L::GFP];otIs549[unc-25p::unc-25(partial)::mChopti::unc-54 3′ UTR + pha-1(+)];him-5(e1490)V) were generated by crossing the respective polyQ and FUS-expressing strains with the OH13526 strain⁷². For RNAi in the neurons of polyQ67 worms, we used the DVG196 strain (rmIs284[F25B3.3p::Q67::YFP];sid-1(pk3321)V;uIs69[pCFJ90(myo-2p::mCherry) + unc-119p::sid-1]).

Worms expressing endogenous WT EPS-8::3xHA (VDL05, eps-8(syb2901)IV) or mutant EPS-8(K524R/K583R/K621R::3×HA) (VDL06, eps-8(syb2901, syb3149)IV) were previously generated via CRISPR–Cas9 (ref. ¹⁴). The strains DVG344 (rmIs284[pF25B3.3::Q67::YFP]);eps-8(syb2901) and DVG363 (rmIs133[unc-54p::Q40::YFP]);eps-8(syb2901) were generated by crossing VDL05 with AM716 and AM141, respectively. DVG345 (rmIs284[pF25B3.3::Q67::YFP]);eps-8(syb2901, syb3149) and DVG364 (rmIs133[unc-54p::Q40::YFP]);eps-8(syb2901, syb3149) were generated by crossing VDL06 to AM716 and AM141, respectively. These strains were validated by sequencing using the following primers: eps-8(syb2901): 5′-TTTGTTCGAAGCATGAACGA-3′ and 5′-AGCAGCCCCTGAAATAGTGA-3′; eps-8(syb2901, syb3149): 5′-AACGAGCTAGCAATCCGAAA-3′ and 5′-AGTGCTCTGCCGTCATTAAT-3′. DVG365 (rmIs284[pF25B3.3::Q67::YFP];eps-8(ok539)) was generated by crossing RB751 to AM716. The strain was outcrossed two times to AM716 and validated by polymerase chain reaction with 5′-TCTCCACCACCACAACGTAA-3′ and 5′-GCGGAGCAACTCTTCCATAG-3′ primers.

RNAi constructs

Adult worms were fed HT115 E. coli carrying either an empty control vector (L4440) or vectors expressing double-stranded RNAi. The RNAi constructs targeting eps-8, ifb-2, jnk-1, kgb-1, mig-2 and otub-3 were obtained from the Vidal library. The csn-6, F07A11.4, math-33, rac-2, usp-4, usp-5 and usp-48 RNAi constructs were obtained from the Ahringer library. All RNAi constructs were sequence verified. The RNAi sequences are listed in Supplementary Table 2.

Lifespan assay

Larvae were synchronized using the egg-laying protocol and grown on OP50 E. coli at 20 °C until day 1 of adulthood. Adult hermaphrodites were then transferred to plates with HT115 E. coli carrying either an empty vector or RNAi constructs for lifespan assays. All lifespan assays were performed at 20 °C. Each condition included 96 worms, scored daily or every other day⁷³. Worms that were lost, burrowed into the medium, had a protruding vulva or underwent bagging were censored⁷³.

Nose touch assay

Age-synchronized worms were assessed for nose touch response as previously described^74,75,76. In brief, worms were placed on a thin bacterial lawn, and an eyelash pick was positioned in front of a forward-moving animal. A lack of response was recorded when the worm continued moving forward to crawl under or over the pick. For each condition, 30–40 animals were tested by monitoring the number of responses to a total of 10 gentle eyelash touches.

Chemotaxis assay

Freshly prepared agar plates (2% agar, 5 mM KPO₄ (pH 6.0), 1 mM CaCl₂, 1 mM MgSO₄) were divided into four equal quadrants, along with an inner circle measuring approximately 1 cm across diagonally. A test solution (0.5% benzaldehyde (Sigma-Aldrich, B1334) in ethanol + 0.25 M sodium azide) and a control solution (ethanol + 0.25 M sodium azide) were added to two opposing diagonal quadrants. On the indicated days of adulthood (as shown in the corresponding figures), worms were collected in S-Basal medium, washed three times to remove residual bacteria and placed at the center of the chemotaxis plate. The plates were sealed with parafilm and incubated at 20 °C for 90 minutes. The number of worms in each quadrant was counted, excluding those that did not cross the inner circle. The chemotaxis index was calculated using the following formula: chemotaxis index = ((number of animals in test quadrants) − (number of animals in control quadrants)) / total number of animals⁷⁷.

Motility assays

C. elegans were synchronized on OP50 E. coli using the egg-laying method and grown until day 1 of adulthood and then randomly transferred to plates with HT115 E. coli containing either empty vector or RNAi for the remainder of the experiment. For experiments with Ub-less EPS-8 mutants or DUB inhibitor treatment, worms were instead transferred to fresh plates containing OP50 E. coli. On the indicated day of adulthood (as shown in the corresponding figures), worms were randomly picked and transferred to a drop of M9 buffer, allowing 30 seconds for recovery²⁴. Body bends were then recorded for 30 seconds and analyzed using ImageJ software (version 1.53k) with the wrMTrck plugin (https://www.phage.dk/plugins/)^78,79. The locomotion velocity data were used to calculate body bends per second.

Microscopy

For imaging GABAergic neurons, fluorescent reporter worms were anesthetized with a drop of 0.5 M sodium azide (Sigma-Aldrich, 26628-22-8) on 4% agarose pads (diluted in distilled water) placed over a standard microscope glass slide (Rogo-Sampaic, 11854782). These preparations were sealed with 24 × 60-mm coverslips (RS France, BPD025). To score the number of GABAergic neurons and ventral nerve cord projections, we used a Zeiss Axio Imager.M2 microscope with a ×40 objective. Whole-body worm images were acquired using a Leica THUNDER Imager microscope with Tile Scan function and a ×40 objective.

Human cell lines

HEK293T/17 cells (American Type Culture Collection (ATCC), CRL-11268) were plated on 0.1% gelatin-coated plates and grown in DMEM (Thermo Fisher Scientific, 11966025), supplemented with 1% MEM non-essential amino acids (Thermo Fisher Scientific, 11140035), 1% GlutaMAX (Life Technologies, 35050038) and 10% FBS (Thermo Fisher Scientific, 10500064) at 37 °C with 5% CO₂. ALS-iPSCs (FUS^P525L/P525L) were kindly provided by Irene Bozzoni and Alessandro Rosa³⁷. iPSCs were cultured on Geltrex (Thermo Fisher Scientific, A1413302) using mTeSR1 medium (STEMCELL Technologies, 85850) at 37 °C with 5% CO₂. All cell lines were routinely tested for mycoplasma contamination, and no contamination was detected.

Motor neuron differentiation

Motor neurons were derived from ALS-iPSCs using a monolayer-based differentiation protocol⁸⁰. ALS-iPSCs were seeded on Geltrex-coated plates and maintained in mTeSR1 medium until confluent. Differentiation was initiated using neuron differentiation medium composed of DMEM/F12 and Neurobasal (1:1; Thermo Fisher Scientific, 11330057 and 21103049), supplemented with non-essential amino acids, GlutaMAX (Thermo Fisher Scientific, 35050038), B27 (Thermo Fisher Scientific, 12587010) and N2 (Thermo Fisher Scientific, 17502048).

From day 0 to day 6, the medium was further supplemented with 1 μM retinoic acid (Sigma-Aldrich, R2625), 1 μM smoothened agonist (SAG; Sigma-Aldrich, 566661), 0.1 μM LDN-193189 (Miltenyi Biotec, 130-103-925) and 10 μM SB-431542 (Miltenyi Biotec, 130-105-336). From day 7 to day 14, the neuron differentiation media were supplemented with 1 μM retinoic acid, 1 μM SAG, 4 μM SU-5402 (Sigma-Aldrich, SML0443) and 5 μM DAPT (Sigma-Aldrich, D5942). After day 14, differentiated motor neurons were dissociated and replated on poly-l-ornithine (Sigma-Aldrich, P3655) and laminin-coated (Thermo Fisher Scientific, 23017015) plates in Neurobasal medium, supplemented with non-essential amino acids, GlutaMAX, N2, B27 and neurotrophic factors (10 ng ml⁻¹ BDNF (BIOZOL, 450-02) and 10 ng ml⁻¹ GDNF (BIOZOL, 450-10)).

Lentiviral infection of human cells

Lentivirus (LV)-non-targeting short hairpin RNA (shRNA), LV-EPS8 shRNA 1 (TRCN0000061544), LV-EPS8 shRNA 2 (TRCN0000061545), LV-USP4 shRNA 1 (TRCN0000004039) and LV-USP4 shRNA 2 (TRCN0000004040) in the pLKO.1-puro backbone were obtained from Mission shRNA (Sigma-Aldrich). Supplementary Table 2 contains the target sequences of each shRNA construct.

To generate stable shRNA-expressing HEK293 cell lines, cells were transduced with 5 µl of concentrated lentivirus and selected with 2 µg ml⁻¹ puromycin (Thermo Fisher Scientific, A1113803). For lentiviral infection of iPSCs, cells were dissociated using Accutase (Thermo Fisher Scientific, A1110501), and 100,000 cells were seeded on Geltrex-coated plates in mTeSR1 medium supplemented with 10 μM ROCK inhibitor for 1 day. The next day, cells were infected with 5 µl of concentrated lentivirus. Medium was replaced the following day to remove residual virus. Selection for lentiviral integration was performed using 2 µg ml⁻¹ puromycin for 2 days.

Transfection of HEK293 cells

HEK293 cells (ATCC, CRL-11268) were seeded on 0.1% gelatin-coated plates. When cells reached approximately 40% confluency, they were transfected with 1 μg of one of the following plasmids using FuGENE HD (Promega), according to the manufacturer’s instructions: pARIS-mCherry-httQ23-GFP, pARIS-mCherry-httQ100-GFP, pLVX-Puro-TDP-43-WT, pLVX-Puro-TDP-43-A382T, pcDNA3.1-FUS-HA-WT or pcDNA3.1-FUS-HA-P525L. In the indicated experiments, cells were co-transfected with an additional 1 μg of the pCMV3-EPS8-HA plasmid. The cells were collected after 72 hours of incubation in standard medium. The pARIS-mCherry-httQ23-GFP and pARIS-mCherry-httQ100-GFP plasmids were generously provided by Frédéric Saudou⁸¹. The FUS-HA-WT and FUS-HA-P525L plasmids were a gift from Dorothee Dormann⁸². The pLVX-Puro-TDP-43-WT and pLVX-Puro-TDP-43-A382T plasmids were provided by Shawn Ferguson (Addgene, 133753 and 133756)⁸³. The pCMV3-EPS8-HA plasmid was obtained from Sino Biological (HG11153-CY).

Filter trap and western blot

For filter trap assays, synchronized adult C. elegans were collected and washed with M9 buffer, and worm pellets were snap frozen in liquid nitrogen. Frozen pellets were thawed on ice and lysed in non-denaturing buffer (50 mM HEPES (pH 7.4), 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 2 mM sodium orthovanadate, 1 mM PMSF, protease inhibitor cocktail (Roche)) using a Precellys 24 homogenizer. Lysates were cleared of worm debris by centrifugation (8,000g, 5 minutes, 4 °C), and protein concentrations were determined using the BCA assay (Thermo Fisher Scientific). To assess protein levels by western blot, 30 μg of total protein was separated by SDS-PAGE and transferred to polyvinylidene difluoride membranes (Millipore). To assess aggregated proteins by filter trap, 100 μg of total protein was supplemented with SDS to a final concentration of 0.5% and loaded onto a cellulose acetate membrane assembled in a slot-blot apparatus (Bio-Rad). Then, the membrane was washed with 0.2% SDS, and SDS-resistant aggregates were detected by immunoblotting.

If lysates were used solely for western blot, worms were lysed with a Precellys 24 homogenizer in buffer containing 50 mM Tris-HCl (pH 7.8), 150 mM NaCl, 1% Triton X-100, 0.25% sodium deoxycholate, 1 mM EDTA, 25 mM N-ethylmaleimide, 2 mM sodium orthovanadate, 1 mM PMSF and protease inhibitor cocktail. Lysates were cleared at 10,600g for 10 minutes at 4 °C, and 30 μg of protein was used for western blot experiments. For analysis of polyQ monomers and SDS-insoluble polyQ aggregates, age-synchronized worms were lysed by sonication in native buffer (50 mM Tris (pH 8), 150 mM NaCl, 5 mM EDTA, 1 mM PMSF, protease inhibitor cocktail). Then, 30 μg of total protein was mixed with SDS to a final concentration of 0.4% and resolved by 12.5% SDS-PAGE.

For both filter trap and western blot analyses of C. elegans, immunoblotting was performed with antibodies against GFP (AMSBIO, TP401, dilution 1:5,000), FUS (Abcam, ab154141, clone CL0190, 1:1,000) and TDP-43 (Abcam, ab225710, 1:1,000). Additionally, for western blot experiments, immunoblotting was conducted with anti-EPS8L2 (Abcam, ab85960, 1:1,000), anti-LGG-1 (ref. ⁸⁴, 1:2,000) and α-tubulin (Sigma-Aldrich, T6199, 1:5,000).

For filter trap and western blot analysis of HEK293 cell lines, the cells were collected in lysis buffer (50 mM HEPES (pH 7.4), 150 mM NaCl, 1 mM EDTA, 1% Triton X-100, 2 mM sodium orthovanadate, 1 mM PMSF, protease inhibitor cocktail), followed by homogenization through a 27-gauge syringe needle. Lysates from cells expressing pARIS-mCherry-httQ23-GFP, pARIS-mCherry-httQ100-GFP or without any overexpression were centrifuged at 8,000g for 5 minutes at 4 °C. Lysates from cells expressing FUS-HA-WT, FUS-HA-P525L, pLVX-Puro-TDP-43-WT or pLVX-Puro-TDP-43-A382T were centrifuged at 1,000g for 5 minutes at 4 °C. The supernatants were collected, and protein concentrations were measured with the BCA assay. For western blot, 30 μg of protein was analyzed as above. For filter trap analysis, 100 μg of total protein was supplemented with SDS to a final concentration of 0.5% and loaded onto a cellulose acetate membrane assembled in a slot-blot apparatus as described above. The membrane was then washed with 0.2% SDS, and SDS-resistant protein aggregates were evaluated by immunoblotting. For filter trap analysis, immunoblotting was conducted with antibodies against GFP (AMSBIO, TP401, 1:5,000), FUS (Abcam, ab154141, clone CL0190, 1:1,000) and TDP-43 (Abcam, ab225710, 1:1,000). For western blot, immunoblotting was conducted with anti-EPS8 (Proteintech, 12455-1-AP, 1:1,000), anti-β-actin (Abcam, 8226, 1:5,000), anti-HTT (Cell Signaling Technology, 5656, 1:1,000), FUS (Abcam, ab154141, clone CL0190, 1:1,000), TDP-43 (Abcam, ab225710, 1:1,000), anti-LC3B (Cell Signaling Technology, 2775, 1:1,000) and anti-USP-4 (Abcam, ab181105, 1:1,000).

For necroptosis analysis, iPSC-derived motor neurons were lysed in RIPA buffer (50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1% Triton X-100, 1% sodium deoxycholate, 0.1% SDS, 1 mM EDTA, 1 mM PMSF, protease inhibitor cocktail). Immunoblotting was performed using anti-phospho-RIP (Ser166) (Cell Signaling Technology, 65746, clone D1L3S, 1:1,000) and anti-RIP (Cell Signaling Technology, 3493, clone D94C12, 1:1,000). Densitometry of filter trap and western blot assays was performed using ImageJ software (version 1.51).

Protein immunoprecipitation for interaction analysis

HEK293 cells were collected and lysed in a protein lysis buffer containing 50 mM Tris-HCl (pH 6.7) 150 mM NaCl, 1% NP40, 0.25% sodium deoxycholate, 1 mM EDTA, 1 mM PMSF, 1 mM sodium orthovanadate, 1 mM NaF and protease inhibitor cocktail. Lysates were homogenized through a 27-gauge syringe needle and centrifuged at 13,000g for 15 minutes at 4 °C. Supernatants were incubated on ice for 1 hour with anti-USP-4 antibody (Abcam, ab181105, 1:100). As a negative control, the same amount of protein was incubated with anti-normal rabbit IgG (Cell Signaling Technology, 2729, 1:378). Samples were then incubated with 50 µl of µMACS MicroBeads for 1 hour at 4 °C with overhead shaking. Then, the samples were loaded onto pre-cleared µMACS columns (Miltenyi Biotec, 130-042-701). The beads were washed three times with a buffer containing 50 mM Tris (pH 7.5), 150 mM NaCl, 5% glycerol and 0.05% Triton, followed by five washes with 50 mM Tris (pH 7.5) and 150 mM NaCl. The samples were eluted with 75 μl of boiled 2× Laemmli buffer, boiled for 5 minutes at 95 °C and analyzed by western blotting.

Native gels analysis

HEK293 cells expressing CMV:mRFP-Q74 (ref. ³⁰) were lysed in buffer containing 50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 0.5% NP-40, 2 mM EDTA, 1 mM EGTA, 10% glycerol, 2 mM sodium orthovanadate, 1 mM PMSF and protease inhibitor cocktail. Lysates were homogenized using a 27-gauge syringe needle and centrifuged at 12,000g for 15 minutes at 4 °C. Supernatants were collected, and protein concentrations were determined using the BCA protein assay (Thermo Fisher Scientific). Equal amounts of protein lysates were mixed 1:1 with sample buffer (50 mM Tris-HCl (pH 6.8), 10% glycerol, 0.01% bromophenol blue). Then, 20 μg of total protein was separated using 4–15% Tris-Glycine eXtended protein gels (Bio-Rad) and imaged via fluorescence using LICOR Odyssey M.

Immunocytochemistry

Cells were fixed with 4% paraformaldehyde in PBS for 20 minutes, followed by permeabilization with 0.2% Triton X-100 in PBS (10 minutes) and blocking with 3% BSA in 0.2% Triton X-100 in PBS (10 minutes). The cells were then incubated with anti-MAP2 (Sigma-Aldrich, M1406, 1:300) and rabbit anti-cleaved caspase-3 (Cell Signalling Technology, 9661S, 1:300) for 2 hours at room temperature. After washing with PBS, cells were incubated with secondary antibodies (Alexa Fluor 488 goat anti-mouse (Thermo Fisher Scientific, A-11029, 1:500) and Alexa Fluor 568 F(ab′)2 fragment of goat anti-rabbit IgG (H + L) (Thermo Fisher Scientific, A-21069, 1:500)) and Hoechst 33342 (Life Technologies, 1656104) for 1 hour at room temperature. Finally, the coverslips were rinsed in PBS, followed by a distilled water wash, and then mounted onto microscope slides with FluorSave Reagent (Merck, 345789).

CytoD, RAC activator and DUB inhibitor treatment

For CytoD treatment, worms were collected and randomly divided equally into M9 solutions containing either 10 μM CytoD (STEMCELL Technologies, 100-0557) or DMSO as a vehicle control. The worms were incubated with CytoD or DMSO for 6 hours on a shaker. For DUB inhibitor experiments, worms were collected and randomly transferred onto plates with OP50 bacteria covered with a final concentration of 13.7 μg ml⁻¹ PR-619 (Merck, 662141) or vehicle control (DMSO) for either 4 hours or 1 day as indicated in the corresponding figures.

HEK293 cells were treated with 2 μM CytoD or DMSO for 4 hours before lysis. For RAC activation, cells were treated with 2 U ml⁻¹ Rac/Cdc42 Activator II (Cytoskeleton, CN02-A) for 6 hours.

Proteasome activity

Day 5 adult worms and HEK293 cells were lysed in proteasome activity assay buffer (50 mM Tris-HCl (pH 7.5), 10% glycerol, 5 mM MgCl₂, 0.5 mM EDTA, 2 mM ATP, 1 mM DTT) using a Precellys 24 or a 27-gauge syringe, respectively. The samples were centrifuged at 10,000g for 10 minutes at 4 °C, and the supernatants were collected. Protein concentrations were determined using the BCA protein assay kit.

To measure chymotrypsin-like proteasome activity, 25 μg of total protein was incubated with the fluorogenic substrate Suc-Leu-Leu-Val-Tyr-AMC (Enzo Life Sciences, BML-P802) in 96-well plates (BD Falcon). Fluorescence was measured every 5 minutes for 2 hours at 20 °C (C. elegans) or 37 °C (human cells) using a microplate fluorometer (PerkinElmer, EnSpire) at 380-nm excitation and 460-nm emission.

Statistics and reproducibility

For quantification of filter trap and western blot data, we presented the results as relative changes compared with the corresponding control conditions. To average and statistically analyze independent experiments for these assays, we normalized test conditions to their corresponding control groups measured concurrently in each replicate experiment. Given that all the control groups were set to 100, we used a non-parametric Wilcoxon test when comparing two conditions to assess changes in protein aggregation and protein levels. For all other assays, we used parametric tests. Data distribution was assumed to be normal, but this was not formally tested. When more than two conditions or two independent variables were compared, we used one-way or two-way ANOVA followed by multiple comparisons tests. All statistical analyses were performed using GraphPad Prism (version 10.4.1).

For lifespan experiments, we used GraphPad Prism (version 10.4.1) and OASIS (version 1)⁸⁵ to determine median and mean lifespan, respectively. The P values were calculated using the log-rank (Mantel–Cox) method and refer to comparisons between experimental and control animals within a single lifespan experiment. Each lifespan graph represents a single, representative experiment. Supplementary Table 1 contains the number of total/censored worms as well as detailed statistical analyses for each replicate lifespan experiment.

No statistical methods were used to predetermine sample size, but our sample sizes are similar to, or greater than, those reported in previous publications using the same procedures^{9,14,16,26,30,33,44,46,50,73,75,76,78,86,87,88}. For motility assays, worms were excluded from analysis if they showed fewer than 0.1 body bends per second or were not recognized by the ImageJ software. No animals or data points were excluded from other analyses. For lifespan assays, worms were randomly picked and transferred from the synchronized population to the different experimental conditions. For all other experiments, worms were randomly distributed into the various experimental groups from single pulls of synchronized populations. Human cells were distributed to the various groups of all experiments from single pulls. Data collection was not randomized. Data collection and analysis were not performed blinded to the conditions of the experiments.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

A new retrospective cohort study published in The Lancet Primary Care has provided compelling real-world evidence that the MVA-BN (Modified Vaccinia Ankara-Bavarian Nordic) vaccine continues to offer substantial protection against severe monkeypox (mpox) disease more than 1.5 years after immunization. The commentary accompanying the study—written by infectious disease experts Dr. Emily Evans and Dr. Boghuma Titanji of Emory University—highlights how the findings mark a significant step forward in understanding vaccine durability and clinical protection in the face of waning antibody levels.

The original research, conducted in New South Wales (NSW), Australia, by Latham et al., represents the largest and most detailed clinical study to date on breakthrough mpox infections in fully vaccinated individuals. It is particularly significant given the limited baseline immunity in the Australian population due to the absence of historical smallpox vaccination campaigns, a contrast to settings in Europe, North America, and parts of Africa.

Durable Protection Despite Waning Antibodies

The study included 674 confirmed mpox cases between June and November 2024, during Australia’s largest recorded mpox outbreak. Of those, 251 individuals (37%) were fully vaccinated with two doses of MVA-BN. The median interval between the second dose and symptom onset was nearly 22 months.

Key outcomes demonstrate that full vaccination was associated with:

• 89% reduced risk of hospitalization compared to unvaccinated individuals (RR 0.11; 95% CI 0.03–0.43),
• 55% reduction in risk of systemic symptoms like fever, headache, and muscle pain (RR 0.72),
• Significant reduction in extragenital lesions, a potential driver of casual-contact transmission (RR 0.45).

Interestingly, fully vaccinated individuals were slightly more likely to present with anogenital lesions, though these were generally mild and did not lead to hospitalization.

Despite laboratory evidence that antibody titers wane within 5–7 months of vaccination, these clinical findings suggest meaningful protection persists well beyond serological decline. This divergence between antibody kinetics and real-world outcomes adds nuance to the discussion around correlates of protection and vaccine-induced immunity.

Implications for HIV-Positive Individuals

While the Australian cohort included people living with HIV, the study did not stratify clinical outcomes by HIV status. This is a notable omission, given that HIV-positive individuals—especially those with advanced disease—are at substantially higher risk of severe mpox, including disseminated and even fatal outcomes.

Previous research has shown that while people with HIV can mount adequate immune responses to MVA-BN, those with lower CD4 counts or poorly managed HIV may have weaker protection. In one clinical trial, antibody titers were significantly higher in people without HIV compared to those with HIV, despite both groups reaching high seropositivity rates.

The absence of outcome data stratified by HIV status represents a critical gap, especially as current mpox outbreaks in sub-Saharan Africa—where HIV prevalence is high—continue to intensify.

A Public Health Opportunity and National Imperative

The findings have important implications for both national and global health security. Infections with mpox, while relatively rare outside high-risk populations, can escalate quickly during outbreaks and impose significant strain on healthcare systems.

Preventing hospitalizations and systemic symptoms—especially in younger, unvaccinated populations—is not only a clinical goal but also a matter of public health resilience. In the Australian outbreak, the vast majority of mpox patients were men under 50, underscoring the vulnerability of generations never immunized against smallpox.

As Dr. Titanji and Dr. Evans note, leveraging sexual health clinics as vaccination hubs has proven effective, but disparities in access persist. Populations disconnected from such services may face increased risk during future outbreaks, further emphasizing the need for broader, community-engaged vaccination strategies.

Global Equity and the Next Phase: Boosters?

The NSW study’s implication that protection extends well beyond the initial year is reassuring—but it also raises new questions. Should a third (booster) dose be recommended for specific populations? Should HIV-positive individuals, or those with high behavioral exposure risk, receive tailored vaccine schedules?

The commentary urges global immunization technical advisory groups to incorporate these findings into deliberations about MVA-BN booster strategies. It also reinforces the call for equitable global access to MVA-BN, especially in lower-income settings currently grappling with resurging outbreaks.

Notably, viral sequencing in the Australian outbreak revealed no substantial genetic divergence between viruses infecting vaccinated and unvaccinated individuals. This suggests vaccine escape was not a major factor in breakthrough infections and bolsters confidence in the ongoing relevance of the MVA-BN platform.

Next Steps: Research, Policy:

This evidence base provides a firm foundation for future preparedness—but several priorities remain:

• Stratified clinical studies on vaccine efficacy in immunocompromised populations,
• Longitudinal analyses of immune response durability post-MVA-BN,
• Global coordination on vaccination campaigns in areas with rising case counts and high HIV prevalence,
• Booster dose policy frameworks informed by risk profiling, not just time since vaccination.

As mpox transitions from a global health emergency to an endemic risk, the world must shift from reactive containment to proactive, equitable protection—particularly for communities historically underserved by immunization programs.

Sources and Further Reading

Evans EE, Titanji BK. Protection that lasts? MVA-BN against clade IIb mpox. The Lancet Primary Care, 24 July 2025.

Latham NH, Pett J, Katelaris AL, et al.  Clinical features of mpox in fully vaccinated people in New South Wales, Australia: a retrospective cohort study. The Lancet Primary Care, 24 July 2025.

Taha AM, Rodriguez-Morales AJ, Sah R. Mpox breakthrough infections: concerns and actions. The Lancet Infectious Diseases, Nov 2023.

Valentina M, Guiulia M, Eleonora C, et al. Humoral and T-Cell Responses Following MVA-BN Booster Vaccination Against Mpox Virus Clades Ib and IIb,  MedRxiv pre-print, 7 July 2025.

Gaithersburg, Md.-based Polaris Genomics, a mental healthcare firm eyeing physical biomarkers to aid diagnoses as well as treatments, has secured $250,000 in debt, according to a recent SEC filing. The company raised over $5.9 million from investors, according to Pitchbook.

The startup up was founded in 2017 by Yusuf Henriques, a US Army veteran, Charles Cathlin, who served in the US Air Force, Princeton graduate Tshaka Cunningham and physician Anne Naclerio, a 30-year veteran of the US Army, with Cathlin drawing on his experience treating the first responders of the 9/11 terror attacks of 2001.

Cathlin serves as the company’s CEO and Cunningham is chief science officer. Cunningham is director of R&D while Naclerio serves as chief medical officer.

According to a report in Startup Health, Cathlin — an engineer and graduate of the Air Force Academy and Stanford University — grappled with the unique clinical challenge of “diagnosing” mental health conditions, rather than relying on observation or self-reporting.

“The firefighters and police officers were traumatized by what they experienced,” Cathlin told Illumina, whose accelerator Polaris Genomics joined as an early-stage startup. “That had a large impact on me and got me interested in mental health, because no one was really addressing it.”

In his quest, Cathlin eventually tracked down the work of a psychiatric researcher in New York City that connected mental health conditions and RNS expression.

“What got me excited was that there was an actual biomarker to identify who actually had post-traumatic stress disorder,” Cathlin told Startup Health. “The fact that you can introduce an objective tool to that process was a game changer.”

Cathlin believes the company’s mission is to make “invisible wounds visible using the power of genomics.”

“We believe genomics is a driving force to connect mental illness to its biological underpinnings. By doing that, we can decrease the stigma, suffering, silence, and suicide.”

Polaris Genomics has partnered with the Illumina Accelerator, and scientists from Mount Sinai and the Max Planck Institute of Psychiatry to develop the first-to-market, patented genomic biomarker assay to identify risks of post-traumatic stress disorder (PTSD). The company was granted two patents on the blood-based biomarker model for PTSD.

Last year, the company launched a trial with Stella DC to further develop PTS-iD, called a first test of its kind to use genomics to detect the physical changes underlying PTSD. Polaris Genomics believes the Covid-19 pandemic and subsequent years of mental health repercussions has “elucidated the urgency for advances in diagnostics and treatment across a range of mental health and neuropsychiatric conditions.”

Background

Obstructive sleep apnea (OSA) is a common sleep disorder, with a prevalence of approximately 23% in women and nearly 50% in men.¹ The development of OSA is influenced by both anatomical and non-anatomical risk factors. Anatomical factors, such as obesity and craniofacial abnormalities, promote upper airway collapse and obstruction during sleep.² Non-anatomical factors include heightened airway collapsibility, a low respiratory arousal threshold, and unstable ventilatory control.³ The hallmark feature of OSA is intermittent hypoxia during sleep, which significantly increases the risk of cardiovascular, neurological, and metabolic disorders.⁴

The potential role of the gut microbiota in human disease development has received increasing attention over the past decade. In particular, microbiota dysbiosis has been implicated in the pathogenesis of OSA.⁵ Disruption of the gut microbiota has been associated with altered sleep-wake architecture⁶ and reduced sleep efficiency.^7,8 It may also impair the ventilatory response to hypercapnia,⁹ thereby contributing to unstable ventilatory control in patients with OSA. In addition, microbiota dysbiosis contributes to the development of obesity,¹⁰ a key risk factor for OSA. Probiotics have emerged as promising adjunctive interventions for OSA, primarily through their ability to reduce systemic inflammation and enhance gut barrier integrity.¹¹ Faecal microbiota transplantation has also been shown to partially alleviate cardiovascular disturbances induced by chronic intermittent hypoxia.¹² Moreover, the probiotic strain Lactobacillus rhamnosus GG has demonstrated beneficial effects in experimental models of OSA, including improvements in metabolic disturbances,¹³ mitigation of hypertension severity,¹⁴ attenuation of cardiac remodeling and inflammation.¹⁵ Accordingly, elucidating the role of gut microbiota in the pathogenesis of OSA holds substantial promise, and the identification of effective probiotic-based interventions may offer a novel therapeutic avenue.

Metabolites and their related biochemical pathways have emerged as important contributors to the development of OSA.¹⁶ An increased prevalence of OSA has been reported in patients with neurodegenerative disorders, potentially related to impairments in central respiratory control and functional alterations of the upper airway.¹⁷ The nervous system and gastrointestinal tract communicate through a bidirectional network of signaling pathways, collectively referred to as the microbiota–gut–brain axis, which involves the vagus nerve, immune mechanisms, and microbiota-associated metabolic and molecular products. Emerging evidence suggests that this axis plays a pivotal role in the pathogenesis of neurodegenerative diseases.¹⁸ These findings highlight the potential importance of microbiota–gut–brain axis related pathways in the pathogenesis and progression of OSA, suggesting that further research in this area is warranted. Previous studies have reported the involvement of metabolites and microbiota-related metabolites in the development and progression of OSA. Xu et al reported correlations between alterations in the oral microbiome and disruptions in urinary metabolites in children with OSA.¹⁹ Using Mendelian randomization (MR), Yan et al identified several gut microbiota and microbiota-related metabolites as potential independent risk factors for OSA.²⁰ Therefore, investigating the relationship between the gut microbiota and OSA, and further exploring the potential mediating role of metabolites, is of substantial significance.

MR provides a powerful framework for investigating the causal relationship between gut microbiota and OSA.²¹ In MR analysis, genetic variants are used as instrumental variables (IVs) for exposure traits, enabling the estimation of causal effects on clinical outcomes while minimizing confounding and reverse causation. In this study, we performed two-sample and two-step MR analyses using summary-level data from the genome-wide association studies (GWAS) on gut microbiota, plasma metabolites, and OSA. This study primarily focused on identifying gut microbiota and potential mediator metabolites that may confer protective effects against OSA, with the aim of uncovering novel therapeutic targets and providing preliminary insights into the underlying mechanisms.

Methods

Study Design

This study was conducted using a two-sample MR framework, with single nucleotide polymorphisms (SNPs) selected as IVs. MR relies on three key assumptions: i the IVs are strongly associated with the exposure; ii the IVs are not associated with any confounders; and iii the IVs affect the outcome solely through the exposure, without exerting a direct effect on the outcome.

An overview of the study design is provided in Figure 1. First, a two-sample MR analysis was performed to explore the potential causal relationship between gut microbiota and OSA. To reduce potential functional heterogeneity, microbial taxa within the same genus or family that showed divergent associations with the OSA were excluded. Only microbial taxa associated with a reduced risk of OSA were retained for further analysis. Second, potential mediators were identified according to the following steps. Step 1: An exploratory two-sample MR analysis was conducted to identify metabolites potentially involved in the development and progression of OSA. To account for multiple testing, the false discovery rate (FDR) was controlled using the Benjamini–Hochberg procedure. Metabolites were prioritized based on inverse variance weighted (IVW) P values adjusted for FDR (P_FDR). The biological relevance of these metabolites was further assessed using the Human Metabolome Database (HMDB) (Version 5.0). Ultimately, the top 10 metabolites with potential biological significance were selected as candidate mediators for subsequent analyses (Supplementary Table 1). Step 2: Potential mediators of the association between gut microbiota and OSA were identified based on the following criteria: i a two-sample MR analysis was conducted to assess the causal relationship between each selected protective taxon and candidate mediator. P values were adjusted for multiple comparisons using the FDR correction. The directionality of the associations was confirmed to be unidirectional. ii a two-sample MR analysis was performed to evaluate the causal effect of each candidate mediator on the OSA, using a more stringent SNP selection threshold (P < 5e-6) and excluding SNPs associated with known confounders. iii the direction of the association between the mediator and OSA had to be opposite to that between the selected protective taxa and the mediator. Third, the mediating effects of the identified metabolites on the causal pathway linking gut microbiota to OSA were quantified using a two-step MR approach. In the initial step, we employed a two-sample MR analysis to assess the total direct effect of gut microbiota on OSA risk (β0). In the subsequent step, we estimated the effect of gut microbiota on plasma metabolites (β1) and the effect of plasma metabolites on OSA (β2), allowing us to calculate the indirect effect (β1 × β2). The proportion of the mediated effect was determined by dividing β1 × β2 by the total effect (β0).

Data Sources

We garnered the GWAS data for the gut microbiota from the Dutch Microbiome Project.²² The Dutch Microbiome Project analyzed feces from 7,738 individuals of European descent, involving 207 taxa.²² The GWAS data for plasma metabolites were obtained from the Canadian Longitudinal Study on Aging cohort, comprising 8,299 participants.²³ This analysis encompassed 1,091 metabolic features and 309 metabolite ratios.

The GWAS data for OSA were obtained from the FinnGen database (R10) with 410385 individuals of European ancestry. The data contained 43901 OSA cases and 366484 controls. OSA diagnostic criteria was depended on ICD codes (ICD-10: G47.3; ICD-9: 3472), which were obtained from the Finnish National Hospital Discharge Registry and the Causes of Death Registry. The ICD-10 code G47.3 encompasses both OSA and central sleep apnea (CSA). Nevertheless, Strausz et al validated the registry-based OSA diagnosis, reporting a positive predictive value of >98%, indicating a high level of diagnostic accuracy.²⁴ The FinnGen study is a large-scale genomics project that has analyzed more than 500,000 Finnish biobank samples, linking genetic variations with health data to uncover disease mechanisms and predispositions.²⁵

Instrumental Variables Selection

In this study, SNPs were selected as IVs, and their selection and validation followed the criteria outlined below. Firstly, due to the limited number of genome-wide significant SNPs available for gut microbiota, we applied a significance threshold of P < 1e-5 to identify potentially relevant SNPs. For the selected mediator metabolites, MR analyses were performed using OSA as the outcome, with SNPs selected based on a stricter threshold of P < 5e-6. Secondly, to minimize bias from linkage disequilibrium (LD), we performed SNP clumping using an LD threshold of R² < 0.001 within a 10,000 kb window. Thirdly, to reduce the risk of weak instrument bias, we calculated the F-statistic for each SNP and retained only those with F > 10 as valid IVs. Functional annotation of SNPs was conducted using functional mapping and gene annotation (FUMA) (Version 1.8.0), based on the most recent release of the GWAS Catalog.²⁶ To reduce the risk of potential pleiotropy, SNPs previously associated with OSA-related traits, such as body mass index, waist circumference, hip circumference, or waist-to-hip ratio, were excluded (Supplementary Table 2).

Statistical Analysis

We conducted a two-sample MR analysis to evaluate the causal relationships between gut microbiota and OSA, as well as between plasma metabolites and OSA independently. We evaluated the causal association between gut microbiota and the plasma metabolites using bidirectional MR. We used the IVW method as the primary MR approach. To enhance the robustness and reliability of our findings, we also applied complementary MR methods, including MR-Egger regression, weighted median, simple mode, and weighted mode. Apart from the MR methods outlined above, we also carried out various supplementary sensitivity analyses. Firstly, we evaluated heterogeneity in causal inference through the calculation of Cochran’s Q statistic. Secondly, we applied the MR-Egger intercept test to detect horizontal pleiotropy. Moreover, the MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) method was employed to detect horizontal pleiotropy and identify potential outlier SNPs. A global test P-value < 0.05 was considered indicative of significant distortion in the causal estimates due to pleiotropy. Additionally, we employed the MR Steiger directionality test to ascertain the causal direction between the exposure and the outcome. Furthermore, the reliability of the findings was assessed through a leave-one-out approach for validation.

Effect sizes were expressed as odds ratios (OR), β-coefficients, and corresponding 95% confidence intervals (CI). All statistical analyses were conducted using the “TwoSampleMR” package (version 0.6.6), “MRPRESSO” package, and “ggplot2” packages within R software (version 4.4.1).

Results

Instrument Variables Included in Analysis

Based on the predefined selection criteria, we identified valid IVs from GWAS summary statistics of gut microbiota and plasma metabolites. Supplementary Tables 3 and 4 provide detailed characteristics of these IVs, including their corresponding F statistics. All included SNPs had F statistics greater than 10, supporting adequate instrument strength.

Effects of Gut Microbiota on Obstructive Sleep Apnea

Using the IVW method, this study identified 4 microbial taxa that were associated with a reduced risk of the OSA, including species Parabacteroides merdae, genus Faecalibacterium, species Faecalibacterium prausnitzii and species Bifidobacterium longum (Table 1). Species Parabacteroides merdae exhibited the most pronounced protective effect (OR = 0.909, 95% CI = 0.828~0.999, P value = 0.047). Species Faecalibacterium prausnitzii and genus Faecalibacterium showed the second strongest protective effects (species Faecalibacterium prausnitzii, OR = 0.921, 95% CI = 0.860~0.986, P value = 0.019; genus Faecalibacterium, OR = 0.923, 95% CI = 0.857~0.994, P value = 0.034). The protective effect of species Bifidobacterium longum was comparatively weaker (OR = 0.930, 95% CI = 0.869~0.997, P value = 0.040).

Table 1 Effects of Gut Microbiota on the Risk of Obstructive Sleep Apnea

Effects of Gut Microbiota on Mediators

Following the established criteria and selection workflow, we identified two candidate mediators, 2-hydroxypalmitate and hyocholate, from the top 10 biologically relevant metabolites. As shown in Table 2 and Supplementary Table 5, species Parabacteroides merdae was positively associated with the levels of 2-hydroxypalmitate (β = 0.254, 95% CI = 0.117~0.391, IVW P value < 0.001, IVW P_FDR value = 0.003). Since MR analyses were performed between the selected microbial taxa and the top 10 metabolites with potential biological significance, FDR correction was applied across these 10 tests using the Benjamini–Hochberg method. After FDR correction, no statistically significant associations were observed between genus Faecalibacterium and 2-hydroxypalmitate, species Faecalibacterium prausnitzii and 2-hydroxypalmitate, or species Bifidobacterium longum and hyocholate.

Table 2 Effects of Gut Microbiota on Mediators

Effects of Selected Mediators on the OSA and Mediation Analysis

Table 3 and Supplementary Table 5, demonstrates that elevated levels of 2-hydroxypalmitate were associated with a reduced risk of OSA (OR = 0.926, 95% CI = 0.865~0.991, P value = 0.027). As presented in Figure 2, through two-step MR analysis, 2-hydroxypalmitate was found to mediate 20.53% of the association between the species Parabacteroides merdae and OSA.

Table 3 Effects of Mediators on Obstructive Sleep Apnea

Figure 2 The 2-hydroxypalmitate mediated the causal effect of species Parabacteroides merdae on OSA. Two-step MR was used to evaluate the mediating role of 2-hydroxypalmitate in the causal pathway linking species Parabacteroides merdae to OSA. The causal effect of species Parabacteroides merdae on 2-hydroxypalmitate, 2-hydroxypalmitate on OSA and species Parabacteroides merdae on OSA were assumed to be β1, β2 and β0, respectively. The proportion of the mediated effect (bold text) was determined by dividing β1× β2 by the total effect (β0). MR estimates were derived from the IVW method in two-sample MR. Abbreviations: OSA, obstructive sleep apnea; MR, mendelian randomization; IVW, inverse variance weighted.

MR Sensitivity Analyses

According to the results presented in Supplementary Table 6, no evidence of heterogeneity was observed, as indicated by Cochran’s Q statistic (all P values > 0.05). Both the MR-Egger intercept test and the MR-PRESSO global test indicated no signs of horizontal pleiotropy, with P values greater than 0.05. In addition, the MR-PRESSO method did not identify any outlier variants. The MR-Steiger directionality test provided no evidence supporting a reverse causal relationship from the OSA to the four protective taxa or to 2-hydroxypalmitate. As shown in Supplementary Figures 1–3, the leave-one-out analysis suggested that certain SNPs may have disproportionately influenced the causal estimates. Based on the overall findings from our sensitivity analyses, the observed associations appear to be relatively robust. Nonetheless, these results should be interpreted with caution.

Discussion

In this study, we performed a comprehensive MR analysis utilizing large-scale GWAS summary data to explore the causal relationships between gut microbiota, plasma metabolites, and OSA. In the Dutch Microbiome Project, species Parabacteroides merdae, genus Faecalibacterium, species Faecalibacterium prausnitzii and species Bifidobacterium longum demonstrated a potential protective association with OSA. This study was exploratory in nature. We included the top 10 metabolites with potential biological significance as candidate mediators. Among them, only 2-hydroxypalmitate was found to mediate the association between species Parabacteroides merdae and OSA, with a mediation proportion of 20.53%.

Species Parabacteroides Merdae and OSA

Species Parabacteroides merdae is a Gram-negative, anaerobic, rod-shaped bacterium commonly found in the human gut microbiota.²⁷ Consistent with our findings, species Parabacteroides merdae retained a strong negative association with OSA.²⁸ The potential protective effect of species Parabacteroides merdae against OSA may be related to its role in alleviating obesity.²⁹ Qiao et al reported that species Parabacteroides merdae significantly attenuated high-fat diet-induced weight gain in mice.³⁰ Given that obesity is a major risk factor for OSA, the beneficial effect of species Parabacteroides merdae on obesity may partially explain its protective role against OSA. Fecal microbiota transplantation has been shown to lower systolic blood pressure (SBP), with increased abundances of species Parabacteroides merdae associated with SBP reduction.³¹ Given that OSA is a known risk factor for hypertension, it is plausible that the SBP-lowering effect of species Parabacteroides merdae may be related to improvements in nocturnal intermittent hypoxia. However, this hypothesis requires further investigation. Evidence linking species Parabacteroides merdae to OSA remains limited. However, further investigation into its potential protective role may help uncover novel therapeutic strategies. Given the complexity of the underlying mechanisms, further research is warranted to identify the key pathways and molecular targets through which species Parabacteroides merdae may influence OSA progression.

2-Hydroxypalmitate and OSA

2-hydroxypalmitate, also known as 2-hydroxyhexadecanoic acid, has emerged as a representative member of the 2-hydroxy fatty acid family.³² These molecules constitute essential structural components of mammalian sphingolipids. Sphingolipids are essential components of cell membranes, particularly abundant in the brain, where they help maintain myelin integrity, facilitate neuronal signaling, and support intercellular communication.³³ Fatty acid 2-hydroxylase (FA2H) catalyzes the biosynthesis of hydroxylated sphingolipids by introducing a hydroxyl group at the α-carbon of long-chain fatty acids.³⁴ FA2H gene mutations are linked to leukodystrophy and spastic paraparesis, highlighting the importance of hydroxylated fatty acid-containing sphingolipids in nervous system function.^35,36 Increasing evidence suggests that alterations in sphingolipid pathways may contribute to the etiopathogenesis of neurodegenerative diseases.³⁷ Parkinson’s disease (PD) is one of the most prevalent neurodegenerative disorders. Sphingolipids play a critical role in various cellular processes involved in the pathogenesis of PD, including mitochondrial function, autophagy, and endosomal trafficking.³⁸ Upper airway obstruction and dysfunction are observed in approximately 24% to 65% of PD patients, primarily attributed to laryngopharyngeal motor impairment.^39,40 This dysfunction reflects a broader impairment of neuromuscular control in the upper airway, characterized by reduced tone in the pharyngeal dilator muscles, impaired coordination of respiratory and swallowing reflexes, and delayed glottic opening.¹⁷ These abnormalities may predispose individuals with PD to the development of OSA, particularly during sleep when compensatory mechanisms are further diminished. Given the essential role of sphingolipids in maintaining neuronal membrane stability and supporting axonal conduction, their dysregulation may plausibly impair the integrity of central or peripheral neural pathways involved in upper airway motor control. However, it must be acknowledged that current evidence directly linking 2-hydroxypalmitate to the regulation of upper airway motor function is limited. Further studies are warranted to clarify this potential association.

However, some studies have suggested that 2-hydroxypalmitate may contribute to the development of OSA. 2-hydroxypalmitate is associated with dyslipidemia, a condition commonly observed in obesity.^41,42 Given that obesity is a major risk factor for OSA, 2-hydroxypalmitate may contribute to the development of OSA through pathways related to fatty acid metabolism. Sullivan et al⁴³ found that vitamin D supplementation was associated with lower 2-hydroxypalmitate levels, while Ayyıldız et al⁴⁴ reported a potential beneficial effect of vitamin D supplementation on the prognosis of mild OSA. These findings are inconsistent with our results. Nonetheless, given the exploratory nature of this study, further research is needed to clarify the role of 2-hydroxypalmitate in OSA pathogenesis.

2-Hydroxypalmitate as a Putative Mediator: Implications and Future Directions

In this study, we identified 2-hydroxypalmitate as a potential mediator of the relationship between species Parabacteroides merdae and the reduced risk of OSA. The mediation analysis demonstrated that 2-hydroxypalmitate accounted for 20.53% of the total effect. In terms of effect size, this proportion represents a moderate mediation effect, comparable to those observed in other microbial-metabolite axes involved in disease progression. For example, prior studies have reported mediation proportions ranging from 6.5% to 25.1% in obesity,⁴⁵ 10.29% to 21.9% in type 2 diabetes,⁴⁶ 11.04% to 15.35% in PD,⁴⁷ 14.62% to 37.48% in chronic airway disease,^48,49 and 8.1% to 22.8% in various cancer types.⁵⁰ These findings suggest that the mediation effect observed in our study falls within a biologically meaningful range and supports the role of 2-hydroxypalmitate as a mediator within the causal pathway from species Parabacteroides merdae to OSA.

Previous studies suggest that species Parabacteroides merdae may reduce the risk of OSA through anti-obesity effects, while 2-hydroxypalmitate may confer protection via sphingolipid metabolism, which modulates upper airway motor function. In our analysis, species Parabacteroides merdae and 2-hydroxypalmitate were positively correlated and both linked to reduced OSA risk, supporting the plausibility of this mediation pathway. Although direct evidence for the regulatory relationship between species Parabacteroides merdae and 2-hydroxypalmitate is currently lacking, our findings suggest a biologically relevant connection that merits further investigation. Overall, this study reveals a gut microbiota-metabolite-OSA pathway and offers new evidence for microbial metabolic mediation in OSA. Given the exploratory nature of this study, future experimental and longitudinal studies are warranted to validate these results and elucidate the underlying mechanisms.

Limitations

This study has several limitations that should be acknowledged. First, the GWAS summary statistics used in our MR analyses were derived exclusively from individuals of European ancestry. As a result, our findings may not be fully generalizable to other populations, given known differences in genetic architecture, LD structure, allele frequencies, and environmental modifiers across ancestries. These population-specific factors could influence both the strength and direction of causal associations, potentially limiting the applicability of our results to non-European groups. To enhance the external validity of microbiota-metabolite-disease mediation frameworks, future studies should incorporate GWAS data from ancestrally diverse cohorts and perform replication analyses across multiple populations. Such efforts are essential to improve the global relevance and translational potential of microbiome-informed causal inference. Second, sleep apnea in the FinnGen study was defined using ICD codes (ICD-10: G47.3; ICD-9: 3472), and individual-level polysomnographic (PSG) data, such as the apnea-hypopnea index, oxygen desaturation index, and sleep architecture, were not available. This limitation precludes accurate confirmation of OSA diagnoses, assessment of disease severity, and identification of clinical subtypes (eg, rapid eye movement-predominant or positional OSA). Notably, ICD-10 code G47.3 includes both OSA and CSA. While Strausz et al²⁴ validated the registry-based OSA definition and reported high diagnostic accuracy, the potential for misclassification remains, particularly due to the inclusion of CSA cases. However, given the low prevalence of CSA⁵¹ and the lack of evidence linking our exposures of interest to CSA risk, any such misclassification is likely nondifferential with respect to exposure. From a statistical perspective, this would tend to bias the effect estimates toward the null, resulting in a conservative estimate of the true causal effect. Future studies incorporating PSG-confirmed, individual-level OSA data are therefore warranted to validate and refine these findings. Third, a relaxed significance threshold (P < 1e-5) was used for SNP selection in the MR analyses to increase the number of valid IVs and improve statistical power. This approach has been adopted in previous MR studies involving complex traits and microbiota-related exposures,^50,52 and is considered acceptable in exploratory settings according to a strategy supported by previous methodological literature.^53–55 However, the use of a relaxed threshold may increase the risk of including weak or pleiotropic IVs. To mitigate this concern, we retained only SNPs with F > 10 to ensure sufficient IVs strength, and excluded those associated with known confounders whenever possible. In addition, the leave-one-out analysis suggested that one or more SNPs might disproportionately influence the causal estimates. Nonetheless, no evidence of heterogeneity (Cochran’s Q statistic) or horizontal pleiotropy (MR-Egger intercept and MR-PRESSO global test) was observed, supporting the robustness of our results. These findings should be interpreted with caution. Future studies using larger GWAS datasets and more advanced MR methods are needed to validate our conclusions. For example, multivariable MR, summary-data-based MR to explore the relationships among genetic variants, exposures, and outcomes,^56,57 and Bayesian co-localization analysis to verify shared causal variants and strengthen causal inference⁵⁸ may offer further insights.

Conclusions

In summary, this study highlights the protective effect of species Parabacteroides merdae against OSA. 2-hydroxypalmitate may act as a partial mediator in the association between species Parabacteroides merdae and OSA. These findings provide novel insights into the mechanisms underlying OSA and suggest potential therapeutic targets, offering promising directions for future research and clinical interventions.

Abbreviations

OSA, Obstructive sleep apnea; MR, Mendelian randomization; IVs, instrumental variables; GWAS, genome-wide association studies; SNPs, single-nucleotide polymorphisms; FDR, false discovery rate; IVW, inverse variance weighted; P_FDR, P values adjusted for false discovery rate; HMDB, Human Metabolome Database; CSA, central sleep apnea; LD, linkage disequilibrium; FUMA, functional mapping and gene annotation; MR-PRESSO, the MR-Pleiotropy Residual Sum and Outlier; OR, odds ratios; CI, confidence intervals; SBP, systolic blood pressure; FA2H, Fatty acid 2-hydroxylase; PD, Parkinson’s disease; PSG, polysomnographic.

Data Sharing Statement

The datasets supporting the conclusions of this article are available in IEU open GWAS project repository (https://www.ebi.ac.uk/gwas/). Details regarding the GWAS on OSA can be accessed through the following link: https://r10.risteys.finngen.fi/endpoints/G6_SLEEPAPNO/.

Ethics Approval and Consent to Participate

All data in this study were derived from publicly accessible GWAS using anonymized summary-level datasets. As this research exclusively analyzed de-identified aggregate data without involving individual participants, sensitive personal information, or commercial interests, ethical approval was formally waived by the Ethics Committee of Beijing Friendship Hospital, Capital Medical University (Approval No.: 2025-P2-115). This study was conducted in full compliance with the Declaration of Helsinki and relevant national ethical regulations.

Acknowledgments

We extend our sincere gratitude to the authors and participants of all GWAS studies whose summary statistics data were utilized in this research.

Author Contributions

Xiaona Wang: Conceptualization, Data Curation, Formal analysis, Funding acquisition, Investigation, Methodology, Software, Validation, and Writing – original draft. Ranran Zhao, Jia Guo, and Ke Yang: Data Curation, Formal analysis, Investigation, Methodology, Validation, and Writing – review & editing. Bo Xu: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Software, Supervision, and Writing – review & editing. All authors made significant contributions to the study, approved the final manuscript for submission, agreed on the choice of journal, and take full responsibility for the integrity of the work.

Funding

This work was supported by the Capital’s Funds for Health Improvement and Research (2024-2-1101 20240402105353, China) and the Seed Program of Beijing Friendship Hospital (YYZZ202235).

Disclosure

The authors declare that they have no competing interests.

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Is reducing the risk of eating disorders with single session interventions a hype or a promise? Tracey Wade at the Flinders University Institute for Mental Health and Wellbeing investigates

What is a single session intervention?

Single session interventions (SSIs) are brief, structured, goal-oriented programs, following evidence-based approaches to create meaningful change to mental health in a single encounter.

What evidence supports SSIs?

An umbrella review of 24 systematic reviews and meta-analyses of SSIs was published between 2007 and 2024. ⁽¹⁾ Only seven included trials of digital or paper-based self-guided SSIs; the remainder focused on face-to-face interactions. Overall, SSIs showed a small, significant positive effect across outcomes and age groups.

Compared to anxiety, depression and substance use, the evidence supporting SSIs for disordered eating is sparse: only two of the systematic reviews included in the umbrella review included studies evaluating eating problems, and only one reported positive effects in adolescents and adults.

What is the rationale for use in the prevention of eating disorders?

So far, insufficient evidence exists to support the use of unguided digital SSIs in the prevention of disordered eating. The rationale for further investigation, however, does exist, as shown in the Figure. Significantly, SSIs may successfully decrease dietary restriction, a key risk factor for the development of disordered eating. Dietary restriction refers to consciously trying to cut back the overall amount eaten to influence shape or weight.

Two studies show a decrease in dietary restriction after completing a SSI. One showed a reduction in restrictive eating in depressed adolescents at three-month follow-up compared to a control condition when either completing a SSI on Behavioural Activation (doing activities that are considered pleasant or display some mastery) or an introduction to the brain and a lesson on neuroplasticity. ⁽²⁾ The second showed a decrease in dietary restriction in adults (mean age of 27.99 years) seeking treatment for an eating disorder, using adapted versions of the two SSIs from the previous study ⁽³⁾ (shown in figure 1).

What questions need to be answered?

A variety of questions that need to be addressed in terms of the usefulness of SSIs for the prevention of eating disorders are listed in table 1. ^(4,5)

Our current research

Our research, funded by a National Mental Health and Research Council Investigator Grant (2025665), has developed nine SSIs on a smartphone app. We consulted young people and members of our Expert Advisory Group (people with lived experience, significant others, and clinicians and researchers specialising in eating disorders) to ensure that the content and features were as engaging as possible. ⁽⁶⁾

Young people aged 14–25 years old with elevated weight concern will be randomised to one of nine SSIs tackling risk factors for disordered eating or a control condition. The content of each SSI is described below. This important research will help better understand the role SSIs can play in reducing the risk of eating disorders in youth.

References

1. Schleider JL, Zapata JP, Rapoport A., et al. (2025). Single-Session Interventions for Mental Health Problems and Service Engagement: Umbrella Review of Systematic Reviews and Meta-Analyses. Annual Review of Clinical Psychology, 21(1), 279–303.
2. Schleider JL., Mullarkey MC, Fox KR, et al. (2022). A randomized trial of online single-session interventions for adolescent depression during COVID-19. Nature Human Behaviour, 6(2), 258–268.
3. Wade TD, Waller G. (2025). Transdiagnostic single session interventions identify rapid versus gradual responders and inform therapy personalisation before commencing therapy for eating disorders. Cognitive Behaviour Therapy.
4. O’Dea B & de Valle MK. (2025). Trial, Error, and Insight: Using the Pilot Study of the HOPE Program to Inform Next Steps for Digital Single-Session Research for Eating Disorders. International Journal of Eating Disorders, 10.1002/eat.24487.
5. Thompson M, Radunz M, Wade TD, Balzan RP. (2024). Bridging the gap: Can single session interventions help enhance mental health treatment delivery for young people in Australia? Australian & New Zealand Journal of Psychiatry, 58(10):829-830.
6. Pellizzer ML, Pennesi J-L, Radunz M, Zhou Y, Wade TD. (2025). Piloting single session interventions in a sample of weight-concerned youth: Study protocol for a randomised controlled trial. Body Image, 54, 101945.

The sixth edition of the European Research and Innovation (R&I) Days will take place on 16-17 September 2025 at The Square in Brussels, bringing together key players from across Europe’s research, business, and innovation

Organised by the European Commission, this event will help to shape the future of EU research by fostering dialogue, collaboration, and solutions in areas critical to Europe’s competitiveness and sustainability.

Among the highlights of the 2025 edition will be three groundbreaking projects managed by the European Health and Digital Executive Agency (HaDEA). These projects, funded under the Horizon 2020 programme, focus on advancing research in health, digital innovation, and environmental sustainability, key priorities for the EU’s future.

MAESTRIA: Advancing heart health through AI

A significant project featured at the event is MAESTRIA (Machine Learning Artificial Intelligence Early Detection of Stroke and Atrial Fibrillation). This project is transforming how medical professionals detect and manage atrial cardiomyopathy, a heart condition associated with atrial fibrillation (AF) and stroke.

By combining advanced AI algorithms, medical imaging, and cutting-edge research, MAESTRIA is building the first-ever digital diagnostic platform specifically for atrial cardiomyopathy. The goal is to enable personalised diagnosis, better risk assessment, and more effective treatment options, ultimately reducing complications like AF and stroke.

The project represents a significant leap forward in preventive healthcare, offering scalable tools to enhance patient outcomes and alleviate the burden of cardiovascular disease across Europe.

PERSEPHONE: Robotics for sustainable seep mining

In terms of industrial innovation, PERSEPHONE (Autonomous Exploration and Extraction of Deep Mineral Deposits) is leading efforts to modernise and automate deep mining operations. As demand for raw materials critical to the green and digital transitions grows, Europe is turning to more brilliant, safer, and more sustainable ways to access these resources.

PERSEPHONE is developing compact, energy-efficient autonomous robots capable of exploring deep or abandoned mines. These robotic systems are equipped with sensors and cameras that generate 3D scans of underground environments. The data collected is used to create a digital twin of the mine, enabling precise planning for safe and efficient mineral extraction.

By minimising risks to human workers and reducing environmental impact, PERSEPHONE supports the EU’s efforts to build a resilient supply chain for critical raw materials, essential for clean energy technologies and digital innovation.

eMOTIONAL cities: Designing healthier urban spaces

Another innovative project, eMOTIONAL Cities, recently concluded its mission to understand how urban environments affect people’s emotional and mental well-being. Using a unique device known as the Cities walker backpack, the project gathered real-life biometric data to assess how individuals respond emotionally to different urban settings.

The findings from eMOTIONAL Cities offer valuable insights for urban planners and policymakers aiming to create healthier, more inclusive cities. By linking emotional responses to environmental factors, the project contributes to the design of urban spaces that promote calmness, happiness, and social connection.

R&I days 2025

Attendees of R&I Days 2025 will have the chance to explore these projects in the exhibition area, engage in high-level discussions, and participate in networking opportunities with policymakers, researchers, and innovators.

This year’s event highlights how EU-funded research, under programmes such as Horizon 2020 and Horizon Europe, continues to drive forward solutions in health, digitalisation, and sustainability, paving the way for a stronger, more resilient Europe.

The American Cancer Society (ACS) has published its annual Prostate Cancer Statistics, 2025 report, showing increasing incidence rates alongside slowing declines in mortality rates.¹

Data for the report were collected by the National Cancer Institute and the Centers for Disease Control and Prevention. Population-based incidence data were analyzed through 2021, and mortality data were analyzed through 2023.

Trends in Incidence and Mortality

Overall, the data showed a marked reversal in prostate cancer incidence trends in recent years. Although the incidence rates declined by 6.4% per year from 2007 to 2014, data show that these rates have been increasing by 3.0% annually from 2014 to 2021. This trend has been largely driven by increasing rates of advanced-stages diagnoses, which are climbing by approximately 4.6% to 4.8% per year.

Notably, prostate cancer mortality rates have been decreasing since the 1990s, though the declines have slowed in recent years. In the 1990s and 2000s, mortality rates decreased by 3% to 4% annually. Over the past decade, these rates have waned to approximately 0.6% per year.

According to the report, rates of distant-stage disease are increasing across every age group. Specifically, rates are increasing by about 3% in those younger than 55 years and about 6% among those aged 55 years and older.

The 5-year relative survival rate for distant-stage prostate cancer is 38%, but the rate increases to nearly 100% for men diagnosed with local-stage or regional-stage disease, emphasizing the importance of early detection.

Overall, the ACS estimates that in 2025, there will be 313,780 new cases of prostate cancer and 35,770 deaths due to the disease.

Persistent Disparities

The report also sheds light on persistent and wide racial disparities.

Based on the data, Black men have a 67% higher incidence rate and are 2 times more likely to die from prostate cancer compared with White men. Similarly, Native American men have a 12% higher prostate cancer mortality rate compared with White men, despite having a 13% lower incidence rate.

“Our research highlighting the continued increases in prostate cancer incidence and persistent racial disparities underscores the need for redoubled efforts to understand the etiology of prostate cancer and optimize early detection,” commented lead author Tyler Kratzer, MPH, associate scientist, cancer surveillance research at the ACS, in a news release from the organization.² “At age 50, per ACS guidelines, all men should have a conversation with their health care provider about the benefits and harms of screening, but Black men and those with a family history of prostate cancer should have that conversation at age 45.”

Data also showed that American Indian and Alaska Native (AIAN) men were the most likely racial group to be diagnosed with distant-stage disease (12% vs 8% among White men). According to the authors, this finding “at least in part reflect[s] lower screening prevalence compared with other men.”

Further, data showed that prostate cancer mortality rates are highest among Black men at 36.9 per 100,000 population, following by 20.6 deaths per 100,000 among AIAN men, 18.4 deaths per 100,000 among White men, 15.4 deaths per 100,000 among Hispanic men, and 8.8 deaths per 100,000 among Asian American and Pacific Islander men.

By geographic location, the highest prostate cancer mortality rates were observed in Washington DC (27.5 deaths per 100,000 population) and Mississippi (24.8 deaths per 100,000 population), both of which have a high proportion of Black residents.

The authors noted, “Increases in advanced diagnosis and persistent disparities highlight the need for redoubled efforts to optimize early detection and address barriers to equitable outcomes, including improved access to high-quality health care for all men.”

Ongoing Legislative Efforts

The Prostate-Specific Antigen Screening (PSA) for High-risk Insured Men (HIM) Act (H.R. 1300/S. 297) is a bipartisan bill in Congress aimed at improving access to prostate cancer screening. Specifically, this bill would waive cost-sharing requirements (deductibles, copays, and coinsurance) for prostate cancer screening tests for men who are at high-risk for the disease.

The ACS Cancer Action Network, the advocacy affiliate for the ACS, has expressed strong support for the bill.

“Out-of-pocket costs such as co-pays can be a barrier to accessing early detection,” explained Lisa A. Lacasse, president of ACS CAN, in the news release.² “No one should be at a disadvantage against cancer. The PSA Screening for HIM Act will help remove a major obstacle that can prevent those at high risk for the disease from getting the screening tests they need to find prostate cancer at the earliest, most treatable stage.”

She added, “We urge the House and the Senate to pass this legislation to help reduce prostate cancer disparities and save more lives.”

REFERENCES

1. Kratzer TB, Mazzitelli N, Star J, et al. Prostate cancer statistics, 2025. CA: A Cancer Journal for Clinicians. 2025. doi:10.3322/caac.70028

2. New ACS Prostate Cancer Statistics Report: Late-stage incidence rates continue to increase rapidly as mortality declines slow. News release. American Cancer Society. September 2, 2025. Accessed September 2, 2025. https://www.prnewswire.com/news-releases/new-acs-prostate-cancer-statistics-report-late-stage-incidence-rates-continue-to-increase-rapidly-as-mortality-declines-slow-302543895.html