Glaucoma, Vision & Longevity: Supplements & Science

Discover the latest science on glaucoma, vision, and longevity. Each episode explores evidence-based supplements for eye health, healthy aging, and lifespan extension. Original articles backed by real scientific research. All source links available at visualfieldtest.com, where you can also take a free visual field test online. Subscribe for weekly insights on glaucoma treatment, glaucoma prevention, vision supplements, and longevity research that could protect your sight and extend your healthspan. MEDICAL DISCLAIMER: This podcast is for educational and informational purposes only. It is not intended as medical advice, diagnosis, or treatment. The content presented should not replace professional medical consultation. Glaucoma is a serious condition that can lead to permanent vision loss. Never stop or modify prescribed treatments without consulting your ophthalmologist or healthcare provider. The supplements and research discussed are for informational

Glaucoma, Vision & Longevity: Supplements & Science is a health podcast hosted by VisualFieldTest.com, with 259 episodes on record and a Required Pod Score of 80.

VisualFieldTest.com hosts Glaucoma, Vision & Longevity: Supplements & Science, a health show with 259 episodes published.

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  Glaucoma, Vision & Longevity: Supplements & Science

  Your Eye Pressure May Look Fine at the Doctor — While Hidden Spikes at Home Still Drive Glaucoma Progression

  Oct 4, 202630 min

  This audio article is from VisualFieldTest.com . Read the full article here: https://visualfieldtest.com/en/your-eye-pressure-may-look-fine-at-the-doctor-while-hidden-spikes-at-home-still-drive-glaucoma-progression Test your visual field online: https://visualfieldtest.com Support the show so new episodes keep coming: https://www.buzzsprout.com/2563091/support Excerpt: Your Eye Pressure May Look Fine at the Doctor—While Hidden Spikes at Home Still Drive Glaucoma Progression Yes: a reassuring pressure reading in the clinic can miss pressure changes that happen during the rest of the day. A study published online on September 30, 2026, found that two new measures of pressure above a patient’s own target were associated with faster visual-field decline when calculated from home readings—but not from office readings. The result is important, but it does not prove that pressure spikes caused the damage, or that home monitoring prevents it. () The key idea is simple: glaucoma care may learn more from a pattern of pressure readings than from one reading at an appointment. But today’s home devices take occasional readings, not continuous measurements, and the study’s “pressure burden” measures are still early research tools. What the September 30, 2026 study found The study, “In-office and remote intraocular pressure metrics associated with visual field progression in treated open-angle glaucoma,” compared pressure measurements taken at home with measurements recorded during routine clinic care. It asked whether different ways of summarizing pressure were associated with how quickly visual-field test results changed over time. () Its most notable finding was that average pressure and maximum pressure were not significantly associated with visual-field decline in this sample—whether measured at home or in the clinic. However, two measures that considered pressure relative to each patient’s individual treatment target—average and total excess above that target—were associated with faster decline in home readings. That distinction matters. This was a retrospective association study, not a trial that assigned patients to home monitoring or showed that reducing pressure burden prevents progression. The study can identify a signal worth investigating; it cannot establish cause and effect. Reconstructing the study population and measurements The researchers reviewed records from 397 treated patients with 777 eyes at Johns Hopkins University and the University of Utah. The final analysis included 94 patients and 150 eyes after exclusions. Patients had used an iCare HOME rebound tonometer between October 2018 and September 2024. The analysis focused on patients with open-angle glaucoma and excluded several other glaucoma types, including angle-closure, traumatic, and uveitic glaucoma. () Who was included? For the full table, please open this article on visualfieldtest.com. The mean visual-field result indicates a wide spread of glaucoma severity, not one uniform stage. The paper does not report how many eyes fell into each stage, so the average cannot be used to reconstruct those percentages. () What treatment were patients receiving? All participants were treated for glaucoma, and the researchers restricted the clinical record data to periods when treatment was consistent with the home-measurement period. Most patients were using at least one pressure-lowering eye drop. Before the home-monitoring period, many eyes had also undergone procedures, including cataract surgery, selective laser trabeculoplasty, trabeculectomy, or micro-invasive glaucoma surgery. These procedure categories can overlap. () Each patient’s target pressure was set by the treating glaucoma specialist as part of routine care. The target was intended to reflect factors such as disease severity, structural damage, starting pressure, and the clinician’s judgment. The paper analyzed target-based measures in 142 eyes, but the accessible report does not give a cohort-wide average target pressure. In other words, it does not support a claim that the group’s mean target was a particular number. That missing average is important: a target is not a universal biological boundary. It is a clinical estimate that should be revisited if the eye continues to worsen. Glaucoma guidelines likewise describe target pressure as individual rather than one fixed number for everyone. () How much home and clinic monitoring was done? Patients were trained to use the iCare HOME and instructed to take readings at least four times during waking hours: from waking to 10 a.m., 10 a.m. to 2 p.m., 2 p.m. to 6 p.m., and 6 p.m. until sleep. Each included eye had at least seven days of home readings; readings beyond ten days were excluded from the analysis. Patients actually made a median of 4.9 home measurements per day per eye, with an average monitoring period of 8.6 days (standard deviation 1.0). Multiplying those summary figures gives a rough estimate of about 42 readings per eye, but that is a calculation—not the reported total for every participant. () Clinic pressure records included a median of 15.5 visits per eye, spanning nearly five years on average. Office readings came from routine care and could use Goldmann applanation tonometry, a clinic iCare rebound device, or a Tono-Pen. Thus, the clinic data were not all collected with one instrument. () Visual-field progression was estimated from at least three reliable Humphrey visual-field tests using the 24-2 SITA program. Eyes were excluded if there were fewer than three reliable tests or if the first-to-last test interval was less than one year. The average eye had 5.82 visual-field tests (standard deviation 2.82) over a mean follow-up of about 6 years. The mean visual-field mean-deviation slope was −0.49 decibels per year (standard deviation 0.67); the median was −0.18 decibels per year. () The pressure readings themselves The average pressure was similar across home and office measurements: For the full table, please open this article on visualfieldtest.com. The average pressure did not differ significantly across methods (p = 0.62). Other standard summaries did differ across the three measurement contexts. The difference between the pooled home readings and the daily home averages is especially useful to understand: averaging by day compresses extremes. A high or low reading on one day contributes less to the daily-average summary than it does to the all-readings-pooled summary. () The study’s table reports the office standard deviation as 2.91 mmHg with a standard deviation of 2.52; the prose gives 2.62. That small discrepancy does not change the main finding, but it is worth noting when reconstructing the dataset. What PMAT, AIE, and TIE mean The study adapted an idea from continuous glucose monitoring: it asked not only “What is the average?” but also “How often, and by how much, did a reading exceed a chosen limit?” Percentage of measurements above threshold (PMAT): The share of readings above a chosen pressure. If 14 of 100 readings are above the limit, the PMAT is 14%. Average intraocular pressure excess (AIE): How far above the threshold the above-threshold readings were, on average. If readings exceed a 15 mmHg threshold by 1, 2, and 3 mmHg, their average excess is 2 mmHg. Total intraocular pressure excess (TIE): A combined measure of how often and how far readings exceeded the threshold. Repeated or larger exceedances contribute more than rare, small exceedances. The study calculated these measures at 12, 15, 18, and 21 mmHg, and at each patient’s physician-set target. It also calculated home measures in two ways: across the entire monitoring period (“absolute”) and as daily summaries averaged over the monitoring period (“daily”). () Important limitation: PMAT is the percentage of measurements above a threshold, not the percentage of hours or days above it. TIE is not a direct measurement of a continuous “mmHg-hours” pressure dose. Four or five sampled readings in a day cannot reveal exactly how long pressure stayed high between readings—or what happened during sleep. The exact statistical relationships reported A negative coefficient means that a higher pressure metric was associated with a more negative, faster-worsening visual-field slope. It does not mean that raising that metric by one unit causes that amount of damage. Standard pressure measures None of the study’s standard pressure summaries was significantly associated with visual-field slope. The reported coefficients, confidence intervals, and p-values were: For the full table, please open this article on visualfieldtest.com. These are results from the published study’s generalized estimating equation models, which accounted for the fact that some patients contributed both eyes. The models were described as unadjusted association models. () Threshold-based measures The strongest and most consistent signal was for home AIE and TIE at the patient-specific target: For the full table, please open this article on visualfieldtest.com. At fixed thresholds of 12, 15, and 18 mmHg, PMAT, AIE, and TIE were not reported as significantly associated with visual-field progression. AIE at 21 mmHg was also not significant. Office-based versions of the threshold metrics were not significantly associated with progression; office AIE at the individualized target came close but did not meet the conventional significance cutoff (p = 0.053). () The published article’s narrative does not state the exact coefficient and p-value for every nonsignificant threshold-based resul Support the show

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  Glaucoma, Vision & Longevity: Supplements & Science

  A 360° Glaucoma Procedure Beat Simple Needle Goniotomy at 2 Years — How Effective Is GATT Really?

  Sep 30, 202623 min

  This audio article is from VisualFieldTest.com . Read the full article here: https://visualfieldtest.com/en/a-360-glaucoma-procedure-beat-simple-needle-goniotomy-at-2-years-how-effective-is-gatt-really Test your visual field online: https://visualfieldtest.com Support the show so new episodes keep coming: https://www.buzzsprout.com/2563091/support Excerpt: A 360° Glaucoma Procedure Beat Simple Needle Goniotomy at 2 Years — How Effective Is GATT Really? Introduction Opening the eye’s natural drainage pathway all the way around sounds as though it should lower pressure more than opening only one small section. A randomized trial published on September 28, 2026 offers a rare direct comparison: gonioscopy-assisted transluminal trabeculotomy, which opens the drainage pathway through 360 degrees, versus a 90-degree procedure using a bent needle. At two years, the full-circle procedure had better average pressure and medication results. But the trial does not prove that treating more degrees alone caused the advantage. The treatments differed in both extent and technique, and the study was small. Its results support gonioscopy-assisted transluminal trabeculotomy as a promising option for selected patients—not as a guarantee of very low pressure or freedom from future treatment. The 2026 randomized trial by Ayub and Costa () What the randomized trial actually studied The trial enrolled 45 eyes from 34 adults at two centers in Brazil. Participants had mild-to-moderate primary open-angle glaucoma, were 40 to 80 years old, had already undergone cataract surgery, and were using no more than three pressure-lowering medicines. Their treated pressure had to be at least 18 millimeters of mercury at two visits. The researchers assigned 23 eyes to gonioscopy-assisted transluminal trabeculotomy (GATT) and 22 to bent ab interno needle goniotomy (BANG). Patients were masked to their procedure, but the surgeons and examiners could identify it. The same experienced surgeon performed all operations. In the full-circle procedure, the surgeon passed a suture around Schlemm’s canal and pulled it through, opening the trabecular meshwork through 360 degrees. The needle procedure removed a strip of tissue over approximately 90 degrees of the nasal angle. So this was not a comparison of the same operation at two different widths: both the instrument and the amount of tissue treated differed. Trial methods and eligibility criteria () Baseline pressure: two different starting points Before surgery, the average pressure while patients were still using their medicines was 19.87 millimeters of mercury in the GATT group and 21.18 in the BANG group. After a medication washout, the averages were much higher and almost identical: 25.43 and 25.55, respectively. The difference between the groups’ treated pressures was not statistically significant, but it matters when interpreting percentage reductions. The average medication burden was also similar: 2.35 medicines in the GATT group and 2.41 in the BANG group. Participants were mostly older adults, with an average age of about 73; the average visual-field loss was mild, and all eyes were pseudophakic, meaning they had an artificial lens after cataract surgery. Baseline data reported for the trial () Two-year results: GATT did better, but the details matter At 24 months, average pressure was 15.41 millimeters of mercury after GATT and 17.79 after BANG. The paper reported reductions from the on-treatment baseline of 22.44% and 16.0%, respectively. Because the GATT group started with a treated average about 1.3 millimeters lower, the difference in the absolute change from those baselines was smaller than the endpoint-pressure gap: approximately 4.46 millimeters of reduction for GATT and 3.39 millimeters for BANG, or roughly 1.1 millimeters more reduction for GATT. The clearest difference was medication use. At two years, the GATT group averaged 0.71 medicines, down from 2.35, while the BANG group averaged 2.26, down from 2.41. That is a reported reduction of 69.78% versus 6.22%. Eleven GATT eyes and two BANG eyes were medication-free. The trial’s “complete success” measure was stricter than simply reaching a particular pressure: an eye needed to be at or below 18 millimeters of mercury, have at least a 20% reduction, and be off medication. “Qualified success” used the same pressure criteria but allowed medication, without increasing the number used at baseline. At 24 months, the paper reported 55.0% complete success after GATT versus 4.5% after BANG. Qualified success was 64.7% versus 13.6% in the article’s results text; its abstract gives 11.4% for BANG. That small inconsistency is worth noting rather than smoothing over. Four GATT eyes reached 12 millimeters of mercury or lower, compared with none after BANG. Four out of 23 randomized GATT eyes is about 17%; four out of 17 GATT eyes completing follow-up is about 24%. Those are simple count-based proportions, not a robust estimate of what an individual patient’s chance would be. The trial’s Kaplan–Meier estimates and its raw eye counts use different methods and denominators. Two-year pressure, medication, target, and success results () Follow-up measurements Patients were scheduled for visits on postoperative days 1, 7, 15, 30, 60, 90, 180, 360, 540, and 720. The journal article’s searchable main text gives exact average pressures at inclusion and at 12 and 24 months. Earlier visit averages were also reported in a conference abstract from the same study. The table below shows those available interim values, with the peer-reviewed journal article’s numbers used for the final 24-month row. The conference report and final paper differ slightly in some late values; the final paper should take precedence. Neither source’s summary gives exact day-15 and day-60 averages. For the full table, please open this article on visualfieldtest.com. Pressure is in millimeters of mercury; figures after ± are standard deviations. The day-1 through day-540 values come from the conference report; final 24-month values come from the journal article. Conference report Final journal article () The pressure rise at day 30 in both groups is a reminder that early postoperative readings can fluctuate. In this trial, medicines were not restarted until day 30; afterwards, treatment was reintroduced under a specified protocol if pressure remained above 18 at consecutive visits. Early and late averages therefore need to be interpreted in light of the medication schedule, not as measurements taken under identical conditions at every visit. Trial follow-up and medication protocol () Loss to follow-up, additional procedures, and safety By 24 months, 19 of 22 BANG eyes and 17 of 23 GATT eyes had completed follow-up. Three BANG eyes left the protocol because they needed additional glaucoma surgery. Six GATT eyes did not complete it: four needed additional surgery, one had a retinal detachment at day 30, and one patient died. Seven eyes had a reoperation: three BANG eyes and four GATT eyes. All three BANG reoperations were bleb needlings; in the GATT group, three were needlings and one was a trabeculectomy. The trial reported no statistically significant difference between groups. Needling is a procedure to revise an existing filtering bleb, so these events should not be read as seven newly created blebs from the angle operations themselves. The study’s failure definition included additional glaucoma surgery. Follow-up and reoperation results () At least one complication was recorded in 12 BANG eyes (54.5%) and 17 GATT eyes (73.9%). Iris damage was the most common complication during surgery, and transient hyphema—blood in the front chamber of the eye—was the most common early postoperative problem. One GATT eye had a total hyphema on day one; it cleared within a week without intervention. The retinal detachment occurred 30 days after GATT, but one event in a small study cannot establish that the operation caused it. The article also reported a BANG eye with persistent corneal edema and cystoid macular edema associated with vitreous prolapse and a poorly positioned artificial lens. Some eyes in both groups showed notable reductions in corneal endothelial-cell counts. At two years, average counts were 1,561.88 cells per square millimeter after GATT and 1,477.56 after BANG; the difference between groups was not statistically significant. At least a 20% reduction occurred in 30.4% of GATT eyes and 22.7% of BANG eyes. These small-sample findings warrant follow-up; “no significant difference” does not establish that either procedure has no effect on the cornea. Complications and endothelial-cell results () Does opening more degrees produce more pressure reduction? Why a 360-degree opening might help The trabecular meshwork is part of the eye’s main fluid-drainage route. In open-angle glaucoma, resistance in this pathway is often too high. GATT opens the meshwork around the full circumference of Schlemm’s canal, whereas the trial’s BANG procedure treated about 90 degrees. A wider opening could help by reducing resistance over a larger area, reaching more of the eye’s drainage channels, and providing alternative routes if some regions drain poorly. Outflow is uneven around the eye, so a small opening may happen to reach a less useful region—or it may reach a particularly effective one. Healing and scarring could also affect how long any opening stays useful. These are plausible explanations, not mechanisms proven by this trial. Trial discussion of treatment extent and regional drainage () The broade Support the show

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  Glaucoma, Vision & Longevity: Supplements & Science

  The Largest Glaucoma Genome Study Yet Found 29 New Genetic Clues — Could Existing Drugs Target Some of Them?

  Sep 29, 202627 min

  This audio article is from VisualFieldTest.com . Read the full article here: https://visualfieldtest.com/en/the-largest-glaucoma-genome-study-yet-found-29-new-genetic-clues-could-existing-drugs-target-some-of-them Test your visual field online: https://visualfieldtest.com Support the show so new episodes keep coming: https://www.buzzsprout.com/2563091/support Excerpt: The Largest Glaucoma Genome Study Yet Found 29 New Genetic Clues — Could Existing Drugs Target Some of Them? The short answer is possibly—but the study did not identify a ready-made glaucoma drug. It found genetic associations that point toward several plausible disease mechanisms, including extracellular-matrix remodeling, aqueous-fluid outflow, cellular stress responses and retinal ganglion-cell survival. Among the four highlighted drug targets, the mammalian target of rapamycin pathway has the strongest combination of genetic, experimental and drug-delivery evidence. Even there, the right direction and amount of treatment remain uncertain. A critical distinction: a gene associated with glaucoma is not automatically a treatment target. The genetic finding may not reveal what the variant does, which eye cell it affects, or whether a drug should increase or decrease the gene’s activity. The paper itself cautions that, for most of these associations, pharmacological direction cannot yet be predicted. () This article distinguishes established evidence—what the studies directly report—from strong inference and informed speculation about possible treatments. What the study actually found The Communications Biology paper was published online on September 23, 2026. Its early-access version is peer reviewed but still described by the publisher as an article in press that may receive further edits. It is a genetic-association study, not a clinical trial. () Cohorts and ancestry For the full table, please open this article on visualfieldtest.com. The discovery and replication sequencing analyses were restricted to participants of European ancestry. The paper says 464,778 European-ancestry participants made up about 95% of its UK Biobank whole-genome-sequencing resource. The All of Us replication sample was also European ancestry. FinnGen represents a Finnish population, while the Million Veteran Program is ancestrally diverse overall, but the study’s cited open-angle-glaucoma analysis used its European-ancestry results. Thus, the large headline sample does not mean that the principal discovery and replication findings were tested across equally large, diverse ancestry groups. () The authors also report a preliminary UK Biobank pan-ancestry analysis that found 15 additional significant variants—11 rare and four common. They had external replication evidence for only one of those, a common variant near ADGRB2. The authors note that many signals were not present or testable in current external datasets. () Important caveat: the replication phenotype was broader than the discovery phenotype In UK Biobank, cases were identified from self-reported glaucoma and medical-record codes, with secondary forms excluded. In All of Us, the researchers used medical-record codes for glaucoma because that definition had more cases and greater statistical power than the smaller primary open-angle glaucoma-specific definition. This means the replication check was not a perfect match to the primary open-angle glaucoma discovery phenotype. FinnGen used a primary open-angle glaucoma endpoint; the Million Veteran Program used an open-angle-glaucoma phenotype. () That does not invalidate the replication evidence, but it makes the word “replication” less straightforward than it may sound. A signal that appears in a broader glaucoma group is supportive; it is not the same as reproducing the exact association in an independently diagnosed primary open-angle glaucoma cohort. Sequencing, variant thresholds and statistical significance The UK Biobank genomes were sequenced on an Illumina NovaSeq 6000 platform at an average depth of about 32.5-fold. The researchers used GraphTyper-called single-nucleotide variants and insertions or deletions, applied quality filters, and used REGENIE, a method designed to account for population structure and relatedness. Single-variant analyses included variants with a minor allele count of at least five and tested variants within genes, including a one-kilobase margin; intergenic variants were excluded. () The paper categorizes variants with an effect-allele frequency below 1% as rare. For single-variant tests, genome-wide significance was P Support the show

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  Glaucoma, Vision & Longevity: Supplements & Science

  Can Air Pollution Damage the Optic Nerve? A Large Review Links PM2.5 to Higher Glaucoma Risk

  Sep 27, 202625 min

  This audio article is from VisualFieldTest.com . Read the full article here: https://visualfieldtest.com/en/can-air-pollution-damage-the-optic-nerve-a-large-review-links-pm2-5-to-higher-glaucoma-risk Test your visual field online: https://visualfieldtest.com Support the show so new episodes keep coming: https://www.buzzsprout.com/2563091/support Excerpt: Can Air Pollution Damage the Optic Nerve? A Large Review Links PM2.5 to Higher Glaucoma Risk The short answer: Long-term exposure to fine particulate matter, or PM2.5, is associated with glaucoma in several populations, and there are plausible ways pollution could affect the eye’s blood supply and nerve cells. But the new European Society of Cataract and Refractive Surgeons analysis is available publicly mainly as a conference announcement—not a full methods paper. Its headline figures cannot yet be checked or translated reliably into a specific change in air pollution concentration. The evidence makes PM2.5 a credible candidate modifiable risk factor, not an established cause of glaucoma. It is reasonable to reduce avoidable exposure when doing so is practical, especially for general health. There is no evidence that an air purifier prevents glaucoma or slows vision loss. What the ESCRS 2026 analysis actually reported The study, presented on September 14, 2026, was titled “Smog and sight: epidemiological evidence on the link between air pollution and ocular aging: a comprehensive systematic review and meta-analysis.” The European Society of Cataract and Refractive Surgeons reported that it included 41 observational studies and data from millions of people, described as coming mainly from East Asia and the United Kingdom. The review considered glaucoma, cataract, and age-related macular degeneration, and examined fine and larger particulate matter, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide. () The 41 studies were not reported as 41 glaucoma studies. They were the total for the review’s eye-disease outcomes. The public announcement does not give the number of glaucoma studies, the exact participant count, the search dates, study-selection rules, pooled model details, pollutant-specific concentration ranges, confidence intervals, or study-quality ratings. The cited conference abstract is identified by number, but I could not verify those details in a full accessible report. The headline findings therefore warrant interest, but they cannot yet be audited in the same way as a full journal article. () The ESCRS announcement says that people in the most polluted areas had up to 70% higher odds of glaucoma than those in the least polluted areas. It also reports that glaucoma risk rose by about 8% for each “meaningful step” up in pollution exposure. The announcement does not define that step as an interquartile-range increase, provide a common PM2.5 increment in micrograms per cubic meter, or give a confidence interval for the 8% figure. So the claim that the ESCRS analysis found a pooled odds ratio of 1.08 per interquartile-range increase is not verifiable from its public summary. () A separate 2026 glaucoma-specific review provides useful context, but it is not the ESCRS review. Its abstract reports 18 observational studies, with eight contributing to a PM2.5 meta-analysis. The pooled relative-risk estimate was 1.12, with substantial between-study variation (I² = 78.7%). That result supports an association, but the abstract does not provide a single shared concentration increment that would let readers convert the estimate into one universal number of micrograms per cubic meter. () What does “per interquartile-range increase” mean? The interquartile range is the difference between the 75th-percentile and 25th-percentile exposure levels within a study. An estimate “per interquartile-range increase” means comparing an exposure one study-specific interquartile range higher with the exposure before that increase. That is useful for analyzing each study, but it does not create a common dose across studies. An interquartile range of about 1 microgram per cubic meter is very different from one of 2.9 micrograms per cubic meter. A percentage increase “per interquartile range” therefore cannot be translated into a fixed PM2.5 concentration unless the study’s own interquartile range is known. Examples from published research illustrate the problem: A United Kingdom Biobank analysis reported an odds ratio of 1.06 per interquartile-range increase in PM2.5; the increment was about 1.1 micrograms per cubic meter in that analysis. A related analysis found higher odds of self-reported glaucoma and differences in retinal structure. () A Canadian Longitudinal Study on Aging analysis reported an odds ratio of 1.14 per interquartile-range increase, with the increment reported as about 2.9 micrograms per cubic meter in a systematic review of the study. () A large rural Chinese study reported an odds ratio of 1.07 per 10 micrograms per cubic meter—a fixed increment, not an interquartile range. () A Taiwanese study used yet another measure: cumulative exposure categories based on PM2.5 levels multiplied by months of exposure. Its highest category had an odds ratio of 1.67 compared with its reference category. Those categories are not equivalent to a person breathing an annual average that is a fixed number of micrograms per cubic meter higher. () Bottom line: An interquartile-range result is meaningful only alongside the underlying exposure range. The ESCRS summary does not report enough information to translate its 8% figure into a dependable concentration change. Odds, relative risk, and absolute risk are different The ESCRS summary’s “70% higher odds” is a relative comparison between exposure groups, not a 70-percentage-point increase in the chance that any one person will get glaucoma. An odds ratio compares the odds of an outcome in one group with the odds in another. A relative risk compares their probabilities. For uncommon outcomes, odds ratios and relative risks can be numerically close, but they are not identical. An individual’s absolute risk also depends on their starting risk, which is affected by factors such as age, family history, and other health characteristics. For illustration only: if a group’s starting risk were 2%, an odds ratio of 1.67 would correspond to a risk of about 3.3%, not 72%. This calculation is not an estimate of the risk in the Taiwanese study or in a particular patient; it simply shows why “70% higher odds” does not mean “70% chance of glaucoma.” In the United Kingdom prospective cohort discussed below, roughly 2% of participants developed glaucoma over a median 12.8 years, but that rate should not be applied to every population. () The “up to 70%” figure should therefore be read as a highest-versus-lowest exposure comparison reported in the conference summary, not as a typical effect for every rise in pollution. A specific underlying Taiwanese study found an odds ratio of 1.67 for its highest cumulative exposure category versus its reference category; the available ESCRS summary does not establish that this was the source of its 70% figure or give enough detail to equate the comparisons. () What do the underlying studies show? The evidence is not limited to the conference announcement. Several earlier studies reported positive associations, although they differ in how they measured pollution and glaucoma. Studies with stronger or more objective designs The most useful epidemiological support comes from studies that follow people over time or use clinical examinations rather than relying only on self-report: United Kingdom Biobank, 12-year follow-up: Among 448,253 participants in the particulate-matter analysis, 8,999 incident glaucoma cases were identified over a median 12.8 years. After the study’s broadest adjustment, each study-specific interquartile-range increase in PM2.5 was associated with a 3% higher hazard of glaucoma (hazard ratio 1.03, 95% confidence interval 1.00–1.06). People in the highest exposure quartile—10.57 to 21.31 micrograms per cubic meter—had a 10% higher hazard than those in the lowest quartile—8.17 to 9.29 micrograms per cubic meter. The continuous estimate was small and just met the conventional threshold for statistical significance; the quartile comparison was also modest. () Rural China: In a cross-sectional study of 33,701 adults, each 10-microgram-per-cubic-meter higher PM2.5 level was associated with an odds ratio of 1.07 for glaucoma, with a confidence interval reaching 1.00. The same study reported a larger estimate for primary angle-closure glaucoma, illustrating that subtype findings may differ. () Canada: In the Canadian Longitudinal Study on Aging, higher PM2.5 was associated with glaucoma after adjustment for sociodemographic and health factors. A positive association was also reported in a model that included multiple pollutants, although the study was cross-sectional and its outcomes included self-reported diagnoses. () United Kingdom Biobank, earlier analyses: An earlier analysis found higher odds of self-reported glaucoma with greater PM2.5 exposure. Because exposure and glaucoma status were assessed in a population-based cohort rather than through long-term follow-up of new diagnoses, it cannot establish which came first. () These findings are directionally consistent: several studies found more glaucoma diagnoses or glaucoma-related structural changes at higher PM2.5 exposure. But studies differ in design and outcome, and the 2026 glaucoma-specific review reported high heterogeneity. The po Support the show

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  Glaucoma, Vision & Longevity: Supplements & Science

  AI Found 21 New Genetic Clues to Glaucoma — Could Some Become Future Drug Targets?

  Sep 26, 202619 min

  This audio article is from VisualFieldTest.com . Read the full article here: https://visualfieldtest.com/en/ai-found-21-new-genetic-clues-to-glaucoma-could-some-become-future-drug-targets Test your visual field online: https://visualfieldtest.com Support the show so new episodes keep coming: https://www.buzzsprout.com/2563091/support Excerpt: AI Found 21 New Genetic Clues to Glaucoma — Could Some Become Future Drug Targets? A study published in npj Genomic Medicine on September 19, 2026 used artificial intelligence to look for glaucoma-related patterns in optical coherence tomography scans, then tested those patterns against genetic data. The researchers reported 21 genetic loci not previously linked to glaucoma, and prioritized 11 genes that might help explain why glaucoma damages the eye. Five of those genes had not previously been reported in glaucoma research. () The work’s main advance is not that artificial intelligence diagnosed glaucoma better. It is that the researchers used measurable patterns of retinal damage—rather than a simple “glaucoma” or “no glaucoma” label—to search for genetic clues. That approach produced a richer biological picture, including a particularly promising signal involving RSPO2 and Wnt signaling in cells that help drain fluid from the eye. But these are genetic leads, not tested glaucoma treatments. The study did not show that changing any of the 11 genes prevents vision loss. The most exciting possibilities still require experiments to establish which genes are truly involved, whether changing them would help or harm, and whether a treatment can reach the right cells safely. What the study found—and what it did not The peer-reviewed article is “Deep-learning-derived glaucoma-related endophenotypes enable novel genome-wide genetic and functional discovery”. It reports 36 genome-wide significant loci in the European-ancestry analysis and 43 in a cross-ancestry analysis. The authors identified 21 loci as previously unreported in glaucoma and used additional analyses to prioritize 11 genes, five of them novel to glaucoma. () A locus is a region of the genome associated with a trait; it may contain several genes. A gene prioritized at a locus is a candidate for explaining the association, not necessarily the gene that causes it. The study therefore offers a set of hypotheses about glaucoma biology. It does not establish that the 21 loci—or any of the 11 genes—cause glaucoma, nor that a drug aimed at them would work. The methodological innovation, in patient-friendly language From a yes-or-no label to a detailed retinal “fingerprint” Many genetic studies classify each participant as having glaucoma or not having glaucoma. That can be a noisy comparison: some people may have undiagnosed disease, and people with glaucoma can have very different patterns and amounts of retinal damage. Instead, these researchers trained machine-learning models on eye scans from people with glaucoma. The models learned patterns in the ganglion cell complex and retinal nerve fiber layer—retinal structures that are affected as glaucoma damages the optic nerve. They then represented those patterns as quantitative traits, or measurable features of the scans. A useful analogy is the difference between asking whether a house is “damaged” and measuring exactly where its walls are cracked, how deep the cracks are, and how much the structure has shifted. The detailed measurements can reveal more about the process behind the damage. These scan-derived traits, which the researchers call endophenotypes, were then linked to genetic differences. They are glaucoma-informed measurements, not a replacement diagnosis or a measure of future vision loss. The study’s full-text manuscript describes two machine-learning model families, labelled AUTO and MOCO, used to produce traits from macular scans. () Reconstructing the research pipeline Train on glaucoma scans: The models were developed using 18,985 clinical optical coherence tomography scans from 8,323 glaucoma patients at Mass Eye and Ear. The earlier manuscript says most had open-angle glaucoma codes, though the training group was not restricted to chart-confirmed primary open-angle glaucoma cases. () Apply the models to UK Biobank: The final peer-reviewed publication reports 39,146 UK Biobank participants with usable genetic and scan-derived data. The ancestry groups were 35,739 European, 1,730 African, and 1,677 Asian participants. The large difference in group sizes means the European results had much greater statistical power. () Run genome-wide association studies: The researchers tested genetic variants against 21 scan-derived traits, separately by ancestry. A genome-wide association study looks across the genome for variants statistically associated with a measured trait. Split samples for discovery and replication: The manuscript describes a 75% discovery / 25% replication split within UK Biobank, followed by meta-analysis. This is useful internal checking, but it is not the same as replication in a fully independent cohort. () Combine results across ancestry groups: They conducted ancestry-specific analyses and then a cross-ancestry meta-analysis, finding 36 significant loci in the European analysis and 43 in the cross-ancestry analysis. Smaller African and Asian sample sizes limit how confidently those group-specific effects can be estimated. Prioritize possible genes and mechanisms: Follow-up analyses included gene-based testing, expression and splicing quantitative trait loci (eQTLs and sQTLs), Bayesian colocalization, Mendelian randomization, and single-cell expression enrichment in eye tissues. These analyses help narrow a locus to possible genes and cell types, but each has its own assumptions and limitations. () Which UK Biobank number should be used? The peer-reviewed publication’s figure is 39,146 participants. An earlier medRxiv abstract reported 47,908, but the manuscript’s detailed ancestry counts—35,739 + 1,730 + 1,677—sum to 39,146. The final publication’s participant number should be used for the peer-reviewed study. The public versions do not clearly explain the origin of the earlier headline figure, so it is safest to treat it as an earlier or inconsistent version figure rather than assume it represents the final analysis. () What “21 new genetic clues” means The authors call 21 loci novel to glaucoma because they had not previously been reported as associated with glaucoma or established glaucoma-related traits. “Novel” here does not mean the genes were newly discovered, that the DNA changes are unique to glaucoma, or that the genes’ roles in the body are now understood. The 11 prioritized genes were: EIF3E, LIN52, NPLOC4, PBLD, RSPO2, SLC25A16, TSPAN10, DYNC1I2, SLC25A12, ATOH7, and C14orf39. The paper identifies RSPO2, EIF3E, LIN52, DYNC1I2, and SLC25A12 as the five genes not previously reported in glaucoma. It also notes prior glaucoma-related or eye-trait evidence for some of the other genes, including ATOH7, C14orf39, NPLOC4, TSPAN10, PBLD, and SLC25A16. () The 11 prioritized genes: biology, eye-cell evidence, and drug prospects The cell evidence below refers to the study’s expression and enrichment analyses—not proof that a gene causes disease in that cell. The single-cell reference data came from non-diseased human eye tissues, and for several genes the article does not identify a particular eye-cell type as the key location. () For the full table, please open this article on visualfieldtest.com. Two shared regions make some gene assignments especially uncertain Several prioritized genes sit in the same genetic region. For example, DYNC1I2 and SLC25A12 share a locus in the study’s prioritization table; both may be plausible candidates, but the association does not establish which gene—or whether both—accounts for the signal. A similar caution applies to the chromosome 10 region involving ATOH7, PBLD, and nearby genes. These are reasons for follow-up experiments, not reasons to discard the findings. () The main biological themes Wnt signaling and aqueous outflow: the clearest treatment-oriented lead Aqueous humor is the clear fluid inside the eye. It normally drains through the trabecular meshwork. If drainage meets too much resistance, eye pressure can rise. Lowering pressure is an established way to slow glaucoma damage. RSPO2 is notable because it can strengthen Wnt signaling and the study found it in trabecular-meshwork and other anterior-segment fibroblasts, as well as optic-nerve-head fibroblasts. That puts a biologically plausible candidate in cells involved in tissue structure and outflow. Importantly, earlier laboratory work supports a role for canonical Wnt signaling in the trabecular meshwork and pressure regulation. In experimental models, blocking Wnt signaling raised pressure, and another study found that Wnt activation could reverse some abnormal features of trabecular-meshwork cells. Those results strengthen the general Wnt–outflow hypothesis—but they do not prove RSPO2 causes glaucoma or establish whether RSPO2 itself should be increased or decreased. () That direction matters. RSPO2 boosts Wnt signaling, and the prior eye studies suggest that too little canonical Wnt activity may be harmful in the trabecular meshwork. A simple plan to block RSPO2 could therefore be wrong. The best therapeutic idea, if the genetics is confirmed, may be to restore or tune local Wnt signaling, rather than turn it off across the body. Retinal ganglion-cell vulnerability, axonal transport, and mitochondria The study’s cross-ancestry gene-expression enrich Support the show

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