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Amyloid PET Quantitation and Centiloid Thresholds in the Diagnosis of Alzheimer Disease
Soleimani‐Meigooni, David N. , Chiotis, Konstantinos, Allen, Isabel E., Rabinovici, Gil D., Joie, Renaud La , Group, Meta-Centiloid Study, Apostolova, Liana G. , Asken, Breton M., Benzinger, Th., Betthauser, Tobey J., Bluma, Marina, Bombois, Stephanie, Bourgeat, Pierrick, Bouteloup, Vincent , Braskie, Meredith N., Brendel, Matthias, Brickman, Adam M., Bryant, Natalie, Bullich, Santiago , Carrillo, Maria C., Casaletto, Kaitlin, Cash, David M., Chang, Chiung-Chih, CHANG, H L, Chao, Yishu , Collij, Lyduine E., Corrada, Maria M., Craft, Suzanne , Dickerson, Bradford C., Dubois, Bruno, Dufouil, Carole, Fajardo, Alfonso, Farrar, Gill , Fortea, Juan, Frings, Lars , Frisoni, Giovanni B., Gardner, Raquel C., Gnörich, Johannes , Gordon, Brian A., Gu, Yuna , Guan, Yihui, Guo, Tengfei, Hanseeuw, Bernard J., Hansson, Oskar, Harrison, Theresa M., Huang, Qi, Huang, ST , Iaccarino, Leonardo, Ishii, Kazunari, Ishi, Kenji, Jagust, William J., Johnson, Sterling C., Kato, Takashi, Katsumi, Yuta, Kaye, Jeffrey, Kolinger, Guilherme D., Kramer, Joel H. , Landau, Susan M., Landeau, Brigitte, Lao, Patrick J., Lee, Sangwon, Lopresti, Brian J., Lowe, Val J. , Luchsinger, José A., Mao, Xiaoxie, March, Andrew, Masters, Colin L., Meyer, Philipp T., Mezenge, Florence, Mormino, Elizabeth C., Franquesa‐Mullerat, María , Nakamura, Akinori, Nordberg, Agneta, O’Brien, John T., O’Bryant, Sid E., Pappas, Ioannis, Peretti, Debora E., Rowe, Christopher C., Rowe, James B., Schwartz, Daniel L., Seo, Sang Won , Shekari, Mahnaz, Smith, Ruben, Snyder, Heather M. , Sokolowski, Andrzej, Sperling, Reisa A., Sun, Pan, Taggett, Jacinda Z., Touroutoglou, Alexandra , Vaillancourt, David E., Giessen, Elsmarieke van de, Vijverberg, Jort, Villemagne, Victor L. , Villeneuve, Sylvia , Wang, Wei-en, Weiner, Michael, Woodworth, Davis, Xiao, Cally , Xie, F, Yoon, Yeojun, Yun, Mijin, Severanc, A4, ABIDE, ADNI*, ADNI-DoD, AgeWell, AIBL, AMYPAD, BACS, BATON, BIOCARD, BLSA, BioFINDER-2, BrANCH, CPAS, DETECT-AD, GEMS, GHABS, HABS, HABS-HD, IDEAS, IMAP, INSIGHT-preAD, Insight46, K-ROAD, LEADS, MCSA, MULNIAD, MEMENTO, SCAN, PREVENT-AD, SPIN,, Corrada, María M. , La Joie, Renaud , Blazhenets, Ganna , Chiotis, Konstantinos , Allen, Isabel Elaine , Rabinovici, Gil D. , Asken, Breton M. , Bejanin, Alexandre , Benzinger, Tammie L.S. , Betthauser, Tobey J. , Blūma, Marina , Bombois, Stéphanie , Bourgeat, Pierrick , Braskie, Meredith N. , Brendel, Matthias , Brickman, Adam M. , Carrillo, María C. , Casaletto, Kaitlin B. , Cash, David M. , Chang, Chiung‐Chih , Chang, Hsin‐I , Chêne, Geneviève , Chételat, Gaël , Coath, William , Collij, Lyduine , Colmant, Lise , Dickerson, Bradford Clark , Dubois, Bruno , Dufouil, Carole , Fortea, Juan , Garibotto, Valentina , Gordon, Brian A. , Guan, Yihui , Guo, Tengfei , Hanseeuw, Bernard , Hansson, Oskar , Harrison, Theresa M. , Iaccarino, Leonardo , Ishii, Kazunari , Ishii, Kenji, Jagust, William J. , Johnson, Sterling C. , Katsumi, Yuta , Kaye, Jeffrey , Koeppe, Robert A. , Kolinger, Guilherme Domingues , Landau, Susan , Landeau, Brigitte , Lao, Patrick , Lee, Sangwon, Lleó, Alberto , Lopresti, Brian J. , Malpetti, Maura , March, Andrew, Masters, Colin L. , Mézenge, Florence, Mormino, Elizabeth C. , Nakamura, Akinori , Nordberg, Agneta , O'Brien, John Tiernan , O’Bryant, Sid E. , Pappas, Ioannis , Quenon, Lisa , Rowe, Christopher Cleon , Rowe, James B. , Rudolph, Marc D. , Salvadó, Gemma , Schott, Jonathan M. , Schwarz, Christopher G. , Shekari, Mahnaz , Silbert, Lisa C. , Smith, Ruben, Sokolowski, Andrzej, Sperling, Reisa Anne , Sun, Pan , Taggett, Jacinda , Toga, Arthur W. , Vaillancourt, David E. , Giessen, Elsmarieke van de , Vemuri, Prashanthi , Villain, Nicolas , Wang, Wei‐en , Weiner, Michael W. , Xie, Fang , Young, Christina B. , Yun, M R

JAMA | July 13, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1001/jama.2026.13116 | PMID 42441390 Get It

Importance Amyloid positron emission tomography (PET) is increasingly used in research and clinical settings to determine the etiology of cognitive decline and eligibility for amyloid-targeting therapies. To assist with amyloid PET evaluation and to guide clinical decision-making, images can be quantified in a standardized unit called Centiloid, the interpretation of which can vary according to the method and threshold used. Objective To collect Centiloid values from available studies and determine robust positivity cutoffs using data-driven methods and correspondence with visual reads. Data Sources PubMed search (October 2024) identified studies with Centiloid values. Corresponding authors were invited to share individual participant data. Additional data were obtained through access-controlled repositories and conference outreach (July 2024-July 2025). Study Selection Studies were included if they provided Centiloids, radiotracer, age, and sex. Data Extraction and Synthesis Each study was analyzed using a unified statistical pipeline; study estimates were pooled using random-effects meta-analysis. Main Outcomes and Measures Gaussian mixture models (GMMs) were fitted to Centiloid values for each study. In studies with a bimodal distribution (per integrated completed likelihood), single cutoffs for positivity were set as mean plus 2 SDs of the lower gaussian component. Using GMMs, a double-cutoff approach defined a lower certainty range using a 90% posterior probability cutoff for assignment to the low (amyloid-negative) vs high (amyloid-positive) component. An alternative Centiloid cutoff was derived from maximizing the correspondence (Cohen κ) with the binary visual reads when available. Results This meta-analysis included cross-sectional amyloid PET scans acquired with 5 radiotracers from 49 227 participants across 53 studies from 15 countries (mean age, 71 years; 54% female, 62% cognitively impaired). The data-driven GMM approach identified a bimodal distribution in 51 studies (n = 48 786), resulting in a single cutoff for positivity of 18 Centiloids (95% CI,16-19; I 2 = 97%). The double-cutoff approach revealed high confidence for interpreting scans as negative when Centiloid values were lower than 11 (95% CI, 9-13; I 2 = 95%) and interpreting scans as positive if Centiloid values were higher than 26 (95% CI, 24-28; I 2 = 95%). In analyses of correspondence with binary (positive or negative) visual reads of amyloid PET scans (n = 35 045; 36 studies), Centiloids were highly predictive of visual positivity (Cohen κ, 0.86; 95% CI, 0.83-0.89; I 2 = 96%) with a cutoff of 27 Centiloids (95% CI, 24-30; I 2 = 80%). Conclusions and Relevance In this individual participant data meta-analysis, positivity cutoffs converged around 18 Centiloids (data-driven) and 27 Centiloids (visual reads). Findings from a double-cutoff analysis suggest that scans in the 11 to 26 Centiloid range should be interpreted with caution depending on the context of use.
Bacteriophage Therapy of Mycobacterium abscessus Mastoiditis
Becken, Bradford , Lauer, Michael J , Russell, Daniel A, Garlena, Rebecca A , Cristinziano, Madison, Abad, Lawrence, Dedrick, Rebekah M, Jacobs-Sera, Deborah, Driscoll, Colin, Zwiener, Jennifer, Hatfull, Graham F , Becken, Bradford , Lauer, Michael J , Russell, Daniel A. , Garlena, Rebecca A. , Cristinziano, Madison, Abad, Lawrence , Dedrick, Rebekah M. , Jacobs‐Sera, Deborah , Driscoll, Colin L. W., Zwiener, Jennifer, Hatfull, Graham F.

Clinical Infectious Diseases | July 10, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1093/cid/ciag439 | PMID 42455053 Get It

Abstract We describe a case of a child with macrolide-resistant Mycobacterium abscessus who initially had clinical improvement on a dual β-lactam regimen but continued to have positive cultures. Suitable phages active against the bacterial strain were identified, administered both systemically and directly to the ear, and were associated with microbiological remission.
Integrating Artificial Intelligence and Automation Into Living Guideline Development: A Scoping Review of Existing Frameworks, Methods, and Applications
Ismaila, Nofisat , Naqvi, Syed Arsalan Ahmed , Ma, Jinhui , Thabane, Lehana , Mbuagbaw, Lawrence , Ma, Jinhui

Clinical and Public Health Guidelines | July 7, 2026 | Volume: 3 | Issue: 3 | Pages: No page available

10.1002/gin2.70079 | PMID 42740792 Get It

ABSTRACT Background Artificial intelligence (AI) and automation offer opportunities to enhance the efficiency, timeliness, and sustainability of living guidelines (LGs). However, how AI and automation have been integrated into existing LG development frameworks remains unclear. This scoping review represents the first step in a broader programme of work aimed at developing a framework which aims to guide responsible and coordinated AI adoption across all phases of LG development. Objective To identify existing frameworks, methods, and approaches that integrate AI or automation into any stage of LG development. Methods We conducted a structured search of PubMed, Embase, Web of Science, Scopus, Cochrane Database for Systematic Review and Cochrane Central Register of Controlled Trials from inception to March 12, 2026. We included peer‐reviewed articles describing frameworks, models, or methods that applied AI or automation in the development of LGs. We extracted data into a standardised form, capturing study characteristics, AI methods, targeted guideline processes, and key findings and synthesised findings using a thematic narrative approach. Results Of 1090 records identified, three studies met the inclusion criteria. The included studies described AI or automation applied to select components of the LG process, to support continuous evidence surveillance, to semi‐automate study screening, and incremental updating of living systematic reviews. None addressed multiple stages of LG development in an integrated manner. Conclusions Current evidence demonstrates fragmented and narrowly focused AI or automation applications within LG development processes. Our findings highlight opportunities for future work to develop and evaluate more comprehensive frameworks that span multiple stages of the LG lifecycle.
Acute and Long‐Term EEG and seizure characteristics in new onset refractory status epilepticus (NORSE)
Gilani, Kia , Hanin, Aurélie , Gaspard, Nicolas , Batra, Ayush , Behrndt, Laken, Day, Gregory S. , Demeret, Sophie , Eschbach, Krista , Foreman, Brandon , Gerard, Elizabeth E. , Gopaul, Margaret T., Hantus, Stephen , Cobos‐Hernandez, Carla, Jimenez, Anthony D. , Jongeling, Amy, Kandula, Padmaja , Kang, Peter, Kellogg, Marissa, Kim, Minjee , Farias‐Moeller, Raquel , Morales, M., Pimentel, Cederic M., Ramírez, Alexandra , Taraschenko, Olga , Zhou, Daniel J., Gofton, Teneille E , Haider, Hiba A , Kandula, Padmaja , Farias-Moeller, Raquel , Navarro, Vincent , Steriade, Claude , Struck, A F , Taraschenko, Olga , Wainwright, Mark S , Hirsch, Lawrence J , Yoo, Ji Yeoun , Eschbach, Krista , Gaspard, Nicolas , Day, Gregory S , Batra, Ayush , Hanin, Aurelie , Foreman, Brandon , Gerard, Elizabeth E , Kim, Minjee , Gofton, Teneille , Gopaul, Margaret , Haider, Hiba A. , Jongeling, Amy , Kazazian, Karnig , Kellogg, Marissa , Navarro, Vincent , Steriade, Claude , Struck, Aaron F. , Wainwright, Mark S. , Zhou, Daniel J., Hirsch, Lawrence J. , Yoo, Ji Yeoun

Epilepsia | June 26, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1002/epi.70349 | PMID 42359767 Get It

Abstract Objective This study was undertaken to examine acute and chronic electroencephalographic (EEG) and seizure characteristics in new onset refractory status epilepticus (NORSE). Methods Multicenter inpatient and follow‐up clinical and EEG data were analyzed using International League Against Epilepsy definitions and American Clinical Neurophysiology Society (ACNS) EEG terminology. Results Forty‐four patients were included from the Yale NORSE/FIRES Biorepository (median age = 29 years, 33 female, 38 cryptogenic). Nine hundred twenty inpatient EEG days were reviewed (median = 13.5 days/patient). Presenting status epilepticus (SE) types included 24 convulsive SE (CSE), five focal–motor (FMSE), and 15 nonconvulsive (NCSE). Of 39 patients with post discharge follow‐up (median = 14.7 months), 61.5% ( n = 24) had seizures and required more antiseizure medications than seizure‐free patients (median = 4 vs. 1, p < .001). Inpatient EEG captured epileptiform discharges in all and periodic discharges in 38 patients. Seizures were captured in 38 patients: 33 electrographic (11 only electrographic) and 27 electroclinical. Total seizure burden ranged 6.5–29 615.0 min (median = 50.7). Seizures fulfilling ACNS EEG criteria for SE were captured in 20 patients; two had CSE and the remainder NCSE with coma, nine of whom also had FMSE. Inpatient seizure days (median = 50.0 vs. 15.5%, p = .004) and seizure burden (median = 42.9 vs. 0 min, p = .009) were higher in the first half of monitored days. Interictal findings were equally present and did not predict postdischarge seizures, whereas electroclinical seizures (90.9% vs. 45.5%, p = .037), seizure burden (median = 116.8 vs. 32.5 min, p = .045), and proportion of seizure days (36.3% vs. 20.0%, p = .037) did. Among 12 patients with follow‐up EEGs (median = 19.6 months post onset), posterior‐dominant rhythm (PDR) returned in nine; five had periodic discharges, and three had seizure captured. Significance Seizures are most commonly convulsive upon presentation and nonconvulsive or clinically subtle throughout the inpatient course in NORSE. Inpatient seizures, but not interictal abnormalities, occur earlier in the inpatient course and presence of electroclinical seizures, seizure burden, and proportion of seizure days but not interictal findings are associated with postdischarge seizures. Although return of PDR reflects neurological recovery, seizure persistence and EEG abnormalities post‐NORSE are common.
Accuracy of the rapid‐response electroencephalography's Automated Seizure Burden Estimator: A follow‐up validation study of version 8 ( AccuRASE II )
Sheikh, Zubeda , Fong, Michael W K , Dhakar, Monica B. , Fang, Wei , Ayub, Neishay , Bacic, Janine , Haider, Hiba A. , Foreman, Brandon , Gilmore, Emily J. , Mizrahi, Moshe , Osman, Gamaleldin , Sheikh, Zubeda B , Dhakar, Monica B , Molino, Janine , Karakis, Ioannis , Schmitt, Sarah E , Osman, Gamaleldin , Yoo, Ji Yeoun , Hirsch, Lawrence J , Haider, Hiba A , Ayub, Neishay , Gilmore, Emily , Foreman, Brandon , Karakis, Ioannis , Yoo, Ji Yeoun , Hirsch, Lawrence J.

Epilepsia | June 25, 2026 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1002/epi.70352 | PMID 42347801 Get It

Abstract Objective Ceribell Inc.'s point‐of‐care electroencephalographic (EEG) system and artificial intelligence‐based Automated Seizure Burden Estimator (ASBE; ClarityPro) have US Food and Drug Administration clearance for diagnosing electrographic status epilepticus (ESE). The AccuRASE study using ASBE version 6 (V6) showed high negative predictive value (NPV) but limited sensitivity and positive predictive value (PPV) at certain thresholds. Version 8 (V8) is the updated algorithm trained with additional EEG samples. Methods We tested V8 on the previously used rapid‐response EEG test dataset (not used to train V8). Sensitivity, specificity, PPV, and NPV were compared against blinded expert annotations. ESE, ESE and possible ESE (ESE/pESE), electrographic seizures (ESz), and Esz with highly epileptiform patterns (Esz/HEPs) at burden thresholds of >1%, >10%, >20%, >50%, and >90% were analyzed. Additionally, we evaluated the built‐in ESE and ESE/pESE alerts (≥90% over 5 min, ≥20% over 1 h, or ≥10 continuous minutes of seizure). Results V8 showed 100% sensitivity at lower thresholds (>10%–20%) for ESE (V6 .86), without a specificity loss (V8 .9 vs. V6 .85), and retained NPV (V8 1.0 vs. V6 .99). Sensitivity at 50% threshold was .86 for ESE (V6 .71), and specificity was .94 (V6 .91); PPV for ESE was 30% for ESE and 80% for ESE/pESE. The specificity for ESE remained high for 90% burden (V8 .96, V6 .97) but the sensitivity dropped (.29 vs. V6 .43). Sensitivity was lower for ESz/HEPs (.54 → .44 at >10% threshold), although the algorithm is not designed to detect HEPs. Built‐in alert analysis showed significantly improved sensitivity for ESE (.57 → .86); specificity and NPV remained high (>.94). Significance ASBE V8 showed meaningful improvements in sensitivity, continued excellent NPV, and improved built‐in alert accuracy for ESE and ESE/pESE. The best seizure burden threshold for ruling out ESE now is 20% (vs. 10% with V6) and that for ruling in ESE/pESE with reasonable certainty is 50% (vs. 90% with V6).
Clinical Associations of Cerebrospinal Fluid TMEM106B in Familial and Sporadic Frontotemporal Dementia
Olzinski, Molly, Downer, Joshua, Rajbanshi, Binita, Li, Jingyao, Loureiro, Joseph, Heuer, Hilary, Ljubenkov, Peter, Vandevrede, Lawren, Staffaroni, Adam, Lario‐Lago, Argentina, Leichter, Dana, Wolf, Amy, Wise, Amy, Sanderson-Cimino, Mark, Barragan, Eden, Spina, S, Grinberg, Lea T., Seeley, William W., Casaletto, Kaitlin B., Kramer, Joel, Ramos, Eilana, Geschwind, Daniel, Cook, Casey, Petrucelli, L, Forsberg, Leah K., Gendron, Tania, Boeve, Bradley F., Rademakers, Rosa, Rosen, Howard J., Saloner, Rowan, Boxer, Adam L., Rojas, Julio C., Abdullah, M. Samy, Apostolova, Liana, Appleby, Brian, Bayram, Ece, Hp, Botha, Bozoki, Andrea, Brushaber, Danielle, Clark, David, Considine, Ciaran M., Darby, R. Ryan, Day, Gregory S., Dickerson, Bradford C., Dickson, Dennis, Domoto-Reilly, Kimiko, Dwosh, Emily, Faber, Kelley M., Fields, Julie A. , Fong, Jamie C., Foroud, Tatiana, Galasko, Douglas R., Gavrilova, Ralitza, Ghoshal, Nupur , Goldman, Jill, Graff-Radford, Jonathan, Graff-Radford, Neill, Grant, Ian M., Cn, Hales, Honig, Lawrence S., Gd, Hsiung, Huey, Edward D, Irwin, David, Jones, David T., Kantarci, Kejal, Knopman, David, Kolander, Tyler , Kornak, J M, Kremers, W., Kwan, Justin , Lapid, Maria, Lee, Suzee, Litvan, Irene, Lucente, Diane, Mackenzie, Ian R., Masdeu, J C, Massimo, Lauren, McGinnis, Scott, McMillan, Corey T., Mendez, Mario F., Mester, Carly, Miyagawa, Toji , Molden, Joie, Onyike, Chiadi, Pantelyat, Alexander, Pascual, Belen, Paulson, Henry, Ramanan, Vijay, Rankin, Katherine P., Rascovsky, Katya, Rhoads, Kristoffer , Savica, Rodolfo, Snyder, Allison, Sullivan, A. Campbell, Syrjanen, Jeremy, Tartaglia, M, Taylor, Jack, Tipton, P E, WEINTRAUB, S, Wint, Dylan, Wong, Bonnie, Yokoyama, Jennifer, Paulson, Henry L. , Barmada, Sami J. , Paulson, Henry L , Barmada, Sami , Cobigo, Yann , Worringer, Kathleen A. , Heuer, Hilary W. , VandeVrede, Lawren , Staffaroni, Adam M. , Wolf, Amy , Wise, Amy B. , Sanderson‐Cimino, Mark , Barragan, Eden V. , Grinberg, Lea T. , Seeley, William W. , Casaletto, Kaitlin B. , Kramer, Joel, Ramos, Eliana Marisa , Geschwind, Daniel H. , Forsberg, Leah K. , Gendron, Tania F. , Boeve, Bradley F. , Perneel, Jolien , Rademakers, Rosa , Rosen, Howard J. , Saloner, Rowan , Boxer, Adam L. , Rojas, Julio C. , Appleby, Brian S. , Barmada, Sami, Bayram, Ece , Botha, Hugo, Bozoki, Andrea C , Brushaber, Danielle , Clark, David, Considine, Ciaran , Dickerson, Bradford Clark , Dickson, Dennis, Domoto‐Reilly, Kimiko , Dwosh, Emily , Foroud, Tatiana, Graff‐Radford, Jonathan , Graff-Radford, Neill, Hales, Chadwick M., Honig, Lawrence S. , Hsiung, Ging-Yuek R., Huey, Edward D. , Jones, David T., Kantarci, Kejal , Kornak, John , Kremers, Walter, Kwan, Justin, Léger, Gabriel C. , Litvan, Irene , Lucente, Diane , Mackenzie, Ian R. , Massimo, Lauren , McGinnis, Scott, McMillan, Corey T. , Mendez, Mario F. , Mester, Carly , Pascual, Belén , Ramanan, Vijay, Rankin, Katherine P. , Roberson, Erik D. , Savica, Rodolfo , Snyder, Allison , Sullivan, A. Campbell , Syrjanen, Jeremy A. , Taylor, Jack C. , Tipton, Philip W., Vandebergh, Marijne , Weıntraub, Sandra , Wint, Dylan

JAMA Neurology | June 22, 2026 | Volume: 83 | Issue: 8 | Pages: 778

10.1001/jamaneurol.2026.1927 | PMID 42329632 Get It

Importance TMEM106B is a frontotemporal lobar degeneration (FTLD) genetic susceptibility factor, and TMEM106B protein aggregates are a feature of aging and neurodegeneration. Whether TMEM106B protein levels are associated with clinical features is unknown. Objective To investigate the clinical associations of cerebrospinal fluid (CSF) TMEM106B in FTLD. Design, Setting, and Participants This cross-sectional study was conducted in 2 independent frontotemporal dementia (FTD) cohorts (recruitment from April 2009 through July 2023, with analyses from January 2025 through April 2026), with a 2-year follow up. This multicenter clinical study integrated clinical, genetic, biomarker, and neuroimaging data. Individuals were recruited through the University of California, San Francisco (n = 3733), or ALLFTD (n = 2343). Participants with available CSF were included. A discovery cohort (n = 271) included participants with sporadic neuropathology-confirmed FTLD; presymptomatic or symptomatic carriers of pathogenic variants in C9orf72 , GRN , or MAPT ; or controls. An independent validation cohort (n = 383) included participants with clinically diagnosed sporadic FTD, Alzheimer disease (AD), and controls. Exposures CSF samples for TMEM106B quantification with aptamer proteomics (SomaScan version 3.0 [discovery cohort] and SomaScan version 4.1 [validation cohort]). Main Outcomes and Measures Parametric tests compared the primary outcome, CSF TMEM106B, by disease severity, TMEM106B rs1990622 genotype, sex, clinical syndrome, pathological diagnosis, and pathogenic variant and determined associations with brain volume. Results In the discovery (n = 271; 136 women [51%]; median [IQR] age, 59 [38-80] years) and validation (n = 383; 183 women [48%]; median [IQR] age, 64 [50-78] years) cohorts, lower CSF TMEM106B was associated with more severe disease (β, −0.15; 95% CI, −0.24 to −0.04; P = .003), lower frontotemporal brain volumes (β, 0.42; 95% CI, 0.24-0.61; P &amp;lt; .001), and faster clinical progression (β, −2.21; 95% CI, −3.70 to −0.72; P = .001). Associations of TMEM106B with clinical disease severity were independent of those with neurofilament light chain. TMEM106B levels were influenced by TMEM106B rs1990622 genotype, where individuals with the protective G/G genotype had lower levels than the risk A/A genotype. CSF TMEM106B levels did not differentiate between FTLD subtypes or between FTLD and AD. Conclusions and Relevance Per the results of this cross-sectional study, TMEM106B is detectable in CSF and levels reflect disease severity in sporadic and genetic FTLD and AD, but levels are also influenced by the TMEM106B rs1990622 genotype. CSF TMEM106B could support further studies to understand the mechanisms of disease and develop clinical tools in FTLD and other neurodegenerative diseases.
A19-10 Seralutinib for the Treatment of Pulmonary Arterial Hypertension (PAH): Results From the Phase 3 PROSERA Trial
Ghofrani, H A, Mclaughlin, V V, Meyer, G Bohns, Benza, R L, Channick, R N, Chin, K M, Frantz, R P, Hemnes, A R, Howard, L S, Zamanian, R T, Kopeć, G, Skride, A, Jerjes-Sánchez, C, Lescano, A J, Subías, M P Escribano, White, R J, Zamudio, T Pulido, Perna, E R, Rosenkranz, S, Badagliacca, R, Scelsi, L, Lima, M A, Sulica, R, Miller, C, Al-Hiti, H, Campos, F, Zagolin, M, Roscigno, R F, Mottola, D, Aranda, R, Cravets, M, Tompkins, C -A A, Parsley, E, Elman, E, Zisman, L S, Vachiery, J L, Sitbon, O, Ghofrani, H A, McLaughlin, Vallerie V. , Meyer, Gisela Martina Bohns , Benza, Raymond L. , Channick, R N, Chin, K M, Frantz, Robert P. , Hemnes, A R, Howard, L S, Zamanian, R.T., Kopeć, Grzegorz , Skride, Andris , Jerjes‐Sánchez, Carlos , Subias, M P Escribano, White, R. James , Perna, Eduardo , Rosenkranz, S, Badagliacca, Roberto , Scelsi, Laura , Sulica, Roxana, Miller, Chad E., Al‐Hiti, Hikmet, Roscigno, Robert F., Mottola, David, Aranda, R, Cravets, Matt , Parsley, Ed, Elman, Erin, Zisman, Lawrence S. , Vachiéry, Jean‐Luc , Sitbon, Olivier

American Journal of Respiratory and Critical Care Medicine | June 22, 2026 | Volume: 212 | Issue: Supplement_2 | Pages: No page available

10.1093/ajrccm/aamag286.279 Get It

Abstract Rationale Seralutinib is an investigational, first-in-class tyrosine kinase inhibitor designed for inhalation and selective for PDGFRα, PDGFRβ, CSF1R, and cKIT, targeting proliferation, inflammation, and fibrosis ─ three core drivers of pulmonary vascular remodeling in PAH. The phase 2 TORREY trial of seralutinib added to standard-of-care treatment in adults with PAH WHO FC II or III met its primary endpoint of a statistically significant reduction in pulmonary vascular resistance (PVR) vs. placebo at 24 weeks. Methods PROSERA (NCT05934526), a phase 3, randomized, double-blind, placebo-controlled, multicenter trial, evaluated the efficacy and safety of inhaled seralutinib in PAH patients treated for up to 48 weeks. Eligible patients (WHO Group 1 PH, FC II or III; REVEAL Lite 2 Risk Score ≥5 or NT-proBNP ≥300 ng/L or PVR ≥800 dyne•s/cm5) on standard background therapy were randomized 1:1 to seralutinib 90 mg or placebo delivered by dry powder inhaler twice daily. The primary endpoint was change in six-minute walk distance (6MWD) from baseline to week 24 in the seralutinib treatment group vs. placebo. Key secondary endpoints included: time to clinical worsening (TTCW), proportion of patients with clinical improvement at week 24, change in NT-proBNP from baseline to week 24, and proportion of patients with ≥1-point decrease from baseline in REVEAL Lite 2 Risk Score at week 24. Safety endpoints included incidence of treatment-emergent adverse events (TEAEs) and serious TEAEs (SAEs). Patients who completed blinded treatment could be eligible to participate in an open-label extension study. Preliminary Blinded Results 390 patients were randomized at 132 sites worldwide. At baseline, mean age was 50.0 years. PAH etiologies included 61.0% idiopathic, 9.7% heritable, and 22.3% associated with connective tissue disease. 25.6% of patients were WHO FC II and 74.4% FC III. Mean time from diagnosis was TBD years. Most patients were receiving 2 (39.2%) or ≥ 3 (54.6%) PAH medications, 29.2% were receiving parenteral prostacyclin. Baseline PVR was 798.4 dyne•s/cm5, 6MWD was 373.7 m, and NT-proBNP was 986.8 ng/L. The difference in 6MWD from baseline to week 24 between seralutinib and placebo was TBD [SD] m (p=TBD). Secondary endpoints of TTCW, clinical improvement, NT-proBNP, and REVEAL Lite 2 Risk Score will be reported. The most common AEs were TBD (x%) and TBD (y%). SAEs and discontinuations related to AE will be reported. Conclusions The PROSERA study demonstrates⋯ [to be updated following unblinding of the data]. Funding Gossamer Bio, Inc. This abstract is funded by: Gossamer Bio, Inc.