Citations

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.

Abstract INTRODUCTION Clinicopathological studies offer crucial interpretations of 18 F‐flortaucipir (FTP) tau positron emission tomography (PET) signal but are limited by methods. We leveraged whole‐brain, quantitative immunohistochemical (IHC) Alzheimer's Disease (AD) tau density maps to comprehensively evaluate the FTP tracer. METHODS We generated IHC maps for three AD‐tau antibodies—AT8, AT100, and MC1—using two human brains histologically staged at Braak IV and VI. FTP‐PET scans were acquired 6 and 10 weeks prior to death. Using region‐wise and voxelwise methods, we correlated FTP‐PET with IHC signals. RESULTS Only AT8 (p‐tau Ser202/Thr205; neuronal and neuritic tau pathology) showed a notable correlation with FTP standardized uptake value ratios (SUVRs) in the Braak VI case (Spearman's rank correlation coefficient [r s ] = 0.461, p < 0.001). FTP SUVRs failed to capture medial temporal lobe (MTL) tau burden, whereas neocortical regions showed lower IHC burden but more variability in FTP uptake. DISCUSSION Although FTP signals correlate well with AT8‐positive tau in the more advanced case, they underestimate the severity of MTL burden, potentially confounding assessments of tau‐targeted therapies.

Importance Brain imaging biomarkers may (1) identify underlying mechanisms of intervention effects and (2) define brain characteristics of those most likely to benefit cognitively from the intervention. Objective To test whether (1) a lifestyle intervention is related to brain changes, (2) brain changes are correlated with intervention-specific cognition changes, and (3) brain imaging biomarkers provide information about who is likely to benefit from a lifestyle intervention. Design, Setting, and Participants In this randomized clinical trial, the POINTER Imaging study was an ancillary study of the 2-year, single-blind multicenter US POINTER clinical trial in which neuroimaging data were collected on eligible enrolled participants. The study was conducted from May 2019 to March 2023 (final follow-up, May 14, 2025). Participants were enrolled into the POINTER Imaging study following a standard procedure at 5 clinical sites in the US. Participant eligibility criteria included an age of 60 to 79 years, sedentary lifestyle, and suboptimal diet, plus at least 2 additional risk criteria for cognitive decline and no contraindications for neuroimaging. Interventions Participants were randomly assigned to receive the structured or self-guided intervention. Both interventions emphasized increased physical and cognitive activity, healthy nutrition, social engagement, and cardiovascular health monitoring, but they differed in intensity and accountability. Main Outcomes and Measures There were 4 primary imaging outcomes: global β-amyloid (Aβ) burden, tau burden in the entorhinal cortex (ERC), hippocampal (HC) volume, and white matter hyperintensity volume. The primary cognitive measure was a global cognitive composite. Results Among 1943 parent trial participants who were assessed for eligibility, 983 underwent at least 1 magnetic resonance imaging or positron emission tomography scanning session. The mean (SD) age was 68.4 (5.2) years; 605 participants (61.5%) were female and 378 male (38.5%). Five hundred sixteen participants received the structured intervention and 467 the self-guided intervention. There were no intervention group differences in longitudinal cognitive or imaging outcomes. Intervention group differences were not associated with or moderated by Aβ status or accumulation. There was a negative association between change in ERC tau and change in global cognition in the self-guided group that was attenuated in the structured group (difference in association: 0.289; 95% CI, 0.029 to 0.550; interaction P = .03). Lower baseline HC volume was associated with greater cognitive benefit for participants in the structured group vs the self-guided group (lower HC: 0.077 SD; 95% CI, 0.022 to 0.132; higher HC: 0.002 SD; 95% CI, −0.037 to 0.041; interaction P = .03). Conclusion and Relevance This study found that a high-intensity multidomain lifestyle intervention did not affect brain biomarker trajectories and was not associated with Aβ pathology, but older adults with specific at-risk brain characteristics, including lower baseline HC volume, showed a greater cognitive benefit of the structured intervention. Trial Registration ClinicalTrials.gov Identifier: NCT03688126

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen's kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure 1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure 1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure 2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure 2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Abstract Background Ten years after the original publication, the Centiloid framework is now broadly used to harmonize amyloid‐PET quantification, facilitate data sharing and comparison across cohorts, and even assist visual interpretation in clinical settings. We evaluated the global implementation of Centiloids by comparing their distribution and corresponding positivity thresholds across cohorts. Methods We gathered data from publicly available cohorts and reached out to investigators across the world to collect cross‐sectional Centiloids, demographic and clinical information, and visual read data. Gaussian mixture models (GMM, k=2) were fitted to Centiloid values for each cohort and cutoffs were calculated as mean + 2SD of the lower Gaussian. When visual reads were available, we determined Centiloid cutoffs that maximized correspondence with visual reads (Cohen’s kappa). Data was combined across cohorts using random effects meta‐analyses. Results As of January 2025, we included 37 cohorts ( n = 41,678 participants) with heterogeneous pipelines, radiotracers, and clinical and demographic characteristics (Table‐1). The low Gaussian peaks ranged from ‐9 to 10CL; the meta‐analysis identified a common peak at 1CL. The second peaks were more heterogeneous (range=38‐102CL; meta‐analysis outcome=64CL). Across cohorts, the proportion of cognitively unimpaired versus impaired participants impacted the position of both peaks, with better separation in cohorts enriched in impaired individuals (Figure‐1C). The meta‐analysis indicated a GMM‐based cutoff of 19CL (95%CI: 16‐21CL, Figure‐1B); subgroup analyses showed no evidence of significant effect between single versus multicenter settings (17 versus 20CL, p = 0.30), MRI‐based or PET‐only processing (18 versus 19CL, p = 0.88), and no evidence of difference across radiotracers (Flutemetamol: 16CL; PIB: 17CL, Flutafuranol: 18CL, Florbetaben: 19CL, Florbetapir: 20CL, p = 0.78). In a subset of 29,496 participants with visual reads available, binary visual reads corresponded well to Centiloids (common kappa=0.86, Figure‐2A). The visual read‐based cutoff of 24CL (95%CI: 21‐27CL, Figure‐2B) maximized correspondence between visual read and quantification and was slightly higher than the GMM‐based cutoff. All meta‐analysis models showed high non‐random heterogeneity (I 2 >80%) across studies, suggesting non‐random differences in peaks and cutoffs. Conclusions Meta‐analysis‐based cutoffs align well with thresholds from the existing literature. High heterogeneity among studies underscores the need to investigate contributing factors, raising concerns about applying common cutoffs.

Abstract Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality globally, with particularly high burdens among people living with HIV (PLWH) in low‐resource settings like Nigeria. Effective early detection remains a major challenge due to limited access to imaging‐based surveillance and the low sensitivity of current biomarkers such as alpha‐fetoprotein (AFP). We conducted an epigenome‐wide association study (EWAS) of circulating cell‐free DNA (ccfDNA) methylation in a Nigerian cohort of HIV‐positive individuals ( n = 245), spanning HCC, cirrhosis (FibroScan ≥12.3 kPa), fibrosis (FibroScan ≥7.6 and <12.3 kPa), and HCC‐free without fibrosis (FibroScan <7.6 kPa) groups. Using random forest modeling, we developed and evaluated a ccfDNA methylation classifier (ccfDNAmRF) for HCC risk prediction. We identified 73 CpG sites significantly associated with HCC (false discovery rate <0.01). The ccfDNAmRF model demonstrated strong discriminatory power, achieving 100% sensitivity and 80%–91% specificity for distinguishing HCC from cirrhosis, fibrosis, and HCC‐free groups (area under the curve [AUC]: 92%–97%). Combining ccfDNA methylation risk scores with AFP further improved classification accuracy (AUC up to 98.5%). Notably, ccfDNA methylation patterns displayed clear dose–response relationships across the disease spectrum, supporting their utility for early‐stage detection and risk stratification. Our findings highlight the promise of ccfDNA methylation biomarkers as a non‐invasive, blood‐based screening tool for improving early identification of HCC cases among PLWH.

Pulmonary infections are commonly observed in hematologic malignancy (HM) patients.For HM patients with low immune functionality and high susceptibility to pulmonary infections, timely identification of pathogens and administration of correct medications can greatly improve patient outcomes[1, 2].The next generation sequencing can achieve an early diagnosis of respiratory infection.To date, the systematic evaluation of the clinical use of mNGS and tNGS for pneumonia in HM patients has been insufficient. A retrospective analysis was conducted on HM patients with suspected pneumonia admitted to the Hematology Department of The Third Xiangya Hospital between April 2019 and April 2024.A total of 234 patients were identified for analysis,including 126 patients used mNGS to detect bronchoalveolar lavage fluid(BALF）and 108 patients used mNGS to detect BALF.The purpose was to compare the diagnostic efficacy of mNGS and tNGS in pulmonary infection pathogens. The overall microbial detection rate of mNGS and tNGS were 88.9% (112/126) and 93.5% (101/108), respectively. And there was no significant difference between them ( p = 0.217).Viruses,bacteria and fungi accounted for 42.2%(117/277), 33.9% (94/277) and 23.8% (66/277) among the microorganisms detected in mNGS, respectively. Meanwhile,Viruses,bacteria and fungi accounted for 61.0%(147/241), 21.2% (51/241) and 17.8% (43/241) among the microorganisms detected in mNGS.In order to compare the diagnostic and concordance between mNGS and tNGS.We used the final clinical diagnosis as the “gold standard”.The sensitivity, specificity, positive predictive value and accuracy of mNGS were 92.7%,37.5%,91.1% and 85.7%, respectively, compared with 97.9%,45.5%,94.1% and 92.6% for tNGS.Further more,we compared the clinical impact of mNGS and tNGS on antibiotic usage.The mNGS results led to adjustments in antibiotic usage for 63 out of the 126 patients(56.3%). Following these alterations, 56 patients (88.9%) reported significant improvements.In tNGS,there are 59 out of the 108 patients(58.4%%) adjustmented in antibiotic usage and 56 patients(94.9%) reported significant improvements.The total death of mNGS and tNGS were 9.8%(11/126) and 4.0%（4/108), respectively. There were no significant differences between the two groups (P ＞0.05).Compared to the microbial range detected by tNGS, mNGS detected an additional 14 pathogenic microorganisms, in which had a very low proportion of pathogenic microorganisms (3.6%,4/112), which did not have any adverse effects on the clinical outcomes of patients. Collectively,we found that tNGS is comparable with mNGS in HM patients with suspected pneumonia for pathogenic microorganism detection.What's more,the ability of tNGS in guiding treatment was consistent with those of mNGS.

AbstractPreviously, lysosomes were primarily referred to as the digestive organelles and recycling centers within cells. Recent discoveries have expanded the lysosomal functional scope and revealed their critical roles in nutrient sensing, epigenetic regulation, plasma membrane repair, lipid transport, ion homeostasis, and cellular stress response. Lysosomal dysfunction is also found to be associated with aging and several diseases. Therefore, function of macroautophagy, a lysosome‐dependent intracellular degradation system, has been identified as one of the updated twelve hallmarks of aging. In this review, we begin by introducing the concept of lysosomal quality control (LQC), which is a cellular machinery that maintains the number, morphology, and function of lysosomes through different processes such as lysosomal biogenesis, reformation, fission, fusion, turnover, lysophagy, exocytosis, and membrane permeabilization and repair. Next, we summarize the results from studies reporting the association between LQC dysregulation and aging/various disorders. Subsequently, we explore the emerging therapeutic strategies that target distinct aspects of LQC for treating diseases and combatting aging. Lastly, we underscore the existing knowledge gap and propose potential avenues for future research.

Abstract Background: Hepatocellular carcinoma (HCC) is the second leading cause of cancer-related deaths worldwide. In countries with high human immunodeficiency virus (HIV) prevalence, such as Nigeria, HIV-associated HCC causes a great health burden due to its early onset, late diagnosis, and poorer prognosis. HIV infection is involved in inflammation of the liver, which may determine an increased risk of hepatocyte neoplastic transformation. Inflammation-related DNA methylation signatures obtained in liquid biopsy, such as circulating cell-free DNA (ccfDNA) extracted from serum/plasma are promising minimally-invasive biomarkers that may inform HCC among people living with HIV. Methods: A total of 289 Nigerian participants with information on ccfDNA and other covariates were included. Participants were classified into three groups by their HCC/HIV status: 1) HCC+/HIV+ (n=28); 2) HCC-/HIV+ (n=185); and 3) HCC+/HIV- (n=76). We constructed ccfDNA methylation inflammation scores using 49 CpGs previously linked to circulating C-reactive protein (CRP) concentrations, and higher scores represented elevated CRP concentrations with lower methylation levels. To compare the ccfDNA methylation inflammation score across the groups, we performed multivariable logistic regression analyses adjusting for age, sex, alcohol consumption, smoking status, body mass index, study sites, and technical variables. Results: Participants with HCC+/HIV+ presented the highest ccfDNA methylation inflammation scores (mean=-0.03, standard deviation [SD] =0.01). Participants with HCC-/HIV+ presented the lowest scores (mean=-0.05, SD=0.01). In the multivariable logistic regressions, one SD increase of inflammation score was associated with 2.5 times higher odds of having HCC among HIV-infected participants (HCC+/HIV+ vs. HCC+/HIV-; OR=2.56, 95% CI=1.39-4.73, P=0.002). No evidence was found for the association between the inflammation score and HIV status among HCC patients (HCC+/HIV+ vs. HCC+/HIV-; OR=1.00, 95% CI=0.59-1.70, P=0.991). In the secondary analysis comparing HCC+ vs. HCC- adjusting for HIV status, one SD increase of inflammation score was associated with 3.2 times higher odds of having HCC (OR=3.22, 95% CI=1.39-7.46, P=0.006). Conclusions: We observed that ccfDNA methylation inflammation score is associated with HCC status among people with HIV. Our findings suggest that ccfDNA methylation-based inflammatory profiles may serve as a potential biomarker for early detection and risk stratification of HCC in resource-constrained countries with a high prevalence of HIV. Citation Format: Kyeezu Kim, Yinan Zheng, Claudia Hawkins, Edith Okeke, Olufunmilayo Lesi, Yishu Qu, Lewis R. Roberts, Demirkan Gursel, Fatimah B. Abdulkareem, Alani Akanmu, Godwin Imade, Jian-Jun Wei, Masha Kocherginsky, Kwang-Youn Kim, Wasiu L. Adeyemo, Firas Wehbe, Chad J. Achenbach, Atiene Sagay, Folasade T. Ogunsola, Robert L. Murphy, Lifang Hou. DNA methylation-based inflammation score is associated with hepatocellular carcinoma among people living with HIV. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6013.

Abstract Purpose: Hepatocellular Carcinoma (HCC) is the leading cause of cancer-related mortality in Nigeria. HIV and viral hepatitis B (HBV) and C (HCV) co-infection are common in Nigeria that significantly accelerates liver disease progression including HCC. Aging-related DNA methylation signatures obtained in liquid biopsy, such as circulating cell-free DNA (ccfDNA) extracted from serum/plasma are promising minimally-invasive biomarkers that may inform HIV-associated HCC. We examined the epigenetic age acceleration (EpiAgeAccel) in ccfDNA in HCC patients with HIV. Methods: The study included three groups of participants: a) HIV positive with HCC (n=7); b) HIV positive and cancer-free (n=45); and c) HIV negative with HCC (n=33). Epigenetic age was estimated by Horvath's calculator using genome-wide ccfDNA methylation data profiled by Illumina EPIC array. EpiAgeAccel was computed as the residuals of a linear model of epigenetic age on chronological age, namely the unexplained portion of epigenetic age by chronological age. We used multiple linear regression to compare EpiAgeAccel between HIV/HCC groups, adjusting for sex, age, education, alcohol intake, and HBV/HCV infection. Results: Among HIV positive participants, there was a higher percentage of men (57% vs. 22%, p&lt;0.001), HBV infection (29% vs. 11%, p=0.004), and HCV infection (57% vs. 2%, p&lt;0.001) in the HCC group compared to the cancer-free group. EpiAgeAccel was 4.8 years higher in HIV positive patients with HCC compared to cancer-free HIV positives (p=0.02). Among HCC patients, EpiAgeAccel was 2.1 years higher in HIV positives compared to HIV negative but not statistically significant. Conclusion: Epigenetic age in ccfDNA is accelerated in HIV-positive HCC patients. EpiAgeAccel measured in ccfDNA may be developed into a surrogate biomarker for minimally invasive HCC detection among HIV-infected patients in low- and middle-income countries. Citation Format: Yinan Zheng, Claudia Hawkins, Edith Okeke, Mary Duguru, Emuobor Odeghe, Olufunmilayo Lesi, Yishu Qu, Kyeezu Kim, Brian Joyce, Jun Wang, Lewis Roberts, Demirkan Gursel, Abdulkareem Fatimah, Alani Akanmu, Godwin Imade, Jian-Jun Wei, Masha Kocherginsky, Kwang-Youn Kim, Oluwakemi Odukoya, Wasiu Adeyemo, Firas Wehbe, Chad Achenbach, Atiene Sagay, Folasade Ogunsola, Robert Murphy, Lifang Hou. Blood-Based Circulating Cell-Free DNA Epigenetic Age Is Accelerated Among HIV-Infected Patients with Hepatocellular Carcinoma in Nigeria [abstract]. In: Proceedings of the 9th Annual Symposium on Global Cancer Research; Global Cancer Research and Control: Looking Back and Charting a Path Forward; 2021 Mar 10-11. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2021;30(7 Suppl):Abstract nr 83.