Abstract
Background
Ciliary neurotrophic factor (CNTF) has been identified as a neuroprotective cytokine that can alleviate cognitive impairment in preclinical studies, although the association of cerebrospinal fluid (CSF) CNTF levels with cognitive decline and disease progression in living humans remains unclear.
Objective
This study aimed to explore the association between baseline CSF CNTF levels and the rate of cognitive decline in cognitively unimpaired (CU) and cognitively impaired (CI) older people respectively.
Methods
A total of 667 participants were included in the study, comprising 161 CU and 506 CI individuals, with an average follow-up time of 3.97 years (SD = 2.99). Linear mixed-effects models were fitted with the Mini-Mental State Examination (MMSE) scores as the primary outcome. As sensitivity analyses, we used another three commonly used cognitive measures as secondary outcomes to test the robustness of our findings. In addition, a Cox proportional hazards model was used to the mild cognitive impairment (MCI) subgroup to investigate the association between baseline CSF CNTF levels and the progression from MCI to dementia.
Results
We observed that higher baseline CSF CNTF levels were linked with a slower rate of cognitive decline in the CI group, while this association was absent in the CU group. These findings were consistent across different cognitive measures. Among MCI participants, higher levels of CSF CNTF were associated with a slower rate of disease progression to dementia.
Conclusions
The association between CSF CNTF levels and both cognitive decline and disease progression highlights the potential of CNTF as a therapeutic target in the context of Alzheimer's disease and related cognitive disorders.
Keywords
Introduction
Alzheimer's disease (AD), the most common cause of dementia in older adults, is clinically characterized by memory loss, followed by impairment in other cognitive domains.1,2 Two hallmark histopathological features of AD patients’ brains are extracellular amyloid-β plaques and intracellular neurofibrillary tangles composed of hyperphosphorylated tau proteins.3,4 This progressive nature of AD poses a major burden on patients, their families, and healthcare systems. 5 Thus, identifying modifiable factors and developing novel intervention strategies are crucial for improving the prognosis for affected older adults.
Ciliary neurotrophic factor (CNTF) is a cytokine with neuroprotective, neurotrophic, and anti-inflammatory properties that has been identified as a potential player in the pathophysiology of neurodegenerative diseases.6,7 A preclinical study has suggested that CNTF administration can mitigate cognitive decline and stabilize synaptic protein levels in an AD model. 8 Oral administration of a CNTF peptide mimetic can rescue cognitive impairment in aged rates via increasing neurogenesis and neuronal plasticity and reducing tau levels.9,10 To our knowledge, no prior investigations have explored the association between cerebrospinal fluid (CSF) CNTF levels and cognitive decline and disease progression over time in living humans.
To fill this gap, our study aimed to examine the association between baseline CSF levels of CNTF and the rate of cognitive decline in cognitively unimpaired (CU) and cognitively impaired (CI) older adults. Given the neuroprotective effect of CNTF found in preclinical studies, we hypothesized that higher baseline levels of CSF CNTF would be associated with a slower rate of cognitive decline. Furthermore, this study investigated the role of CSF CNTF in the progression from mild cognitive impairment (MCI) to dementia. Utilizing a Cox proportional hazards model, we explored the association between CNTF levels and the time to conversion to dementia among an MCI subgroup.
Methods
Alzheimer's Disease Neuroimaging Initiative (ADNI) database
The cross-sectional and longitudinal data utilized in the present study were obtained from the ADNI database, accessible at https://adni.loni.usc.edu/. Launched in 2003 as a collaborative public-private effort, ADNI's primary objective has been to investigate the effectiveness of combining various methods, such as cognitive assessments, magnetic resonance imaging (MRI), positron emission tomography (PET) scans, and other biomarkers, in tracking the progression of MCI and mild AD. For more detailed information about ADNI, please visit https://adni-info.org. The ADNI study was approved by the Institutional Review Boards at each participating site, and written informed consent was obtained from each participant or their authorized representatives.
Participants
In the present study, we selected participants who had undergone at least two assessments of the Mini-Mental State Examination (MMSE), 11 which served as our primary outcome measure, and had baseline measurements of CSF CNTF levels, which was our predictor of interest. The study included a total of 667 participants, consisting of 161 CU individuals and 506 CI individuals, which included those with MCI and mild AD dementia. For specific enrollment criteria and detailed information about the ADNI, please refer to the ADNI website (https://adni.loni.usc.edu/wp-content/uploads/2024/02/ADNI_General_Procedures_Manual_29Feb2024.pdf). Briefly, the criteria for CU included an MMSE score of 24 or higher and a Clinical Dementia Rating (CDR) 12 score of 0. For MCI, the criteria included an MMSE score of 24 or higher, a CDR score of 0.5, a subjective memory complaint, objective memory impairment as assessed by the Wechsler Memory Scale Logical Memory II, and essentially preserved abilities to perform daily life activities. For mild AD dementia, the criteria included an MMSE score between 20 and 26, a CDR score of 0.5 or 1, and meeting the National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association criteria for probable AD. 13
Cognitive outcomes
The MMSE, a global cognition measure, served as our primary outcome. The Clinical Dementia Rating Sum of Boxes (CDR-SB), 14 Alzheimer's Disease Assessment Scale Cognitive Subscale 13-item version (ADAS-Cog-13), 15 and Rey Auditory Verbal Learning Test (RAVLT) 16 total score were treated as secondary cognitive outcomes. MMSE Score ranges from 0 to 30, with higher scores indicating better cognitive performance. CDR-SB score ranges from 0 to 18, with 0 representing no impairment and 18 representing severe impairment. ADAS-Cog-13 score ranges from 0 to 85, with higher scores indicating more severe cognitive impairment. RAVLT total score ranges from 0 to 75, with 0 indicating no words recalled and 75 indicating perfect recall of all words.
Measurement of CSF Aβ42 levels and genotyping of the APOE4 allele
The CSF levels of Aβ42 were examined by the Leslie M. Shaw group at the Department of Pathology & Laboratory Medicine and the Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania (UPENN). The Roche Elecsys Aβ (1-42) CSF immunoassay was employed to measure CSF Aβ42 levels, following the manufacturer's protocol and as described in earlier studies.17,18 Values are expressed in pg/mL for Aβ42. Amyloid status (negative vs. positive) was classified using a cutoff of CSF Aβ42 levels < 1098 pg/mL, according to a previously published study. 19
The genotypes of the APOE gene, located at locus 19q13.2, for all study participants were acquired from the ADNI database, accessible at adni.loni.usc.edu.
Measurement of CSF CNTF levels
The median time interval between cognitive assessments and CSF sample collection at baseline was 6 days. CSF CNTF levels were determined as part of proteomic analytes using SomaLogic's SomaScan platform by the Neurogenomics and Informatics Center at Washington University. SomaLogic conducted preliminary standardization processes for the protein quantifications. Essentially, hybridization normalization was performed on a per-sample basis. Aptamers were then categorized into three distinct normalization cohorts—S1, S2, and S3—based on the signal-to-noise ratio observed in both technical replicates and samples. This categorization was crucial to avoid combining aptamers with different protein signal intensities for additional normalization steps. 20 Following this categorization, a median-based normalization was applied to address various assay-related inconsistencies, including variations in protein concentration, pipetting, reagent concentration, and timing of the assay. CSF CNTF levels are reported in relative fluorescence units (RFU).
Statistical analyses
Comparison of demographic and clinical variables was conducted using two-sample t-tests for continuous variables and Pearson's chi-squared (χ²) tests for categorical variables. Continuous variables were summarized as mean (standard deviation), whereas categorical variables were summarized as count (n) and percentage. At baseline, Spearman rank correlation tests were performed to examine the correlation between CSF CNTF levels and cognitive measures in the combined sample, as well as in the CU and CI groups separately. To examine the association between baseline CSF CNTF levels and longitudinal cognitive decline over time, a linear mixed-effects model with MMSE scores as the outcome was conducted. This model included age, gender, education, APOE4 carrier status (non-carriers vs. carriers), amyloid positivity (negative vs. positive, using CSF Aβ42 levels < 1098 pg/mL as the cutoff), and their interactions with follow-up time (in years). The model also included a random intercept for each subject. The number of visits at each follow-up time point is listed in Supplemental Table 1. Regarding the handling of missing values, a complete case analysis was applied in the linear mixed-effects model analysis. Specifically, a participant is included in the analysis if they have at least two non-missing visits (one of which must be the baseline visit). For participants with more than two data points, all available data points were included in the models. As secondary analyses, additional linear mixed-effects models were conducted with CDR-SB, ADAS-Cog-13, and RAVLT total scores as outcomes to test whether the results remained consistent. Finally, to examine the relationship between baseline CSF CNTF levels and disease progression from MCI to dementia, a Cox proportional hazards model was performed among MCI individuals. The Cox model was adjusted for age, gender, education, APOE4 status, and amyloid positivity. CSF CNTF levels were treated as a continuous variable. All statistical analyses were carried out using R software, 21 and the significance level was set at p < 0.05.
Results
Baseline sample characteristics by cognitive status
A total of 667 participants were included (mean age 73 ± 7 years; n = 284 [43%] female; mean level of education 16 ± 3 years; n = 330 [49%] APOE4 carriers), of whom 506 [76%] were CI. Participants were followed for 3.97 ± 2.99 years and had at least two assessments of MMSE. Comparison of demographic and clinical variables between cognitive groups (CU versus CI) is summarized in Table 1. All variables were significantly different between the two cognitive groups, except for the percentage of female gender and CSF CNTF levels.
Sample characteristics by cognitive status.
Continuous variables are summarized as Mean (SD) and categorical variables are summarized as n (%). Comparison of continuous variables was conducted using Welch Two Sample t-tests, and categorical variables were compared using Pearson's Chi-squared tests. CU: cognitively unimpaired; CI: cognitively impaired; APOE4: Apolipoprotein E; MMSE: Mini-Mental State Examination; CDR-SB: Clinical Dementia Rating Sum of Boxes; ADAS-Cog-13: Alzheimer's Disease Assessment Scale Cognitive Subscale 13-item version; RAVLT: Rey Auditory Verbal Learning Test; CNTF: ciliary neurotrophic factor; RFU: relative fluorescence units.
Cross-sectional correlation between CSF CNTF levels and cognitive performance
To explore the cross-sectional relationship between CSF CNTF levels and MMSE scores, Spearman's rank correlation tests were conducted in the combined sample, as well as in the CU and CI groups separately. In the CU participants, CSF CNTF levels were not significantly correlated with MMSE scores (rho = 0.12, p = 0.14; Figure 1A). Similarly, in the CI participants, CSF CNTF levels were not related with MMSE scores (rho = 0.06, p = 0.15; Figure 1B). In the combined sample (n = 667), CSF CNTF levels were not significantly correlated with MMSE scores (rho = 0.05, p = 0.2; Figure 1C).
Relationship between CSF CNTF levels and MMSE scores in the CU and CI groups at baseline. CU: cognitively unimpaired; CI: cognitively impaired; MMSE: Mini-Mental State Examination; CNTF: ciliary neurotrophic factor; RFU: relative fluorescence units.
Association of baseline CSF CNTF levels with cognitive decline over time in the Cu and Ci groups
Regression terms that represent associations with changes in MMSE scores over time are listed in Table 2. In the CU model, the interaction between CSF CNTF and follow-up time was not significant (coefficient: 0.005, p = 0.296; see Figure 2A), suggesting that baseline CSF CNTF levels were not associated with longitudinal cognitive decline in the CU participants. However, in the CI group, the interaction term between CSF CNTF levels and follow-up time was significant (coefficient: 0.033, p < 0.001; see Figure 2B), suggesting that baseline CSF CNTF levels were associated with longitudinal cognitive decline in the CI participants. Specifically, the positive coefficient of the interaction term (CSF CNTF × time) in the CI model suggests that higher baseline levels of CSF CNTF were associated with slower cognitive decline (higher MMSE scores indicate better cognitive performance) over time in the CI group. In the combined sample, the interaction term between CSF CNTF levels and follow-up time was significant (coefficient: 0.023, p < 0.001; see Supplemental Table 2 and Figure 2C), suggesting that higher baseline levels of CSF CNTF were associated with a slower rate of cognitive decline over time in the combined sample.
Association of baseline CSF CNTF levels with change in MMSE score over time. CSF CNTF was treated as a continuous variable in the model, while the categorization into three groups (1 SD above the mean, mean, and 1 SD below the mean) was for illustrative purposes. CU: cognitively unimpaired; CI: cognitively impaired; MMSE: Mini-Mental State Examination; CNTF: ciliary neurotrophic factor.
Summary of linear mixed-effect models.
CU: cognitively unimpaired; CI: cognitively impaired; APOE4: Apolipoprotein E; CNTF: ciliary neurotrophic factor.
As part of our sensitivity analysis, we included the CDR-SB, ADAS-Cog-13, and RAVLT total score as secondary outcomes in our models. As detailed in Supplemental Table 3, the results remained consistent across all cognitive measures. Specifically, we observed that higher baseline levels of CSF CNTF were associated with a slower rate of cognitive decline over time in the CI group, while no significant associations were found in the CU group.
Association of baseline CSF CNTF levels with clinical progression to dementia in MCI
We performed a Kaplan-Meier survival analysis to examine the association between baseline CSF CNTF levels and the time to cognitive progression from MCI to dementia. MCI participants (n = 381) were stratified into two groups based on CSF CNTF levels: low (below the median levels of 72 RFU) and high (above 72 RFU). The Kaplan-Meier curves demonstrated that individuals in the high CSF CNTF group had a significantly slower rate of progression to dementia compared to those in the low CSF CNTF group (log-rank test, p < 0.046; see Figure 3). To further examine the relationship between baseline CSF CNTF levels and disease progression from MCI to dementia, a Cox proportional hazards model was performed. The Cox model was adjusted for age, gender, education, APOE4 status, and amyloid positivity. CSF CNTF levels were treated as a continuous predictor. We found that baseline CSF CNTF levels were significantly associated with the disease progression (HR: 0.93, 95% CI: 0.88–0.98, p = 0.004; Table 3), suggesting that higher levels of CSF CNTF were associated with slower disease progression to dementia.
Survival curves based on CSF CNTF levels. The levels of CSF CNTF were categorized into two groups based on the median of 72 RFU. Disease-free survival means no progression to dementia from MCI. CNTF: ciliary neurotrophic factor.
Summary of the Cox model.
HR: hazard ratio; CI: confidence interval; APOE4: Apolipoprotein E; CNTF: ciliary neurotrophic factor.
Supplementary analyses
Due to the potential role of body mass index (BMI) in CNTF levels, 22 we further added BMI as a covariate in the models. Two participants did not have BMI data available at baseline, leading to a reduced sample size of 665 (160 CU and 505 CI participants). The results remained consistent. As shown in Supplemental Table 4, we found that higher baseline levels of CSF CNTF were associated with a slower rate of cognitive decline over time in the CI group (coefficient = 0.03, p < 0.001), whereas no significant associations were observed in the CU group (coefficient = 0.005, p = 0.33).
We further reduced the MCI sample to 70% of the total (381 participants) and reran the Cox model. As shown in Supplemental Table 5, the results remained unchanged. We found that baseline CSF CNTF levels were significantly associated with disease progression (HR: 0.93, 95% CI: 0.87–0.99, p = 0.026), suggesting that higher levels of CSF CNTF were associated with a slower rate of disease progression to dementia among MCI participants.
We included individuals with at least three MMSE assessments (one of which must be the baseline) in the linear mixed-effects models. The sample size at baseline was reduced from 667 to 640 (156 CU and 484 CI participants) because 27 individuals did not have three MMSE assessments. With this new sample, we reran the linear mixed-effects models and then extracted individualized slopes for each subject. As shown in Supplemental Figure 1, in the CU group, CSF CNTF levels were not associated with MMSE slopes (MMSE slopes represent the change in MMSE scores per year; r = 0.05, p = 0.5). In the CI group, higher CSF CNTF levels were positively associated with MMSE slopes (r = 0.09, p = 0.038), indicating that higher CSF CNTF levels were associated with a slower rate of cognitive decline over time among CI individuals.
As an additional analysis, we included Florbetapir (AV45) and Fluorodeoxyglucose (FDG) PET scans as dependent variables in the linear mixed-effects models. For AV45 PET, we included individuals who had at least two data points, resulting in a sample size of 307 (86 CU and 221 CI participants). CSF CNTF levels were not associated with changes in AV45 SUVRs over time in either the CU or CI group (see Supplemental Table 6; all p > 0.05). For FDG PET, we included individuals who had at least two data points, resulting in a sample size of 341 (96 CU and 245 CI participants). As shown in Supplemental Table 7, in the CU group, CSF CNTF levels were not associated with changes in FDG SUVRs over time (coefficient = −0.001, p = 0.372). However, in the CI group, CSF CNTF levels were significantly associated with changes in FDG SUVRs over time (coefficient = 0.001, p = 0.043).
Finally, we further added an interaction term between CNTF, Aβ status, and time in the CU and CI models to examine whether Aβ status affects the association between CNTF and cognitive decline over time. In the CU model, the interaction between CNTF, Aβ status, and time was not significant for MMSE (Supplemental Table 8; coefficient = 0.002, p = 0.887). However, in the CI model, the interaction between CNTF, Aβ status, and time was significant for MMSE (coefficient = 0.066, p < 0.001), suggesting that Aβ status may influence the association between CNTF and cognitive decline. To better understand this interaction, Supplemental Figure 2 was created to facilitate interpretation. As shown in Supplemental Figure 2, in the CI group, higher baseline CNTF levels were associated with a slower rate of cognitive decline in Aβ-positive individuals, while this association was absent in Aβ-negative individuals.
Discussion
This is the first study to examine the relationship between CSF levels of CNTF and cognitive decline and disease progression in older people with different degrees of cognitive impairment. We observed that higher baseline CSF CNTF levels were linked with a slower rate of cognitive decline, as measured by MMSE, in the CI group, while this association was absent in the CU group. Our sensitivity analyses using CDR-SB, ADAS-Cog-13, and RAVLT total scores as secondary outcomes further strengthened the robustness of the findings. Additionally, among MCI participants, higher levels of CSF CNTF were associated with a slower rate of disease progression to dementia as found in a Cox model. Our results contribute to the growing body of evidence indicating that neurotrophic factors may play a critical role in the pathophysiology of cognitive impairment and disease progression.
Our findings are consistent with previous preclinical studies demonstrating the neuroprotective effects of CNTF in animal models of AD8,23,24 and highlight the potential of targeting CNTF as a therapeutic strategy for slowing cognitive decline and disease progression. 6 The observed association between higher CSF CNTF levels and a slower rate of cognitive decline in CI individuals suggested that CNTF may counteract the detrimental effects of neurodegeneration, possibly by decreasing Aβ-induced cytotoxic events, 25 reducing tau pathology, 9 and enhancing neuroprotection and synaptic plasticity. 26 For instance, peripheral administration of Peptide 6 (P6), a CNTF mimetic, was reported to increase dentate gyrus neurogenesis, neuronal plasticity, and memory performance in adult C57Bl/6 mice. 27 Additionally, chronic treatment with Peptide 021 (P021), another CNTF mimetic, substantially decreased tau pathologies by reducing glycogen synthase kinase-3 beta (GSK3) activity in 3xTg-AD mice. 28 Investigators from the same group also found that P021 could rescue synaptic deficits and enhance neurogenesis during the synaptic compensation period. 26 However, the lack of association between CSF CNTF levels and cognitive decline in the CU group requires further investigation. One possible explanation is that CNTF may only become influential once neurodegenerative processes have initiated, and thus, its impact on cognition may not be evident in individuals without detectable cognitive impairment. Alternatively, the protective effects of CNTF may be masked by compensatory mechanisms in cognitively healthy individuals, which could mask any associations with cognitive decline. These findings may have important implications for the development of novel therapeutic strategies targeting CNTF or its signaling pathways to slow cognitive decline and disease progression in neurodegenerative diseases. Future studies should focus on elucidating the underlying mechanisms by which CNTF affects cognitive decline and disease progression, as well as exploring potential delivery methods to overcome the blood-brain barrier and optimize CNTF bioavailability. Moreover, investigating the synergistic effects of CNTF in combination with other therapeutic agents, such as Aβ-targeting drugs or tau-modifying therapies, may offer enhanced benefits for patients with AD.
The supplementary analyses suggested that CNTF levels do not seem to affect amyloid burden but are linked to a reduction in the decline of cerebral glucose metabolism, as evidenced by FDG PET imaging. This finding is consistent with CNTF's role in protecting against neurodegeneration driven by amyloid pathology and its ability to slow cognitive decline in individuals with amyloid positivity. The absence of such effects in amyloid-negative individuals suggests a potentially specific interaction between CNTF and neurodegeneration related to amyloid pathology. This suggests that CNTF may primarily exert its neuroprotective effects in the context of amyloid pathology, rather than providing generalized protection in the absence of amyloid pathology. This specificity highlights significant clinical implications for developing targeted therapeutic strategies to address neurodegenerative diseases associated with amyloid accumulation. Future studies should focus on elucidating the molecular mechanisms underlying this interaction and exploring the potential of CNTF-based interventions to mitigate neurodegenerative processes in amyloid-positive populations.
Several limitations should be taken into account. First, the observational nature of the study design precluded definitive conclusions about causality. Future interventional studies are needed to confirm our findings and explore potential mechanisms. Additionally, investigating the role of CNTF in other neurodegenerative diseases and examining the effects of modulating CNTF levels through interventional strategies could offer further insights into its therapeutic potential. Third, ADNI participants are a sample of convenience, and they are predominantly white and highly educated, which may not represent the general population. Further studies with larger sample size and more diverse populations are needed to validate the robustness of the current results. Fourth, the relationship between CNTF levels and cognitive decline was statistically significant, although the effect size appeared small. The clinical relevance of this effect still requires further investigation. Finally, future studies should evaluate the performance of the SomaScan platform relative to commonly used immunoassay techniques in measuring CSF CNTF levels.
In conclusion, the association of CSF CNTF levels with cognitive decline and disease progression highlights the potential of CNTF as a therapeutic target in the context of AD and related cognitive disorders.
Supplemental Material
sj-docx-1-alz-10.1177_13872877251329612 - Supplemental material for Association of cerebrospinal fluid ciliary neurotrophic factor levels with cognitive decline and disease progression
Supplemental material, sj-docx-1-alz-10.1177_13872877251329612 for Association of cerebrospinal fluid ciliary neurotrophic factor levels with cognitive decline and disease progression by Shanshan Wang, Li Han, Hong Ni, Shaofa Ke, Tengwei Pan and in Journal of Alzheimer's Disease
Supplemental Material
sj-docx-2-alz-10.1177_13872877251329612 - Supplemental material for Association of cerebrospinal fluid ciliary neurotrophic factor levels with cognitive decline and disease progression
Supplemental material, sj-docx-2-alz-10.1177_13872877251329612 for Association of cerebrospinal fluid ciliary neurotrophic factor levels with cognitive decline and disease progression by Shanshan Wang, Li Han, Hong Ni, Shaofa Ke, Tengwei Pan and in Journal of Alzheimer's Disease
Supplemental Material
sj-pdf-3-alz-10.1177_13872877251329612 - Supplemental material for Association of cerebrospinal fluid ciliary neurotrophic factor levels with cognitive decline and disease progression
Supplemental material, sj-pdf-3-alz-10.1177_13872877251329612 for Association of cerebrospinal fluid ciliary neurotrophic factor levels with cognitive decline and disease progression by Shanshan Wang, Li Han, Hong Ni, Shaofa Ke, Tengwei Pan and in Journal of Alzheimer's Disease
Footnotes
Acknowledgments
Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie, Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (
). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California.
Data used in preparation of this article were generated by the Neurogenomics and Informatics Center at Washington University (https://neurogenomics.wustl.edu/). As such, the investigators within the NGI provided data but did not participate in analysis or writing of this report. A complete listing of NGI investigators can be found at: ]
CSF Somalogic (7 K) and Metabolomics (Metabolon HD4) data generation and QC was supported by grants from the National Institutes of Health (RF1AG074007 (PI: Yun Ju Sung), R01AG044546 (PI: Carlos Cruchaga), P01AG003991(PI: John Morris and Carlos Cruchaga), RF1AG053303 (PI: Carlos Cruchaga), RF1AG058501 (PI: Carlos Cruchaga), and U01AG058922 (PI: Carlos Cruchaga)), and the Chan Zuckerberg Initiative (CZI), and the Alzheimer's Association Zenith Fellows Award (ZEN-22-848604, awarded to Carlos Cruchaga).
The recruitment and clinical characterization of research participants at Washington University were supported by NIH P30AG066444 (PI: John Morris and Carlos Cruchaga), P01AG03991(PI: John Morris and Carlos Cruchaga), and P01AG026276 (PI: John Morris and Carlos Cruchaga).
Ethical considerations
Not applicable.
Consent to participate
Not applicable.
Consent for publication
Not applicable.
Author contributions
Shanshan Wang (Formal analysis; Investigation; Methodology; Validation; Visualization; Writing – original draft); Li Han (Formal analysis; Investigation; Methodology; Visualization; Writing – original draft); Hong Ni (Formal analysis; Investigation; Methodology; Visualization; Writing – review & editing); Shaofa Ke (Conceptualization; Formal analysis; Investigation; Methodology; Project administration; Supervision; Validation; Writing – review & editing); Tengwei Pan (Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Supervision; Validation; Visualization; Writing – review & editing).
Funding
This work did not receive any grant from funding agencies in the public, commercial, or not-for-profit sectors.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Data availability
Data used in the present study has been made publicly available by the ADNI in the Laboratory of Neuro Imaging (LONI) database.
Supplemental material
Supplemental material for this article is available online.
References
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
