Su, Yi

Learning from multimodal data sets can leverage complementary information and lead to improved performance for prediction tasks. A commonly used strategy to account for feature correlations in high-dimensional data sets is the latent variable approach. Several latent variable methods have been proposed for multimodal data sets; however, these methods either focus on extracting a shared component across all modalities or extracting a shared component and individual components specific to each modality, overlooking correlations within partial subsets of modalities. We propose multimodal fission learning (MMFL), the first supervised latent variable model that adopts a generalizable decomposition into globally joint, partially joint, and individual components from multimodal data sets. A key strength of MMFL is a natural extension to incorporate incomplete multimodal data in either training and test phases by leveraging the learned modality structure. Through simulation studies, we demonstrate that MMFL outperforms a variety of existing multimodal algorithms under both complete modality and incomplete modality settings. We applied MMFL to two real-world case studies: early prediction of Alzheimer’s disease using neuroimaging and genetic data and predicting posttraumatic headache improvement using clinical data collected via questionnaires and brain neuroimaging data. MMFL achieved improved predictive accuracy and enhanced interpretability offering insights for within- and cross-modal relationships of multimodal data sets. History: Rema Padman served as the senior editor for this article. Funding: This research was supported by the National Institutes of Health [Grants 2R42AG053149-02A1, R01AG069453, 30AG072980, R01AG069453, and 1R61NS113315-01], the National Science Foundation [Grant DMS-2053170], and the Department of Defense [Award W81XWH-19-0534]. The grantee organization is the Northern California Institute for Research and Education. In the past, ADNI has also received funding from the National Institute of Biomedical Imaging and Bioengineering, the Canadian Institutes of Health Research, and private sector contributions through the Foundation for the National Institutes of Health including 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. Data Ethics & Reproducibility Note: The code capsule is available at https://github.com/lingchm/MMFL and in the e-Companion to this article (available at https://doi.org/10.1287/ijds.2024.0059 ).

Abstract Repetitive head impacts are associated with structural brain changes and an increased risk for chronic traumatic encephalopathy, a progressive neurodegenerative disease that can only be diagnosed after death. Chronic traumatic encephalopathy is defined by the abnormal accumulation of phosphorylated tau protein, particularly at the depths of the superior frontal sulci, suggesting that sulcal morphology may serve as a relevant structural biomarker. Contact sport athletes, such as former football players, are at elevated risk due to their prolonged exposure to repetitive head impacts. Cortical atrophy linked to underlying tau accumulation may result in shallower and wider sulci, potentially making sulcal morphology an imaging marker for identifying individuals at risk for this disease. This study investigated sulcal morphological differences in former football players and examined associations with age, football-related exposure, clinical diagnosis of traumatic encephalopathy syndrome, levels of certainty for chronic traumatic encephalopathy pathology, neuropsychological performance, and positron emission tomography imaging using flortaucipir. We analysed structural magnetic resonance imaging data from 169 male former football players (mean age 57.2 (8.2) years, range 45–74) and 54 age-matched, unexposed asymptomatic male controls (mean age 59.4 (8.5) years, range 45–74). Sulcal depth and width were quantified using the CalcSulc, focusing on two regions in each hemisphere commonly affected by chronic traumatic encephalopathy pathology: the superior frontal and occipitotemporal sulci. Generalized least squares models were used to assess group differences and interactions with age and football exposure variables, including age of first exposure, total years played, and cumulative head impact exposure. An analysis of covariance evaluated relationships between sulcal morphology, clinical measures, and flortaucipir uptake, adjusting for age, race, body mass index, education, imaging site, apolipoprotein E4 status, and total intracranial volume. Former football players demonstrated significantly shallower sulcal depth in the left superior frontal sulcus compared to unexposed controls. Earlier age of first exposure and longer football careers were associated with greater widening of the left occipitotemporal sulcus. Higher cumulative head impact exposure was linked to reduced sulcal depth in the left superior frontal region. However, sulcal morphology was not associated with clinical diagnosis, levels of certainty, neuropsychological test performance, or flortaucipir imaging. These findings suggest that sulcal morphology may reflect cumulative exposure to repetitive head impacts, particularly in brain regions vulnerable to chronic traumatic encephalopathy pathology. Future ante- and post-mortem validation studies are needed to determine whether sulcal morphology can serve as a reliable in vivo biomarker of risk.

Background: Amyloid-β (Aβ) plaques play a pivotal role in Alzheimer’s disease. The current positron emission tomography (PET) is expensive and limited in availability. In contrast, blood-based biomarkers (BBBMs) show potential for characterizing Aβ plaques more affordably. We have previously proposed an MRI-based hippocampal morphometry measure to be an indicator of Aβ plaques. Objective: To develop and validate an integrated model to predict brain amyloid PET positivity combining MRI feature and plasma Aβ42/40 ratio. Methods: We extracted hippocampal multivariate morphometry statistics from MR images and together with plasma Aβ42/40 trained a random forest classifier to perform a binary classification of participant brain amyloid PET positivity. We evaluated the model performance using two distinct cohorts, one from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the other from the Banner Alzheimer’s Institute (BAI), including prediction accuracy, precision, recall rate, F1 score, and AUC score. Results: Results from ADNI (mean age 72.6, Aβ+ rate 49.5%) and BAI (mean age 66.2, Aβ+ rate 36.9%) datasets revealed the integrated multimodal (IMM) model’s superior performance over unimodal models. The IMM model achieved prediction accuracies of 0.86 in ADNI and 0.92 in BAI, surpassing unimodal models based solely on structural MRI (0.81 and 0.87) or plasma Aβ42/40 (0.73 and 0.81) predictors. CONCLUSIONS: Our IMM model, combining MRI and BBBM data, offers a highly accurate approach to predict brain amyloid PET positivity. This innovative multiplex biomarker strategy presents an accessible and cost-effective avenue for advancing Alzheimer’s disease diagnostics, leveraging diverse pathologic features related to Aβ plaques and structural MRI.

AbstractINTRODUCTIONAmyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin‐1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre‐/postcodon 200) influences these pathologic features and dementia at different stages.METHODSIndividuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross‐sectionally evaluated regional Pittsburgh compound B‐positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging‐based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition.RESULTSPostcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures.DISCUSSIONWe demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials.Highlights Mutation position influences Aβ burden, SVD, and dementia. PSEN1 pre‐200 group had stronger associations between Aβ burden and disease stage. PSEN1 post‐200 group had stronger associations between SVD markers and disease stage. PSEN1 post‐200 group had worse dementia score than pre‐200 in late disease stage. Diffusion tensor imaging‐based SVD markers mediated mutation position effects on dementia in the late stage.

AbstractBackgroundChronic traumatic encephalopathy (CTE) is a neurodegenerative disease thought to be caused, in part, by repetitive head impact (RHI) exposure and characterized by phosphorylated tau deposition with varying patterns in the cerebral cortex. Flortaucipir tau PET data from the DIAGNOSE CTE Research Project was examined to investigate tau PET patterns and its relation to RHI exposure in former professional and college American football players.MethodIn this study, 218 DIAGNOSE CTE participants, ages 45‐74, with flortaucipir PET were included; 104 were former National Football League players (PRO), 58 were former college football players (COL), and 56 had no history of contact sports, other exposure to RHI, or traumatic brain injury (UE). Regional flortaucipir uptake was quantified using established procedures for three previously defined statistical regions (superior frontal, left parietal, and medial temporal) and compared across the three groups. Association analyses were also performed to examine the relationship between flortaucipir uptake and exposure to RHI using the cumulative head impact index for linear acceleration g‐force (CHII‐G). The potential clinical utility of flortaucipir PET for CTE was also investigated by examining its ability to differentiate participants meeting criteria for traumatic encephalopathy syndrome (TES) and probable or possible level of certainty for CTE pathology from those who do not meet those criteria.ResultSignificantly higher flortaucipir uptake was observed in former football players than in participants without RHI exposure, controlling for age and race for the superior frontal region (Fig. 1A), left parietal, and medial temporal regions. Association between regional flortaucipir uptake and CHII‐G was only observed in the superior frontal region in former players (PRO+COL) 60 years and older (Fig. 1B) and no association was observed in the full PRO+COL group. Flortaucipir PET was not able to differentiate TES groups in former football players (Fig. 1C).ConclusionElevated flortaucipir uptake was observed in former American football players to a group of unexposed men. The association between flortaucipir uptake and exposure to RHI may require a long latent period to manifest. Further investigation of more sensitive tau PET tracers and quantification techniques is warranted to better characterize CTE related tau pathology.

AbstractINTRODUCTIONTau is a key pathology in chronic traumatic encephalopathy (CTE). Here, we report our findings in tau positron emission tomography (PET) measurements from the DIAGNOSE CTE Research Project.METHODWe compare flortaucipir PET measures from 104 former professional players (PRO), 58 former college football players (COL), and 56 same‐age men without exposure to repetitive head impacts (RHI) or traumatic brain injury (unexposed [UE]); characterize their associations with RHI exposure; and compare players who did or did not meet diagnostic criteria for traumatic encephalopathy syndrome (TES).RESULTSSignificantly elevated flortaucipir uptake was observed in former football players (PRO+COL) in prespecified regions (p < 0.05). Association between regional flortaucipir uptake and estimated cumulative head impact exposure was only observed in the superior frontal region in former players over 60 years old. Flortaucipir PET was not able to differentiate TES groups.DISCUSSIONAdditional studies are needed to further understand tau pathology in CTE and other individuals with a history of RHI.

Background: Alzheimer’s disease (AD) is the most common type of age-related dementia, affecting 6.2 million people aged 65 or older according to CDC data. It is commonly agreed that discovering an effective AD diagnosis biomarker could have enormous public health benefits, potentially preventing or delaying up to 40% of dementia cases. Tau neurofibrillary tangles are the primary driver of downstream neurodegeneration and subsequent cognitive impairment in AD, resulting in structural deformations such as hippocampal atrophy that can be observed in magnetic resonance imaging (MRI) scans. Objective: To build a surface-based model to 1) detect differences between APOE subgroups in patterns of tau deposition and hippocampal atrophy, and 2) use the extracted surface-based features to predict cognitive decline. Methods: Using data obtained from different institutions, we develop a surface-based federated Chow test model to study the synergistic effects of APOE, a previously reported significant risk factor of AD, and tau on hippocampal surface morphometry. Results: We illustrate that the APOE-specific morphometry features correlate with AD progression and better predict future AD conversion than other MRI biomarkers. For example, a strong association between atrophy and abnormal tau was identified in hippocampal subregion cornu ammonis 1 (CA1 subfield) and subiculum in e4 homozygote cohort. Conclusion: Our model allows for identifying MRI biomarkers for AD and cognitive decline prediction and may uncover a corner of the neural mechanism of the influence of APOE and tau deposition on hippocampal morphology.