IU Indianapolis ScholarWorks :: Browsing by Author "Polsinelli, Angelina J."

Browsing by Author "Polsinelli, Angelina J."

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A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer’s disease risk and rates of disease progression
(Wiley, 2023) Bae, Jinhyeong; Logan, Paige E.; Acri, Dominic J.; Bharthur, Apoorva; Nho, Kwangsik; Saykin, Andrew J.; Risacher, Shannon L.; Nudelman, Kelly; Polsinelli, Angelina J.; Pentchev, Valentin; Kim, Jungsu; Hammers, Dustin B.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
Background: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies. Methods: We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed. Results: Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression. Discussion: The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.
APOE ε4 carrier status and sex differentiate rates of cognitive decline in early- and late-onset Alzheimer's disease
(Wiley, 2023) Polsinelli, Angelina J.; Logan, Paige E.; Lane, Kathleen A.; Manchella, Mohit K.; Nemes, Sára; Sanjay, Apoorva Bharthur; Gao, Sujuan; Apostolova, Liana G.; Neurology, School of Medicine
Background: We studied the effect of apolipoprotein E (APOE) ε4 status and sex on rates of cognitive decline in early- (EO) and late- (LO) onset Alzheimer's disease (AD). Method: We ran mixed-effects models with longitudinal cognitive measures as dependent variables, and sex, APOE ε4 carrier status, and interaction terms as predictor variables in 998 EOAD and 2562 LOAD participants from the National Alzheimer's Coordinating Center. Results: APOE ε4 carriers showed accelerated cognitive decline relative to non-carriers in both EOAD and LOAD, although the patterns of specific cognitive domains that were affected differed. Female participants showed accelerated cognitive decline relative to male participants in EOAD only. The effect of APOE ε4 was greater in EOAD for executive functioning (p < 0.0001) and greater in LOAD for language (p < 0.0001). Conclusion: We found APOE ε4 effects on cognitive decline in both EOAD and LOAD and female sex in EOAD only. The specific patterns and magnitude of decline are distinct between the two disease variants. Highlights: Apolipoprotein E (APOE) ε4 carrier status and sex differentiate rates of cognitive decline in early-onset (EO) and late-onset (LO) Alzheimer's disease (AD). APOE ε4 in EOAD accelerated decline in memory, executive, and processing speed domains. Female sex in EOAD accelerated decline in language, memory, and global cognition. The effect of APOE ε4 was stronger for language in LOAD and for executive function in EOAD. Sex effects on language and executive function decline differed between EOAD and LOAD.
APOE-ε4 is associated with earlier symptom onset in LOAD but later symptom onset in EOAD
(Wiley, 2023) Polsinelli, Angelina J.; Lane, Kathleen A.; Manchella, Mohit K.; Logan, Paige E.; Gao, Sujuan; Apostolova, Liana G.; Neurology, School of Medicine
Background: We studied the effect of apolipoprotein E (APOE) ε4 status and sex on age of symptom onset (AO) in early- (EO) and late- (LO) onset Alzheimer's disease (AD). Method: A total of 998 EOAD and 2562 LOAD participants from the National Alzheimer's Coordinating Center (NACC) were included. We used analysis of variance to examine AO differences between sexes and APOE genotypes and the effect of APOE ε4, sex, and their interaction on AO in EOAD and LOAD, separately. Results: APOE ε4 carriers in LOAD had younger AO and in EOAD had older AO. Female EOAD APOE ε4 carriers had older AO compared to non-carriers (P < 0.0001). There was no difference for males. Both male and female LOAD APOE ε4 carriers had younger AO relative to non-carriers (P < 0.0001). Conclusion: The observed earlier AO in EOAD APOE ε4 non-carriers relative to carriers, particularly in females, suggests the presence of additional AD risk variants.
Atypical Alzheimer Disease Variants
(Wolters Kluwer, 2022) Polsinelli, Angelina J.; Apostolova, Liana G.; Neurology, School of Medicine
Purpose of review: This article discusses the clinical, neuroimaging, and biomarker profiles of sporadic atypical Alzheimer disease (AD) variants, including early-onset AD, posterior cortical atrophy, logopenic variant primary progressive aphasia, dysexecutive variant and behavioral variant AD, and corticobasal syndrome. Recent findings: Significant advances are being made in the recognition and characterization of the syndromically diverse AD variants. These variants are identified by the predominant cognitive and clinical features: early-onset amnestic syndrome, aphasia, visuospatial impairments, dysexecutive and behavioral disturbance, or motor symptoms. Although understanding of regional susceptibility to disease remains in its infancy, visualizing amyloid and tau pathology in vivo and CSF examination of amyloid-β and tau proteins are particularly useful in atypical AD, which can be otherwise prone to misdiagnosis. Large-scale research efforts, such as LEADS (the Longitudinal Early-Onset Alzheimer Disease Study), are currently ongoing and will continue to shed light on our understanding of these diverse presentations. Summary: Understanding the clinical, neuroimaging, and biomarker profiles of the heterogeneous group of atypical AD syndromes improves diagnostic accuracy in patients who are at increased risk of misdiagnosis. Earlier accurate identification facilitates access to important interventions, social services and disability assistance, and crucial patient and family education.
Barriers and facilitators to participating in Alzheimer’s disease biomarker research in Black and White older adults
(Wiley, 2023-06-05) Eliacin, Johanne; Polsinelli, Angelina J.; Epperson, Francine; Gao, Sujuan; Van Heiden, Sarah; Westmoreland, Glenda; Richards, Ralph; Richards, Mollie; Campbell, Christopher; Hendrie, Hugh; Risacher, Shannon L.; Saykin, Andrew J.; Wang, Sophia; Medicine, School of Medicine
Introduction: The study examined Black and White prospective participants' views of barriers to and facilitators of participation in Alzheimer's disease (AD) biomarker research. Methods: In a mixed-methods study, 399 community-dwelling Black and White older adults (age ≥55) who had never participated in AD research completed a survey about their perceptions of AD biomarker research. Individuals from lower socioeconomic and education backgrounds and Black men were over-sampled to address perspectives of traditionally under-represented groups. A subset of participants (n = 29) completed qualitative interviews. Results: Most participants expressed interest in biomarker research (overall 69%). However, Black participants were comparatively more hesitant than White participants (28.9% vs 15.1%), were more concerned about study risks (28.9% vs 15.1%), and perceived multiple barriers to participating in brain scans. These results persisted even after adjusting for trust and perceived knowledge of AD. Information was a primary barrier (when absent) and incentive (when provided) for AD biomarker research participation. Black older adults desired more information about AD (eg, risk, prevention), general research processes, and specific biomarker procedures. They also desired return of results to make informed decisions about their health, research-sponsored community awareness events, and for researchers to mitigate the burden placed on participants in research (eg, transportation, basic needs). Conclusion: Our findings increase representativeness in the literature by focusing on individuals with no history of AD research experience and those from traditionally underrepresented groups in research. Results suggest that the research community needs to improve information sharing and raising awareness, increase their presence in the communities of underrepresented groups, reduce incidental costs, and provide valuable personal health information to participants to increase interest. Specific recommendations for improving recruitment are addressed. Future studies will assess the implementation of evidence-based, socioculturally sensitive recruitment strategies to increase enrollment of Black older adults into AD biomarker studies. HIGHLIGHTS: Individuals from under-represented groups are interested in Alzheimer's disease (AD) biomarker research. After adjusting for trust and AD knowledge, Black participants were still more hesitant .Information is a barrier (when absent) to and incentive (when given) for biomarker studies. Reducing burden (e.g., transportation) is essential for recruiting Black older adults.
Baseline neuropsychiatric symptoms and psychotropic medication use midway through data collection of the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) cohort
(Wiley, 2023) Polsinelli, Angelina J.; Wonderlin, Ryan J.; Hammers, Dustin B.; Pena Garcia, Alex; Eloyan, Anii; Taurone, Alexander; Thangarajah, Maryanne; Beckett, Laurel; Gao, Sujuan; Wang, Sophia; Kirby, Kala; Logan, Paige E.; Aisen, Paul; Dage, Jeffrey L.; Foroud, Tatiana; Griffin, Percy; Iaccarino, Leonardo; Kramer, Joel H.; Koeppe, Robert; Kukull, Walter A.; La Joie, Renaud; Mundada, Nidhi S.; Murray, Melissa E.; Nudelman, Kelly; Soleimani-Meigooni, David N.; Rumbaugh, Malia; Toga, Arthur W.; Touroutoglou, Alexandra; Vemuri, Prashanthi; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph; Mendez, Mario F.; Womack, Kyle; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily; Salloway, Steven; Sha, Sharon J.; Turner, Raymond S.; Wingo, Thomas S.; Wolk, David A.; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; LEADS Consortium; Neurology, School of Medicine
Introduction: We examined neuropsychiatric symptoms (NPS) and psychotropic medication use in a large sample of individuals with early-onset Alzheimer's disease (EOAD; onset 40-64 years) at the midway point of data collection for the Longitudinal Early-onset Alzheimer's Disease Study (LEADS). Methods: Baseline NPS (Neuropsychiatric Inventory - Questionnaire; Geriatric Depression Scale) and psychotropic medication use from 282 participants enrolled in LEADS were compared across diagnostic groups - amyloid-positive EOAD (n = 212) and amyloid negative early-onset non-Alzheimer's disease (EOnonAD; n = 70). Results: Affective behaviors were the most common NPS in EOAD at similar frequencies to EOnonAD. Tension and impulse control behaviors were more common in EOnonAD. A minority of participants were using psychotropic medications, and use was higher in EOnonAD. Discussion: Overall NPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants. Future research will investigate moderators and etiological drivers of NPS, and NPS differences in EOAD versus late-onset AD. Keywords: early-onset Alzheimer's disease; early-onset dementia; mild cognitive impairment; neuropharmacology; neuropsychiatric symptoms; psychotropic medications.
Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes
(IOS Press, 2023) Hammers, Dustin B.; Lin, Joshua H.; Polsinelli, Angelina J.; Logan, Paige E.; Risacher, Shannon L.; Schwarz, Adam J.; Apostolova, Liana G.; Alzheimer’s Disease Neuroimaging Initiative; Neurology, School of Medicine
Background: Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed. Objective: The aim of the current study is to establish criterion validity to support these recently-developed staging schemes. Methods: Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods. Results: Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates. Conclusions: Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.
Deep multiple instance learning for foreground speech localization in ambient audio from wearable devices
(Springer, 2021) Hebbar, Rajat; Papadopoulos, Pavlos; Reyes, Ramon; Danvers, Alexander F.; Polsinelli, Angelina J.; Moseley, Suzanne A.; Sbarra, David A.; Mehl, Matthias R.; Narayanan, Shrikanth; Neurology, School of Medicine
Over the recent years, machine learning techniques have been employed to produce state-of-the-art results in several audio related tasks. The success of these approaches has been largely due to access to large amounts of open-source datasets and enhancement of computational resources. However, a shortcoming of these methods is that they often fail to generalize well to tasks from real life scenarios, due to domain mismatch. One such task is foreground speech detection from wearable audio devices. Several interfering factors such as dynamically varying environmental conditions, including background speakers, TV, or radio audio, render foreground speech detection to be a challenging task. Moreover, obtaining precise moment-to-moment annotations of audio streams for analysis and model training is also time-consuming and costly. In this work, we use multiple instance learning (MIL) to facilitate development of such models using annotations available at a lower time-resolution (coarsely labeled). We show how MIL can be applied to localize foreground speech in coarsely labeled audio and show both bag-level and instance-level results. We also study different pooling methods and how they can be adapted to densely distributed events as observed in our application. Finally, we show improvements using speech activity detection embeddings as features for foreground detection.
Differences in baseline cognitive performance between participants with early-onset and late-onset Alzheimer's disease: Comparison of LEADS and ADNI
(Wiley, 2025) Hammers, Dustin B.; Eloyan, Ani; Thangarajah, Maryanne; Taurone, Alexander; Beckett, Laurel; Gao, Sujuan; Polsinelli, Angelina J.; Kirby, Kala; Dage, Jeffrey L.; Nudelman, Kelly; Aisen, Paul; Reman, Rema; La Joie, Renaud; Lagarde, Julien; Atri, Alireza; Clark, David; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Honig, Lawrence S.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Womack, Kyle; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Grant, Ian; Rogalski, Emily; Johnson, Erik C. B.; Salloway, Steven; Sha, Sharon J.; Turner, Raymond Scott; Wingo, Thomas S.; Wolk, David A.; Carrillo, Maria C.; Dickerson, Bradford C.; Rabinovici, Gil D.; Apostolova, Liana G.; LEADS Consortium 1 for the Alzheimer's Disease Neuroimaging Initiative; Neurology, School of Medicine
Introduction: Early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) share similar amyloid etiology, but evidence from smaller-scale studies suggests that they manifest differently clinically. Current analyses sought to contrast the cognitive profiles of EOAD and LOAD. Methods: Z-score cognitive-domain composites for 311 amyloid-positive sporadic EOAD and 314 amyloid-positive LOAD participants were calculated from baseline data from age-appropriate control cohorts. Z-score composites were compared between AD groups for each domain. Results: After controlling for cognitive status, EOAD displayed worse visuospatial, executive functioning, and processing speed/attention skills relative to LOAD, and LOAD displayed worse language, episodic immediate memory, and episodic delayed memory. Discussion: Sporadic EOAD possesses distinct cognitive profiles relative to LOAD. Clinicians should be alert for non-amnestic impairments in younger patients to ensure proper identification and intervention using disease-modifying treatments. Highlights: Both early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease (LOAD) participants displayed widespread cognitive impairments relative to their same-aged peers. Cognitive impairments were more severe for EOAD than for LOAD participants in visuospatial and executive domains. Memory and language impairments were more severe for LOAD than for EOAD participants Results were comparable after removing clinical phenotypes of posterior cortical atrophy (PCA), primary progressive aphasia (lv-PPA), and frontal-variant AD.
Dissociable spatial topography of cortical atrophy in early‐onset and late‐onset Alzheimer's disease: A head‐to‐head comparison of the LEADS and ADNI cohorts
(Wiley, 2025) Katsumi, Yuta; Touroutoglou, Alexandra; Brickhouse, Michael; Eloyan, Ani; Eckbo, Ryan; Zaitsev, Alexander; La Joie, Renaud; Lagarde, Julien; Schonhaut, Daniel; Thangarajah, Maryanne; Taurone, Alexander; Vemuri, Prashanthi; Jack, Clifford R., Jr.; Dage, Jeffrey L.; Nudelman, Kelly N. H.; Foroud, Tatiana; Hammers, Dustin B.; Ghetti, Bernardino; Murray, Melissa E.; Newell, Kathy L.; Polsinelli, Angelina J.; Aisen, Paul; Reman, Rema; Beckett, Laurel; Kramer, Joel H.; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Grant, Ian M.; Honig, Lawrence S.; Johnson, Erik C. B.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily; Salloway, Stephen; Sha, Sharon; Turner, R. Scott; Wingo, Thomas S.; Wolk, David A.; Womack, Kyle; Carrillo, Maria C.; Rabinovici, Gil D.; Apostolova, Liana G.; Dickerson, Bradford C.; LEADS Consortium for the Alzheimer's Disease Neuroimaging Initiative; Neurology, School of Medicine
Introduction: Early-onset and late-onset Alzheimer's disease (EOAD and LOAD, respectively) have distinct clinical manifestations, with prior work based on small samples suggesting unique patterns of neurodegeneration. The current study performed a head-to-head comparison of cortical atrophy in EOAD and LOAD, using two large and well-characterized cohorts (LEADS and ADNI). Methods: We analyzed brain structural magnetic resonance imaging (MRI) data acquired from 377 sporadic EOAD patients and 317 sporadicLOAD patients who were amyloid positive and had mild cognitive impairment (MCI) or mild dementia (i.e., early-stage AD), along with cognitively unimpaired participants. Results: After controlling for the level of cognitive impairment, we found a double dissociation between AD clinical phenotype and localization/magnitude of atrophy, characterized by predominant neocortical involvement in EOAD and more focal anterior medial temporal involvement in LOAD. Discussion: Our findings point to the clinical utility of MRI-based biomarkers of atrophy in differentiating between EOAD and LOAD, which may be useful for diagnosis, prognostication, and treatment. Highlights: Early-onset Alzheimer's disease (EOAD) and late-onset AD (LOAD) patients showed distinct and overlapping cortical atrophy patterns. EOAD patients showed prominent atrophy in widespread neocortical regions. LOAD patients showed prominent atrophy in the anterior medial temporal lobe. Regional atrophy was correlated with the severity of global cognitive impairment. Results were comparable when the sample was stratified for mild cognitive impairment (MCI) and dementia.

Browsing by Author "Polsinelli, Angelina J."

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