Browsing by Author "Brosch, Jared"

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    BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity
    (medRxiv, 2023-12-05) Dempsey, Desarae A.; Deardorff, Rachael; Wu, Yu-Chien; Yu, Meichen; Apostolova, Liana G.; Brosch, Jared; Clark, David G.; Farlow, Martin R.; Gao, Sujuan; Wang, Sophia; Saykin, Andrew J.; Risacher, Shannon L.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    The BrainAGE method is used to estimate biological brain age using structural neuroimaging. However, the stability of the model across different scan parameters and races/ethnicities has not been thoroughly investigated. Estimated brain age was compared within- and across- MRI field strength and across voxel sizes. Estimated brain age gap (BAG) was compared across demographically matched groups of different self-reported races and ethnicities in ADNI and IMAS cohorts. Longitudinal ComBat was used to correct for potential scanner effects. The brain age method was stable within field strength, but less stable across different field strengths. The method was stable across voxel sizes. There was a significant difference in BAG between races, but not ethnicities. Correction procedures are suggested to eliminate variation across scanner field strength while maintaining accurate brain age estimation. Further studies are warranted to determine the factors contributing to racial differences in BAG.
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    Comparison of Risk Factor Control in the Year After Discharge for Ischemic Stroke Versus Acute Myocardial Infarction
    (American Heart Association, 2018-02) Bravata, Dawn M.; Daggy, Joanne; Brosch, Jared; Sico, Jason J.; Baye, Fitsum; Myers, Laura J.; Roumie, Christianne L.; Cheng, Eric; Coffing, Jessica; Arling, Greg; Medicine, School of Medicine
    BACKGROUND AND PURPOSE: The Veterans Health Administration has engaged in quality improvement to improve vascular risk factor control. We sought to examine blood pressure (<140/90 mm Hg), lipid (LDL [low-density lipoprotein] cholesterol <100 mg/dL), and glycemic control (hemoglobin A1c <9%), in the year post-hospitalization for acute ischemic stroke or acute myocardial infarction (AMI). METHODS: We identified patients who were hospitalized (fiscal year 2011) with ischemic stroke, AMI, congestive heart failure, transient ischemic attack, or pneumonia/chronic obstructive pulmonary disease. The primary analysis compared risk factor control after incident ischemic stroke versus AMI. Facilities were included if they cared for ≥25 ischemic stroke and ≥25 AMI patients. A generalized linear mixed model including patient- and facility-level covariates compared risk factor control across diagnoses. RESULTS: Forty thousand two hundred thirty patients were hospitalized (n=75 facilities): 2127 with incident ischemic stroke and 4169 with incident AMI. Fewer stroke patients achieved blood pressure control than AMI patients (64%; 95% confidence interval, 0.62-0.67 versus 77%; 95% confidence interval, 0.75-0.78; P<0.0001). After adjusting for patient and facility covariates, the odds of blood pressure control were still higher for AMI than ischemic stroke patients (odds ratio, 1.39; 95% confidence interval, 1.21-1.51). There were no statistical differences for AMI versus stroke patients in hyperlipidemia (P=0.534). Among patients with diabetes mellitus, the odds of glycemic control were lower for AMI than ischemic stroke patients (odds ratio, 0.72; 95% confidence interval, 0.54-0.96). CONCLUSIONS: Given that hypertension control is a cornerstone of stroke prevention, interventions to improve poststroke hypertension management are needed
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    Feasibility and Acceptability of Using Plasma Biomarkers for Diagnosing Alzheimer’s Disease in Primary Care
    (Oxford University Press, 2023-12-21) Fowler, Nicole; Swartzell, Kristen; Hammers, Dustin; Brosch, Jared; Murray, James; Willis, Deanna; Medicine, School of Medicine
    Blood-based biomarkers (Aβ, P-tau, neurofilament light) are clinically available to aid in the diagnosis of Alzheimer’s disease and related dementias (ADRD). However, no research has examined the use of blood biomarkers to aid in the diagnosis of ADRD in primary care (PC). Our study will test feasibility and acceptability of implementing blood-based biomarkers for ADRD in PC. Participants include: all PC patients ≥65 years presenting to one of six PC clinics between 6/1/22 and 5/31/23 who score cognitively impaired on the Linus Health Digital Clock and Recall (DCR™), and PC providers (PCPs) of these patients. Patients will view a decision guide about biomarkers and complete the Concerns about Alzheimer’s Disease Dementia Scale, and the Future Time Perspective Scale and the Impact of Events Scale. These measures and the PHQ-9 and GAD-7 will be repeated within 2 weeks of results disclosure. PCPs will receive training on biomarker disclosure techniques and best practices. To date 9 PCPs have consented to provide the biomarker results disclosure and 11 have declined. Following completion of PCP consent (n=100), a total of 200 patients who failed the DCR are eligible to be approached for consent. By November 2023, we anticipate that 150 patients will have completed biomarker testing, and we will have examined the biomarker results in the context of patient neuropsychological and clinical data, comorbidities, and sociodemographic information. This study will provide information regarding feasibility and utility of ADRD biomarkers in PC and a preliminary analysis of biomarker results compared with the patients’ clinical profiles.
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    Implementation of a Digital Cognitive Screening Program for Dementia in Primary Care
    (Oxford University Press, 2023-12-21) Fowler, Nicole; Mullavey, Judy; Swartzell, Kristen; Hammers, Dustin; Brosch, Jared; Murray, James; Willis, Deanna; Medicine, School of Medicine
    Early identification of Alzheimer’s disease and related dementias (ADRD) has become paramount given the emergence of disease modifying therapies. Integration of rapid, scalable tools to identify early cognitive impairment in primary care is essential because most at-risk individuals have limited access to specialty care. Yet, competing demands on primary care practices can make integration challenging. This demonstration project is being conducted to understand the feasibility, acceptability, and implementation of digital cognitive screening in primary care. Patients ≥65 years presenting to one of six primary care sites between 06/01/2022 and 06/30/2023 are asked to complete the Linus Health Digital Clock and Recall (DCR™) cognitive screening. Data regarding number of screening attempts that were refused, incomplete, or completed was collected. Results of the first completed screening-results were analyzed using descriptive statistics. As of 2/15/23, there are 3,920 screening attempts. DCR™ screenings were completed 40.8% of the time, refused 57.4%, and attempted but incomplete 1.8%. Thirteen-percent of attempts were positive for cognitive impairment, 37% were borderline, 44% were unimpaired, and 6% were unanalyzable. Average patient age is 73.2±6.0 years, 58% female, and 6% report less than high school education. Patients with positive screenings are older, slightly more female, and reported less education. Cognitive screening via DCR™ is ongoing and has been completed in nearly half of those approached, with half scoring cognitively impaired or borderline. This approach appears to have utility in early detection of cognitive impairment in primary care. By November 2023 we will have follow-up data for patients who screened positive.
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    Longitudinal head-to-head comparison of 11C-PiB and 18F-florbetapir PET in a Phase 2/3 clinical trial of anti-amyloid-β monoclonal antibodies in dominantly inherited Alzheimer disease
    (Springer, 2023) Chen, Charles D.; McCullough, Austin; Gordon, Brian; Joseph-Mathurin, Nelly; Flores, Shaney; McKay, Nicole S.; Hobbs, Diana A.; Hornbeck, Russ; Fagan, Anne M.; Cruchaga, Carlos; Goate, Alison M.; Perrin, Richard J.; Wang, Guoqiao; Li, Yan; Shi, Xinyu; Xiong, Chengjie; Pontecorvo, Michael J.; Klein, Gregory; Su, Yi; Klunk, William E.; Jack, Clifford; Koeppe, Robert; Snider, B. Joy; Berman, Sarah B.; Roberson, Erik D.; Brosch, Jared; Surti, Ghulam; Jiménez-Velázquez, Ivonne Z.; Galasko, Douglas; Honig, Lawrence S.; Brooks, William S.; Clarnette, Roger; Wallon, David; Dubois, Bruno; Pariente, Jérémie; Pasquier, Florence; Sanchez-Valle, Raquel; Shcherbinin, Sergey; Higgins, Ixavier; Tunali, Ilke; Masters, Colin L.; van Dyck, Christopher H.; Masellis, Mario; Hsiung, Robin; Gauthier, Serge; Salloway, Steve; Clifford, David B.; Mills, Susan; Supnet-Bell, Charlene; McDade, Eric; Bateman, Randall J.; Benzinger, Tammie L. S.; DIAN-TU Study Team; Neurology, School of Medicine
    Purpose: Pittsburgh Compound-B (11C-PiB) and 18F-florbetapir are amyloid-β (Aβ) positron emission tomography (PET) radiotracers that have been used as endpoints in Alzheimer's disease (AD) clinical trials to evaluate the efficacy of anti-Aβ monoclonal antibodies. However, comparing drug effects between and within trials may become complicated if different Aβ radiotracers were used. To study the consequences of using different Aβ radiotracers to measure Aβ clearance, we performed a head-to-head comparison of 11C-PiB and 18F-florbetapir in a Phase 2/3 clinical trial of anti-Aβ monoclonal antibodies. Methods: Sixty-six mutation-positive participants enrolled in the gantenerumab and placebo arms of the first Dominantly Inherited Alzheimer Network Trials Unit clinical trial (DIAN-TU-001) underwent both 11C-PiB and 18F-florbetapir PET imaging at baseline and during at least one follow-up visit. For each PET scan, regional standardized uptake value ratios (SUVRs), regional Centiloids, a global cortical SUVR, and a global cortical Centiloid value were calculated. Longitudinal changes in SUVRs and Centiloids were estimated using linear mixed models. Differences in longitudinal change between PET radiotracers and between drug arms were estimated using paired and Welch two sample t-tests, respectively. Simulated clinical trials were conducted to evaluate the consequences of some research sites using 11C-PiB while other sites use 18F-florbetapir for Aβ PET imaging. Results: In the placebo arm, the absolute rate of longitudinal change measured by global cortical 11C-PiB SUVRs did not differ from that of global cortical 18F-florbetapir SUVRs. In the gantenerumab arm, global cortical 11C-PiB SUVRs decreased more rapidly than global cortical 18F-florbetapir SUVRs. Drug effects were statistically significant across both Aβ radiotracers. In contrast, the rates of longitudinal change measured in global cortical Centiloids did not differ between Aβ radiotracers in either the placebo or gantenerumab arms, and drug effects remained statistically significant. Regional analyses largely recapitulated these global cortical analyses. Across simulated clinical trials, type I error was higher in trials where both Aβ radiotracers were used versus trials where only one Aβ radiotracer was used. Power was lower in trials where 18F-florbetapir was primarily used versus trials where 11C-PiB was primarily used. Conclusion: Gantenerumab treatment induces longitudinal changes in Aβ PET, and the absolute rates of these longitudinal changes differ significantly between Aβ radiotracers. These differences were not seen in the placebo arm, suggesting that Aβ-clearing treatments may pose unique challenges when attempting to compare longitudinal results across different Aβ radiotracers. Our results suggest converting Aβ PET SUVR measurements to Centiloids (both globally and regionally) can harmonize these differences without losing sensitivity to drug effects. Nonetheless, until consensus is achieved on how to harmonize drug effects across radiotracers, and since using multiple radiotracers in the same trial may increase type I error, multisite studies should consider potential variability due to different radiotracers when interpreting Aβ PET biomarker data and, if feasible, use a single radiotracer for the best results.
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    Measuring Subjective Cognitive Decline in Older Adults: Harmonization Between the Cognitive Change Index and the Measurement of Everyday Cognition Instruments
    (IOS Press, 2022) Wells, Lindsey F.; Risacher, Shannon L.; McDonald, Brenna C.; Farlow, Martin R.; Brosch, Jared; Gao, Sujuan; Apostolova, Liana G.; Saykin, Andrew J.; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of Medicine
    Background: Self and informant (proxy or study partner) reports of everyday cognitive functioning have been shown to be associated with incipient neurodegenerative disease. The 20-item Cognitive Change Index (CCI) and the 39-item Measurement of Everyday Cognition (ECog) were each developed to characterize early subjective changes in cognitive function. Objective: We examined the relationship between CCI and ECog self and informant-based evaluations to determine content overlap and provide a co-calibration for converting between these widely used instruments. Methods: 950 participants (57.1% female, mean age = 71.2 years) from ADNI and the Indiana ADRC with self-based evaluations and 279 participants (60.9% female, mean age = 71.8 years) with informant-based evaluations (Indiana ADRC) were included. Analyzed variables for the CCI and ECog included domain mean scores, memory domain total scores, and total scores for all items. Spearman correlations, regression analyses, and frequency distributions were used to assess the relationship between CCI and ECog. Sex, age, years of education, race/ethnicity, APOE ε4 carrier status, and baseline diagnosis were also analyzed as potentially relevant covariates. Results: CCI and ECog total scores were highly correlated for the self (r = 0.795, p < 0.001) and informant-based (r = 0.840, p < 0.001) versions, as expected. Frequency distributions of self and informant total scores were generated and plotted separately. Quadratic regressions for self (r2 = 0.626) and informant (r2 = 0.741) scores were used to create a translation table between the CCI and ECog total scores. Conclusion: Self and informant total scores can be harmonized and translated between the CCI and ECog to facilitate cross-study and longitudinal assessment of perceived cognitive change, an important patient-reported outcome.
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    Resting state network profiles of Alzheimer disease and frontotemporal dementia: A preliminary examination
    (Cambridge University Press, 2018-05-10) Contreras, Joey Annette; Risacher, Shannon L.; Dzemidzic, Mario; West, John D.; McDonald, Brenna C.; Farlow, Martin R.; Matthews, Brandy R.; Apostolova, Liana G.; Brosch, Jared; Ghetti, Bernard; GoÑi, Joaquin; Medicine, School of Medicine
    OBJECTIVES/SPECIFIC AIMS: Recent evidence from resting-state fMRI studies have shown that brain network connectivity is altered in patients with neurodegenerative disorders. However, few studies have examined the complete connectivity patterns of these well-reported RSNs using a whole brain approach and how they compare between dementias. Here, we used advanced connectomic approaches to examine the connectivity of RSNs in Alzheimer disease (AD), Frontotemporal dementia (FTD), and age-matched control participants. METHODS/STUDY POPULATION: In total, 44 participants [27 controls (66.4±7.6 years), 13 AD (68.5.63±13.9 years), 4 FTD (59.575±12.2 years)] from an ongoing study at Indiana University School of Medicine were used. Resting-state fMRI data was processed using an in-house pipeline modeled after Power et al. (2014). Images were parcellated into 278 regions of interest (ROI) based on Shen et al. (2013). Connectivity between each ROI pair was described by Pearson correlation coefficient. Brain regions were grouped into 7 canonical RSNs as described by Yeo et al. (2015). Pearson correlation values were then averaged across pairs of ROIs in each network and averaged across individuals in each group. These values were used to determine relative expression of FC in each RSN (intranetwork) and create RSN profiles for each group. RESULTS/ANTICIPATED RESULTS: Our findings support previous literature which shows that limbic networks are disrupted in FTLD participants compared with AD and age-matched controls. In addition, interactions between different RSNs was also examined and a significant difference between controls and AD subjects was found between FP and DMN RSNs. Similarly, previous literature has reported a disruption between executive (frontoparietal) network and default mode network in AD compared with controls. DISCUSSION/SIGNIFICANCE OF IMPACT: Our approach allows us to create profiles that could help compare intranetwork FC in different neurodegenerative diseases. Future work with expanded samples will help us to draw more substantial conclusions regarding differences, if any, in the connectivity patterns between RSNs in various neurodegenerative diseases.