Publications -- Melissa E. Petersen
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/31203
This collection is limited to articles published under the terms of a creative commons license or other open access publishing agreement since 2016. It is not intended as a complete list of the author's works.
Browse
Browsing Publications -- Melissa E. Petersen by Subject "Alzheimer Disease"
Now showing 1 - 7 of 7
- Results Per Page
- Sort Options
Item A Precision Medicine Approach to Treating Alzheimer's Disease Using Rosiglitazone Therapy: A Biomarker Analysis of the REFLECT Trials(IOS Press, 2021-05-18) O'Bryant, Sid E.; Zhang, Fan; Petersen, Melissa E.; Johnson, Leigh A.; Hall, James R.; Rissman, Robert A.Background: The REFLECT trials were conducted to examine the treatment of mild-to-moderate Alzheimer's disease utilizing a peroxisome proliferator-activated receptor gamma agonist. Objective: To generate a predictive biomarker indicative of positive treatment response using samples from the previously conducted REFLECT trials. Methods: Data were analyzed on 360 participants spanning multiple negative REFLECT trials, which included treatment with rosiglitazone and rosiglitazone XR. Support vector machine analyses were conducted to generate a predictive biomarker profile. Results: A pre-defined 6-protein predictive biomarker (IL6, IL10, CRP, TNFɑ, FABP-3, and PPY) correctly classified treatment response with 100% accuracy across study arms for REFLECT Phase II trial (AVA100193) and multiple Phase III trials (AVA105640, AV102672, and AVA102670). When the data was combined across all rosiglitazone trial arms, a global RSG-predictive biomarker with the same 6-protein predictive biomarker was able to accurately classify 98%of treatment responders. Conclusion: A predictive biomarker comprising of metabolic and inflammatory markers was highly accurate in identifying those patients most likely to experience positive treatment response across the REFLECT trials. This study provides additional proof-of-concept that a predictive biomarker can be utilized to help with screening and predicting treatment response, which holds tremendous benefit for clinical trials.Item Accelerating Hyperparameter Tuning in Machine Learning for Alzheimer's Disease With High Performance Computing(Frontiers Media S.A., 2021-12-08) Zhang, Fan; Petersen, Melissa E.; Johnson, Leigh A.; Hall, James R.; O'Bryant, Sid E.Driven by massive datasets that comprise biomarkers from both blood and magnetic resonance imaging (MRI), the need for advanced learning algorithms and accelerator architectures, such as GPUs and FPGAs has increased. Machine learning (ML) methods have delivered remarkable prediction for the early diagnosis of Alzheimer's disease (AD). Although ML has improved accuracy of AD prediction, the requirement for the complexity of algorithms in ML increases, for example, hyperparameters tuning, which in turn, increases its computational complexity. Thus, accelerating high performance ML for AD is an important research challenge facing these fields. This work reports a multicore high performance support vector machine (SVM) hyperparameter tuning workflow with 100 times repeated 5-fold cross-validation for speeding up ML for AD. For demonstration and evaluation purposes, the high performance hyperparameter tuning model was applied to public MRI data for AD and included demographic factors such as age, sex and education. Results showed that computational efficiency increased by 96%, which helped to shed light on future diagnostic AD biomarker applications. The high performance hyperparameter tuning model can also be applied to other ML algorithms such as random forest, logistic regression, xgboost, etc.Item Acute Regression in Down Syndrome(MDPI, 2021-08-23) Handen, Benjamin; Clare, Isabel; Laymon, Charles; Petersen, Melissa E.; Zaman, Shahid; O'Bryant, Sid E.; Minhas, Davneet; Tudorascu, Dana; Brown, Stephanie; Christian, BradleyAcute regression has been reported in some individuals with Down syndrome (DS), typically occurring between the teenage years and mid to late 20s. Characterized by sudden, and often unexplained, reductions in language skills, functional living skills and reduced psychomotor activity, some individuals have been incorrectly diagnosed with Alzheimer's disease (AD).|This paper compares five individuals with DS who previously experienced acute regression with a matched group of 15 unaffected individuals with DS using a set of AD biomarkers.|While the sample was too small to conduct statistical analyses, findings suggest there are possible meaningful differences between the groups on proteomics biomarkers (e.g., NfL, total tau). Hippocampal, caudate and putamen volumes were slightly larger in the regression group, the opposite of what was hypothesized. A slightly lower amyloid load was found on the PET scans for the regression group, but no differences were noted on tau PET.|Some proteomics biomarker findings suggest that individuals with DS who experience acute regression may be at increased risk for AD at an earlier age in comparison to unaffected adults with DS. However, due to the age of the group (mean 38 years), it may be too early to observe meaningful group differences on image-based biomarkers.Item Characterization of the Meal-Stimulated Incretin Response and Relationship With Structural Brain Outcomes in Aging and Alzheimer's Disease(Frontiers Media S.A., 2020-11-30) Morris, Jill K.; John, Casey S.; Green, Zachary D.; Wilkins, Heather M.; Wang, Xiaowan; Kamat, Ashwini; Swerdlow, Russell S.; Vidoni, Eric D.; Petersen, Melissa E.; O'Bryant, Sid E.; Honea, Robyn A.; Burns, Jeffrey M.Background: Individuals with Alzheimer's Disease (AD) are often characterized by systemic markers of insulin resistance; however, the broader effects of AD on other relevant metabolic hormones, such as incretins that affect insulin secretion and food intake, remains less clear. Methods: Here, we leveraged a physiologically relevant meal tolerance test to assess diagnostic differences in these metabolic responses in cognitively healthy older adults (CH; n = 32) and AD (n = 23) participants. All individuals also underwent a comprehensive clinical examination, cognitive evaluation, and structural magnetic resonance imaging. Results: The meal-stimulated response of glucose, insulin, and peptide tyrosine tyrosine (PYY) was significantly greater in individuals with AD as compared to CH. Voxel-based morphometry revealed negative relationships between brain volume and the meal-stimulated response of insulin, C-Peptide, and glucose-dependent insulinotropic polypeptide (GIP) in primarily parietal brain regions. Conclusion: Our findings are consistent with prior work that shows differences in metabolic regulation in AD and relationships with cognition and brain structure.Item Neurodegeneration from the AT(N) framework is different among Mexican Americans compared to non-Hispanic Whites: A Health & Aging Brain among Latino Elders (HABLE) Study(Wiley Periodicals, LLC, 2022-02-09) O'Bryant, Sid E.; Zhang, Fan; Petersen, Melissa E.; Hall, James R.; Johnson, Leigh A.; Yaffe, Kristine; Braskie, Meredith N.; Rissman, Robert A.; Vig, Rocky; Toga, Arthur W.Introduction: We sought to examine a magnetic resonance imaging (MRI)-based marker of neurodegeneration from the AT(N) (amyloid/tau/neurodegeneration) framework among a multi-ethnic, community-dwelling cohort. Methods: Community-dwelling Mexican Americans and non-Hispanic White adults and elders were recruited. All participants underwent comprehensive assessments including an interview, functional exam, clinical labs, informant interview, neuropsychological testing and 3T MRI of the brain. A neurodegeneration MRI meta-region of interest (ROI) biomarker for the AT(N) framework was calculated. Results: Data were examined from n = 1305 participants. Mexican Americans experienced N at significantly younger ages. The N biomarker was significantly associated with cognitive outcomes. N was significantly impacted by cardiovascular factors (e.g., total cholesterol, low-density lipoprotein) among non-Hispanic Whites whereas diabetes (glucose, HbA1c, duration of diabetes) and sociocultural (household income, acculturation) factors were strongly associated with N among Mexican Americans. Discussion: The prevalence, progression, timing, and sequence of the AT(N) biomarkers must be examined across diverse populations.Item Proteomic profiles of prevalent mild cognitive impairment and Alzheimer's disease among adults with Down syndrome(Wiley Periodicals, Inc., 2020-04-17) Petersen, Melissa E.; Zhang, Fan; Krinsky-McHale, Sharon J.; Silverman, Wayne; Lee, Joseph H.; Pang, Deborah; Hall, James R.; Schupf, Nicole; O'Bryant, Sid E.Introduction: We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease (AD) in the general population would apply to adults with Down syndrome (DS). Methods: Plasma samples were obtained from 398 members of a community-based cohort of adults with DS. A total of n = 186 participants were determined to be non-demented and without mild cognitive impairment (MCI) at baseline and throughout follow-up; n = 50 had prevalent MCI; n = 42 had prevalent AD. Results: The proteomic profile yielded an area under the curve (AUC) of 0.92, sensitivity (SN) = 0.80, and specificity (SP) = 0.98 detecting prevalent MCI. For detecting prevalent AD, the proteomic profile yielded an AUC of 0.89, SN = 0.81, and SP = 0.97. The overall profile closely resembled our previously published profile of AD in the general population. Discussion: These data provide evidence of the applicability of our blood-based algorithm for detecting MCI/AD among adults with DS.Item The Health & Aging Brain among Latino Elders (HABLE) study methods and participant characteristics(Wiley Periodicals, LLC, 2021-06-21) O'Bryant, Sid E.; Johnson, Leigh A.; Barber, Robert C.; Braskie, Meredith N.; Christian, Bradley; Hall, James R.; Hazra, Nalini; King, Kevin; Kothapalli, Deydeep; Large, Stephanie; Mason, David; Matsiyevskiy, Elizabeth; McColl, Roderick; Nandy, Rajesh; Palmer, Raymond; Petersen, Melissa E.; Philips, Nicole; Rissman, Robert A.; Shi, Yonggang; Toga, Arthur W.; Vintimilla, Raul; Vig, Rocky; Zhang, Fan; Yaffe, KristineIntroduction: Mexican Americans remain severely underrepresented in Alzheimer's disease (AD) research. The Health & Aging Brain among Latino Elders (HABLE) study was created to fill important gaps in the existing literature. Methods: Community-dwelling Mexican Americans and non-Hispanic White adults and elders (age 50 and above) were recruited. All participants underwent comprehensive assessments including an interview, functional exam, clinical labs, informant interview, neuropsychological testing, and 3T magnetic resonance imaging (MRI) of the brain. Amyloid and tau positron emission tomography (PET) scans were added at visit 2. Blood samples were stored in the Biorepository. Results: Data was examined from n = 1705 participants. Significant group differences were found in medical, demographic, and sociocultural factors. Cerebral amyloid and neurodegeneration imaging markers were significantly different between Mexican Americans and non-Hispanic Whites. Discussion: The current data provide strong support for continued investigations that examine the risk factors for and biomarkers of AD among diverse populations.