Leigh A. Johnson, Ph.D.
Permanent URI for this communityhttps://hdl.handle.net/20.500.12503/31190
Member, Institute for Healthy Aging
Assistant Professor, Institute for Translational Research
Assistant Professor, Pharmacology & Neuroscience
Email: Leigh.Johnson@unthsc.edu
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Browsing Leigh A. Johnson, Ph.D. by Subject "Alzheimer Disease"
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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 Circulating mitochondrial DNA: New indices of type 2 diabetes-related cognitive impairment in Mexican Americans(PLoS, 2019-03-12) Silzer, Talisa K.; Barber, Robert C.; Sun, Jie; Pathak, Gita A.; Johnson, Leigh A.; O'Bryant, Sid E.; Phillips, NicoleMitochondrial function has been implicated and studied in numerous complex age-related diseases. Understanding the potential role of mitochondria in disease pathophysiology is of importance due to the rise in prevalence of complex age-related diseases, such as type 2 diabetes (T2D) and Alzheimer's disease (AD). These two diseases specifically share common pathophysiological characteristics which potentially point to a common root cause or factors for disease exacerbation. Studying the shared phenomena in Mexican Americans is of particular importance due to the disproportionate prevalence of both T2D and AD in this population. Here, we assessed the potential role of mitochondria in T2D and cognitive impairment (CI) in a Mexican American cohort by analyzing blood-based indices of mitochondrial DNA copy number (mtDNACN) and cell-free mitochondrial DNA (CFmtDNA). These mitochondrial metrics were also analyzed for correlation with relevant neuropsychological variables and physiological data collected as indicators of disease and/or disease progression. We found mtDNACN to be significantly decreased in individuals with CI, while CFmtDNA was significantly elevated in T2D; further, CFmtDNA elevation was significantly exacerbated in individuals with both diseases. MtDNACN was found to negatively correlate with age and fatty acid binding protein concentration, while positively correlating with CFmtDNA as well as CERAD total recall score. Candidate gene SNP-set analysis was performed on genes previously implicated in maintenance and control of mitochondrial dynamics to determine if nuclear variants may account for variability in mtDNACN. The results point to a single significant locus, in the LRRK2/MUC19 region, encoding leucine rich repeat kinase 2 and mucin 19. This locus has been previously implicated in Parkinson's disease, among others; rs7302859 was the driver SNP. These combined findings further indicate that mitochondrial dysfunction (as assessed by proxy via mtDNACN) is intimately linked to both T2D and CI phenotypes as well as aging.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 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.