Publications -- James R. Hall
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12503/32389
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.
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Browsing Publications -- James R. Hall by Author "Edwards, Melissa"
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Item A proteomic signature for dementia with Lewy bodies(Elsevier Inc., 2019-03-15) O'Bryant, Sid E.; Ferman, Tanis J.; Zhang, Fan; Hall, James R.; Pedraza, Otto; Wszolek, Zbigniew K.; Como, Tori; Julovich, David A.; Mattevada, Sravan; Johnson, Leigh A.; Edwards, Melissa; Graff-Radford, Neill R.Introduction: We sought to determine if a proteomic profile approach developed to detect Alzheimer's disease would distinguish patients with Lewy body disease from normal controls, and if it would distinguish dementia with Lewy bodies (DLB) from Parkinson's disease (PD). Methods: Stored plasma samples were obtained from 145 patients (DLB n = 57, PD without dementia n = 32, normal controls n = 56) enrolled from patients seen in the Behavioral Neurology or Movement Disorders clinics at the Mayo Clinic, Florida. Proteomic assays were conducted and analyzed as per our previously published protocols. Results: In the first step, the proteomic profile distinguished the DLB-PD group from controls with a diagnostic accuracy of 0.97, sensitivity of 0.91, and specificity of 0.86. In the second step, the proteomic profile distinguished the DLB from PD groups with a diagnostic accuracy of 0.92, sensitivity of 0.94, and specificity of 0.88. Discussion: These data provide evidence of the potential utility of a multitiered blood-based proteomic screening method for detecting DLB and distinguishing DLB from PD.Item Depression, inflammation, and memory loss among Mexican Americans: analysis of the HABLE cohort(Cambridge University Press, 2017-06-20) Johnson, Leigh A.; Edwards, Melissa; Gamboa, Adriana; Hall, James R.; Robinson, Michelle; O'Bryant, Sid E.Background: This study explored the combined impact of depression and inflammation on memory functioning among Mexican-American adults and elders. Methods: Data were analyzed from 381 participants of the Health and Aging Brain study among Latino Elders (HABLE). Fasting serum samples were collected and assayed in duplicate using electrochemiluminesce on the SECTOR Imager 2400A from Meso Scale Discovery. Positive DepE (depression endophenotype) was codified as any score >1 on a five-point scale based on the GDS-30. Inflammation was determined by TNFɑ levels and categorized by tertiles (1st, 2nd, 3rd). WMS-III LMI and LMII as well as CERAD were utilized as measures of memory. ANOVAs examined group differences between positive DepE and inflammation tertiles with neuropsychological scale scores as outcome variables. Logistic regressions were used to examine level of inflammation and DepE positive status on the risk for MCI. Results: Positive DepE as well as higher inflammation were both independently found to be associated with lower memory scores. Among DepE positive, those who were high in inflammation (3rd tertile) were found to perform significantly worse on WMS-III LM I (F = 4.75, p = 0.003), WMS-III LM II (F = 8.18, p < 0.001), and CERAD List Learning (F = 17.37, p < 0.001) when compared to those low on inflammation (1st tertile). The combination of DepE positive and highest tertile of inflammation was associated with increased risk for MCI diagnosis (OR = 6.06; 95% CI = 3.9-11.2, p < 0.001). Conclusion: Presence of elevated inflammation and positive DepE scores increased risk for worse memory among Mexican-American older adults. Additionally, the combination of DepE and high inflammation was associated with increased risk for MCI diagnosis. This work suggests that depression and inflammation are independently associated with worse memory among Mexican-American adults and elders; however, the combination of both increases risk for poorer memory beyond either alone.Item Potential two-step proteomic signature for Parkinson's disease: Pilot analysis in the Harvard Biomarkers Study(Elsevier Inc., 2019-05-02) O'Bryant, Sid E.; Edwards, Melissa; Zhang, Fan; Johnson, Leigh A.; Hall, James R.; Kuras, Yuliya; Scherzer, Clemens R.Introduction: We sought to determine if our previously validated proteomic profile for detecting Alzheimer's disease would detect Parkinson's disease (PD) and distinguish PD from other neurodegenerative diseases. Methods: Plasma samples were assayed from 150 patients of the Harvard Biomarkers Study (PD, n = 50; other neurodegenerative diseases, n = 50; healthy controls, n = 50) using electrochemiluminescence and Simoa platforms. Results: The first step proteomic profile distinguished neurodegenerative diseases from controls with a diagnostic accuracy of 0.94. The second step profile distinguished PD cases from other neurodegenerative diseases with a diagnostic accuracy of 0.98. The proteomic profile differed in step 1 versus step 2, suggesting that a multistep proteomic profile algorithm to detecting and distinguishing between neurodegenerative diseases may be optimal. Discussion: These data provide evidence of the potential use of a multitiered blood-based proteomic screening method for detecting individuals with neurodegenerative disease and then distinguishing PD from other neurodegenerative diseases.