Browsing by Author "McDonald, Brenna C."
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Item Alpha-synuclein (SNCA) polymorphisms exert protective effects on memory after mild traumatic brain injury(Elsevier, 2016-09-06) Shee, Kevin; Lucas, Alexandra; Flashman, Laura A.; Nho, Kwangsik; Tsongalis, Gregory J.; McDonald, Brenna C.; Saykin, Andrew J.; McAllister, Thomas W.; Rhodes, C. Harker; Psychiatry, School of MedicineProblems with attention and short-term learning and memory are commonly reported after mild traumatic brain injury (mTBI). Due to the known relationships between α-synuclein (SNCA), dopaminergic transmission, and neurologic deficits, we hypothesized that SNCA polymorphisms might be associated with cognitive outcome after mTBI. A cohort of 91 mTBI patients one month after injury and 86 healthy controls completed a series of cognitive tests assessing baseline intellectual function, attentional function, and memory, and was genotyped at 13 common single nucleotide polymorphisms (SNPs) in the SNCA gene. Significant differences in two memory measures (p = 0.001 and 0.002), but not baseline intellectual function or attentional function tasks, were found between the mTBI group and controls. A highly significant protective association between memory performance and SNCA promoter SNP rs1372525 was observed in the mTBI patients (p = 0.006 and 0.029 for the long and short delay conditions of the California Verbal Learning Tests, respectively), where the presence of at least one copy of the A (minor) allele was protective after mTBI. These results may help elucidate the pathophysiology of cognitive alterations after mTBI, and thus warrant further investigation.Item Alterations in brain structure and function in breast cancer survivors: effect of post-chemotherapy interval and relation to oxidative DNA damage(Springer, 2013) Conroy, Susan K.; McDonald, Brenna C.; Smith, Dori J.; Moser, Lyndsi R.; West, John D.; Kamendulis, Lisa M.; Klaunig, James E.; Champion, Victoria L.; Unverzagt, Frederick W.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineNeuroimaging studies have begun to uncover the neural substrates of cancer and treatment-related cognitive dysfunction, but the time course of these changes in the years following chemotherapy is unclear. This study analyzed multimodality 3T MRI scans to examine the structural and functional effects of chemotherapy and post-chemotherapy interval (PCI) in a cohort of breast cancer survivors (BCS; n = 24; PCI mean 6, range 3-10 y) relative to age- and education-matched healthy controls (HC; n = 23). Assessments included voxel-based morphometry for gray matter density (GMD) and fMRI for activation profile during a 3-back working memory task. The relationships between brain regions associated with PCI and neuropsychological performance, self-reported cognition, and oxidative and direct DNA damage as measured in peripheral lymphocytes were assessed in secondary analyses. PCI was positively associated with GMD and activation on fMRI in the right anterior frontal region (Brodmann Areas 9 and 10) independent of participant age. GMD in this region was also positively correlated with global neuropsychological function. Memory dysfunction, cognitive complaints, and oxidative DNA damages were increased in BCS compared with HC. Imaging results indicated lower fMRI activation in several regions in the BCS group. BCS also had lower GMD than HC in several regions, and in these regions, GMD was inversely related to oxidative DNA damage and learning and memory neuropsychological domain scores. This is the first study to show structural and functional effects of PCI and to relate oxidative DNA damage to brain alterations in BCS. The relationship between neuroimaging and cognitive function indicates the potential clinical relevance of these findings. The relationship with oxidative DNA damage provides a mechanistic clue warranting further investigation.Item Alterations in brain structure related to breast cancer and its treatment: Chemotherapy and other considerations(Springer US, 2013-12) McDonald, Brenna C.; Saykin, Andrew J.; Department of Radiology and Imaging Sciences, School of MedicineCognitive effects of cancer and its treatment have been a topic of increasing investigation over the past ∼30 years. Recent studies have focused on better understanding the neural correlates of these effects, with an emphasis on post-chemotherapy effects in breast cancer patients. Structural MRI studies have utilized both automated and manual approaches to quantify gray and white matter characteristics (e.g., regional volume and density) in breast cancer patients treated with chemotherapy relative to patients who did not receive chemotherapy and/or healthy controls. While most work to date has been retrospective, a small number of baseline (pre-systemic therapy) and prospective longitudinal studies have been conducted. Data have consistently shown lower gray and white matter volume and density in patients treated with chemotherapy, particularly in frontal and temporal brain regions. Host factors and/or the cancer disease process and other therapies (e.g., antiestrogen treatment) also seem likely to contribute to the observed differences, though the relative contributions of these effects have not yet been investigated in detail. These structural abnormalities have been shown to relate to subjective and objective cognitive functioning, as well as to biological factors that may help to elucidate the underlying mechanism(s). This review examines the currently available published observations and discusses the major themes and promising directions for future studies.Item Altered Cerebral Blood Flow One Month after Systemic Chemotherapy for Breast Cancer: A Prospective Study Using Pulsed Arterial Spin Labeling MRI Perfusion(Public Library of Science, 2014-05-09) Nudelman, Kelly N. H.; Wang, Yang; McDonald, Brenna C.; Conroy, Susan K.; Smith, Dori J.; West, John D.; O’Neill, Darren P.; Schneider, Bryan P.; Saykin, Andrew J.; Medical and Molecular Genetics, School of MedicineCerebral structural and functional alterations have been reported after chemotherapy for non-CNS cancers, yet the causative mechanism behind these changes remains unclear. This study employed a novel, non-invasive, MRI-based neuroimaging measure to provide the first direct longitudinal measurement of resting cerebral perfusion in breast cancer patients, which was tested for association with changes in cognitive function and gray matter density. Perfusion was measured using pulsed arterial spin labeling MRI in women with breast cancer treated with (N = 27) or without (N = 26) chemotherapy and matched healthy controls (N = 26) after surgery before other treatments (baseline), and one month after chemotherapy completion or yoked intervals. Voxel-based analysis was employed to assess perfusion in gray matter; changes were examined in relation to overall neuropsychological test performance and frontal gray matter density changes measured by structural MRI. Baseline perfusion was not significantly different across groups. Unlike control groups, chemotherapy-treated patients demonstrated significantly increased perfusion post-treatment relative to baseline, which was statistically significant relative to controls in the right precentral gyrus. This perfusion increase was negatively correlated with baseline overall neuropsychological performance, but was not associated with frontal gray matter density reduction. However, decreased frontal gray matter density was associated with decreased perfusion in bilateral frontal and parietal lobes in the chemotherapy-treated group. These findings indicate that chemotherapy is associated with alterations in cerebral perfusion which are both related to and independent of gray matter changes. This pattern of results suggests the involvement of multiple mechanisms of chemotherapy-induced cognitive dysfunction. Additionally, lower baseline cognitive function may be a risk factor for treatment-associated perfusion dysregulation. Future research is needed to clarify these mechanisms, identify individual differences in susceptibility to treatment-associated changes, and further examine perfusion change over time in survivors.Item Altered Default Mode Network Connectivity in Older Adults with Cognitive Complaints and Amnestic Mild Cognitive Impairment(Sage, 2013) Wang, Yang; Risacher, Shannon L.; West, John D.; McDonald, Brenna C.; MaGee, Tamiko R.; Farlow, Martin R.; Gao, Sujuan; O’Neill, Darren P.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineDefault mode network (DMN) disruption has been reported in Alzheimer's disease (AD), yet the specific pattern of altered connectivity over the course of prodromal AD remains to be characterized. The aim of this study was to assess DMN connectivity in older adults with informant-verified cognitive complaints (CC) but normal neuropsychological performance compared to individuals with mild cognitive impairment (MCI) and healthy controls (HC). DMN maps were derived from resting-state fMRI using independent component analysis. Group comparisons of DMN connectivity were performed between older adults with MCI (n = 18), CC (n = 23), and HC (n = 16). Both CC and MCI showed decreased DMN connectivity in the right hippocampus compared to HC, with the CC group showing greater connectivity than MCI. These differences survived atrophy correction and correlated with cognitive performance. DMN connectivity appears sensitive to early prodromal neurodegenerative changes associated with AD, notably including pre-MCI individuals with cognitive complaints.Item Alzheimer disease–related biomarkers and cancer-related cognitive decline: the Thinking and Living with Cancer study(Oxford University Press, 2024) Mandelblatt, Jeanne; Dage, Jeffrey L.; Zhou, Xingtao; Small, Brent J.; Ahles, Tim A.; Ahn, Jaeil; Artese, Ashley; Bethea, Traci N.; Breen, Elizabeth C.; Carroll, Judith E.; Cohen, Harvey J.; Extermann, Martine; Graham, Deena; Claudine, Isaacs; Jim, Heather S. L.; McDonald, Brenna C.; Nakamura, Zev M.; Patel, Sunita K.; Rebeck, G. William; Rentscher, Kelly E.; Root, James C.; Russ, Kristen A.; Tometich, Danielle B.; Turner, R. Scott; Van Dyk, Kathleen; Zhai, Wanting; Huang, Li-Wen; Saykin, Andrew J.; Neurology, School of MedicinePurpose: We evaluated whether plasma Alzheimer disease (AD)-related biomarkers were associated with cancer-related cognitive decline among older breast cancer survivors. Methods: We included survivors aged 60-90 years with primary stage 0-III breast cancers (n = 236) and frequency-matched noncancer control paricipant (n = 154) who passed a cognitive screen and had banked plasma specimens. Participants were assessed at baseline (presystemic therapy) and annually for up to 60 months. Cognition was measured using tests of attention, processing speed, and executive function and learning and memory; perceived cognition was measured by the Functional Assessment of Cancer Therapy-Cognitive Function v3 Perceived Cognitive Impairments. Baseline plasma neurofilament light, glial fibrillary acidic protein, β-amyloid 42 and 40 and phosphorylated tau 181 were assayed using single molecule arrays. Mixed models tested associations between cognition and baseline AD biomarkers, time, group (survivor vs control participant), and their 2- and 3-way interactions, controlling for age, race, Wide Range 4 Achievement Test Word Reading score, comorbidity, and body mass index; 2-sided P values of .05 were considered statistically significant. Results: There were no group differences in baseline AD-related biomarkers except survivors had higher baseline neurofilament light levels than control participants (P = .013). Survivors had lower adjusted longitudinal attention, processing speed, and executive function than control participants starting from baseline and continuing over time (P ≤ .002). However, baseline AD-related biomarker levels were not independently associated with adjusted cognition over time, except control participants had lower attention, processing speed, and executive function scores with higher glial fibrillary acidic protein levels (P = .008). Conclusion: The results do not support a relationship between baseline AD-related biomarkers and cancer-related cognitive decline. Further investigation is warranted to confirm the findings, test effects of longitudinal changes in AD-related biomarkers, and examine other mechanisms and factors affecting cognition presystemic therapy.Item Amyloid and Tau Pathology are Associated with Cerebral Blood Flow in a Mixed Sample of Nondemented Older Adults with and without Vascular Risk Factors for Alzheimer’s Disease(Elsevier, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Vosmeier, Aaron; Deardorff, Rachael; Chumin, Evgeny J.; Dzemidzic, Mario; Wu, Yu-Chien; Gao, Sujuan; McDonald, Brenna C.; Yoder, Karmen K.; Unverzagt, Frederick W.; Wang, Sophia; Farlow, Martin R.; Brosch, Jared R.; Clark, David G.; Apostolova, Liana G.; Sims, Justin; Wang, Danny J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineIdentification of biomarkers for the early stages of Alzheimer's disease (AD) is an imperative step in developing effective treatments. Cerebral blood flow (CBF) is a potential early biomarker for AD; generally, older adults with AD have decreased CBF compared to normally aging peers. CBF deviates as the disease process and symptoms progress. However, further characterization of the relationships between CBF and AD risk factors and pathologies is still needed. We assessed the relationships between CBF quantified by arterial spin-labeled magnetic resonance imaging, hypertension, APOEε4, and tau and amyloid positron emission tomography in 77 older adults: cognitively normal, subjective cognitive decline, and mild cognitive impairment. Tau and amyloid aggregation were related to altered CBF, and some of these relationships were dependent on hypertension or APOEε4 status. Our findings suggest a complex relationship between risk factors, AD pathologies, and CBF that warrants future studies of CBF as a potential early biomarker for AD.Item Analysis of the Inverse Association between Cancer and Alzheimer’s Disease: Results from the Alzheimer’s Disease Neuroimaging Initiative Cohort(Office of the Vice Chancellor for Research, 2014-04-11) Nudelman, Kelly N. H.; Risacher, Shannon L.; West, John D.; Nho, Kwangsik; Ramanan, Vijay K.; McDonald, Brenna C.; Shen, Li; Foroud, Tatiana M.; Schneider, Bryan P.; Saykin, Andrew J.Although a number of studies support a reciprocal inverse association between diagnoses of cancer and Alzheimer’s disease (AD), to date there has not been any systemic investigation of the neurobiological impact of or genetic risk factors underlying this effect. To facilitate this goal, this study aimed to replicate the inverse association of cancer and AD using data from the NIA Alzheimer’s Disease Neuroimaging Initiative, which includes age-matched cases and controls with information on cancer history, AD progression, neuroimaging, and genomic data. Subjects included individuals with AD (n=234), mild cognitive impairment (MCI, n=542), and healthy controls (HC, n=293). After controlling for sex, education, race/ethnicity, smoking, and apolipoprotein E (APOE) e2/3/4 allele groups, cancer history was protective against baseline AD diagnosis (p=0.042), and was associated with later age of AD onset (p=0.001). Cancer history appears to result in a cumulative protective effect; individuals with more than one cancer had a later age of AD onset compared to those with only one cancer (p=0.001). Finally, a protective effect of AD was also observed in individuals who developed incident cancer after enrolling (post-baseline visit); 20 individuals with MCI and 9 HC developed cancer, while no AD patients had subsequent cancer diagnoses (p=0.013). This supports previous research on the inverse association of cancer and AD, and importantly provides novel evidence that this effect appears to be independent of APOE, the major known genetic risk factor for AD. Future analyses will investigate the neurobiological and genetic basis of this effect.Item Associating Persistent Self-Reported Cognitive Decline with Neurocognitive Decline in Older Breast Cancer Survivors Using Machine Learning: The Thinking and Living with Cancer Study(Elsevier, 2022) Van Dyk, Kathleen; Ahn, Jaeil; Zhou, Xingtao; Zhai, Wanting; Ahles, Tim A.; Bethea, Traci N.; Carroll, Judith E.; Cohen, Harvey Jay; Dilawari, Asma A.; Graham, Deena; Jacobsen, Paul B.; Jim, Heather; McDonald, Brenna C.; Nakamura, Zev M.; Patel, Sunita K.; Rentscher, Kelly E.; Saykin, Andrew J.; Small, Brent J.; Mandelblatt, Jeanne S.; Root, James C.; Radiology and Imaging Sciences, School of MedicineIntroduction: Many cancer survivors report cognitive problems following diagnosis and treatment. However, the clinical significance of patient-reported cognitive symptoms early in survivorship can be unclear. We used a machine learning approach to determine the association of persistent self-reported cognitive symptoms two years after diagnosis and neurocognitive test performance in a prospective cohort of older breast cancer survivors. Materials and methods: We enrolled breast cancer survivors with non-metastatic disease (n = 435) and age- and education-matched non-cancer controls (n = 441) between August 2010 and December 2017 and followed until January 2020; we excluded women with neurological disease and all women passed a cognitive screen at enrollment. Women completed the FACT-Cog Perceived Cognitive Impairment (PCI) scale and neurocognitive tests of attention, processing speed, executive function, learning, memory and visuospatial ability, and timed activities of daily living assessments at enrollment (pre-systemic treatment) and annually to 24 months, for a total of 59 individual neurocognitive measures. We defined persistent self-reported cognitive decline as clinically meaningful decline (3.7+ points) on the PCI scale from enrollment to twelve months with persistence to 24 months. Analysis used four machine learning models based on data for change scores (baseline to twelve months) on the 59 neurocognitive measures and measures of depression, anxiety, and fatigue to determine a set of variables that distinguished the 24-month persistent cognitive decline group from non-cancer controls or from survivors without decline. Results: The sample of survivors and controls ranged in age from were ages 60-89. Thirty-three percent of survivors had self-reported cognitive decline at twelve months and two-thirds continued to have persistent decline to 24 months (n = 60). Least Absolute Shrinkage and Selection Operator (LASSO) models distinguished survivors with persistent self-reported declines from controls (AUC = 0.736) and survivors without decline (n = 147; AUC = 0.744). The variables that separated groups were predominantly neurocognitive test performance change scores, including declines in list learning, verbal fluency, and attention measures. Discussion: Machine learning may be useful to further our understanding of cancer-related cognitive decline. Our results suggest that persistent self-reported cognitive problems among older women with breast cancer are associated with a constellation of mild neurocognitive changes warranting clinical attention.Item Associating persistent self-reported cognitive decline with neurocognitive decline in older breast cancer survivors using machine learning: The Thinking and Living with Cancer study(Elsevier, 2022-11) Van Dyk, Kathleen; Ahn, Jaeil; Zhou, Xingtao; Zhai, Wanting; Ahles, Tim A.; Bethea, Traci N.; Carroll, Judith E.; Cohen, Harvey Jay; Dilawari, Asma A.; Graham, Deena; Jacobsen, Paul B.; Jim, Heather; McDonald, Brenna C.; Nakamura, Zev M.; Patel, Sunita K.; Rentscher, Kelly E.; Saykin, Andrew J.; Small, Brent J.; Mandelblatt, Jeanne S.; Root, James C.; Radiology and Imaging Sciences, School of MedicineIntroduction: Many cancer survivors report cognitive problems following diagnosis and treatment. However, the clinical significance of patient-reported cognitive symptoms early in survivorship can be unclear. We used a machine learning approach to determine the association of persistent self-reported cognitive symptoms two years after diagnosis and neurocognitive test performance in a prospective cohort of older breast cancer survivors. Materials and Methods: We enrolled breast cancer survivors with non-metastatic disease (n=435) and age- and education-matched non-cancer controls (n=441) between August 2010 and December 2017 and followed until January 2020; we excluded women with neurological disease and all women passed a cognitive screen at enrollment. Women completed the FACT-Cog Perceived Cognitive Impairment (PCI) scale and neurocognitive tests of attention, processing speed, executive function, learning, memory and visuospatial ability, and timed activities of daily living assessments at enrollment (pre-systemic treatment) and annually to 24 months, for a total of 59 individual neurocognitive measures. We defined persistent self-reported cognitive decline as clinically meaningful decline (3.7+ points) on the PCI scale from enrollment to twelve months with persistence to 24 months. Analysis used four machine learning models based on data for change scores (baseline to twelve months) on the 59 neurocognitive measures and measures of depression, anxiety, and fatigue to determine a set of variables that distinguished the 24-month persistent cognitive decline group from non-cancer controls or from survivors without decline. Results: The sample of survivors and controls ranged in age from were ages 60–89. Thirty-three percent of survivors had self-reported cognitive decline at twelve months and two-thirds continued to have persistent decline to 24 months (n=60). Least Absolute Shrinkage and Selection Operator (LASSO) models distinguished survivors with persistent self-reported declines from controls (AUC=0.736) and survivors without decline (n=147; AUC=0.744). The variables that separated groups were predominantly neurocognitive test performance change scores, including declines in list learning, verbal fluency, and attention measures. Discussion: Machine learning may be useful to further our understanding of cancer-related cognitive decline. Our results suggest that persistent self-reported cognitive problems among older women with breast cancer are associated with a constellation of mild neurocognitive changes warranting clinical attention.