Browsing by Subject "Neuroimaging"
Now showing 1 - 10 of 76
Results Per Page
Sort Options
Item Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder(Wiley, 2019-05) Salminen, Lauren E.; Morey, Rajendra A.; Riedel, Brandalyn C.; Jahanshad, Neda; Dennis, Emily L.; Thompson, Paul M.; Radiology and Imaging Sciences, School of MedicinePosttraumatic stress disorder (PTSD) is a heterogeneous condition associated with a range of brain imaging abnormalities. Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here, we used a novel machine learning method – evolving partitions to improve classification (EPIC) – to identify shared and unique structural neuroimaging markers of ELS and PTSD in 97 combat-exposed military veterans. METHODS: We used EPIC with repeated cross-validation (CV) to determine how combinations of cortical thickness, surface area, and subcortical brain volumes could contribute to classification of PTSD (n = 40) versus controls (n = 57), and classification of ELS within the PTSD (ELS+ n = 16; ELS− n = 24) and control groups (ELS+ n = 16; ELS− n = 41). Additional inputs included intracranial volume, age, sex, adult trauma, and depression. RESULTS: On average, EPIC classified PTSD with 69% accuracy (SD = 5%), and ELS with 64% accuracy in the PTSD group (SD = 10%), and 62% accuracy in controls (SD = 6%). EPIC selected unique sets of individual features that classified each group with 75–85% accuracy in post hoc analyses; combinations of regions marginally improved classification from the individual atlas-defined brain regions. Across analyses, surface area in the right posterior cingulate was the only variable that was repeatedly selected as an important feature for classification of PTSD and ELS. CONCLUSIONS: EPIC revealed unique patterns of features that distinguished PTSD and ELS in this sample of combat-exposed military veterans, which may represent distinct biotypes of stress-related neuropathology.Item Alport's syndrome and intracranial aneurysm: mere coincidence or undiscovered causal relationship(BMJ, 2019-01-29) Bose, Subhasish; Pathireddy, Samata; Baradhi, Krishna M.; Aeddula, Narothama Reddy; Medicine, School of MedicineA 44-year-old Caucasian man with a history of deceased donor renal transplant for end-stage renal disease from Alport's syndrome (AS), presented with a spontaneous subarachnoid haemorrhage and hydrocephalus. Following an external ventricular drain for the hydrocephalus, a CT angiography revealed a dissection of the left vertebral artery extending into vertebro-basilar junction necessitating a bypass between left occipital artery to left posterior inferior cerebellar artery. He had a posterior fossa Craniectomy, C1 laminectomy and coiling off, of the left vertebral artery. Postprocedure course was prolonged but uneventful with complete recovery and normal renal function 18 months postpresentation. AS, a disease caused by abnormalities in the synthesis of type IV collagen, can cause aneurysms with severe and permanent neurological sequalae. We present a case of AS with intracranial arterial dissection with potential life-threatening consequences and discuss the genetic and molecular basis of AS along with review of the relevant literature.Item Altered Cerebral Blood Flow in Older Adults with Alzheimer’s Disease: A Systematic Review(Springer, 2023) Swinford, Cecily G.; Risacher, Shannon L.; Wu, Yu-Chien; Apostolova, Liana G.; Gao, Sujuan; Bice, Paula J.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineThe prevalence of Alzheimer’s disease is projected to reach 13 million in the U.S. by 2050. Although major efforts have been made to avoid this outcome, so far there are no treatments that can stop or reverse the progressive cognitive decline that defines Alzheimer’s disease. The utilization of preventative treatment before significant cognitive decline has occurred may ultimately be the solution, necessitating a reliable biomarker of preclinical/prodromal disease stages to determine which older adults are most at risk. Quantitative cerebral blood flow is a promising potential early biomarker for Alzheimer’s disease, but the spatiotemporal patterns of altered cerebral blood flow in Alzheimer’s disease are not fully understood. The current systematic review compiles the findings of 81 original studies that compared resting gray matter cerebral blood flow in older adults with mild cognitive impairment or Alzheimer’s disease and that of cognitively normal older adults and/or assessed the relationship between cerebral blood flow and objective cognitive function. Individuals with Alzheimer’s disease had relatively decreased cerebral blood flow in all brain regions investigated, especially the temporoparietal and posterior cingulate, while individuals with mild cognitive impairment had consistent results of decreased cerebral blood flow in the posterior cingulate but more mixed results in other regions, especially the frontal lobe. Most papers reported a positive correlation between regional cerebral blood flow and cognitive function. This review highlights the need for more studies assessing cerebral blood flow changes both spatially and temporally over the course of Alzheimer’s disease, as well as the importance of including potential confounding factors in these analyses.Item APOE effect on Alzheimer's disease biomarkers in older adults with significant memory concern(Elsevier, 2015-12) Risacher, Shannon L.; Kim, Sungeun; Nho, Kwangsik; Foroud, Tatiana; Shen, Li; Peterson, Ronald C.; Jack Jr, Clifford R.; Beckett, Laurel A.; Aisen, Paul S.; Koeppe, Robert A.; Jagust, William J.; Shaw, Leslie M.; Trojanowski, John Q.; Department of Radiology and Imaging Sciences, IU School of MedicineINTRODUCTION: This study assessed apolipoprotein E (APOE) ε4 carrier status effects on Alzheimer's disease imaging and cerebrospinal fluid (CSF) biomarkers in cognitively normal older adults with significant memory concerns (SMC). METHODS: Cognitively normal, SMC, and early mild cognitive impairment participants from Alzheimer's Disease Neuroimaging Initiative were divided by APOE ε4 carrier status. Diagnostic and APOE effects were evaluated with emphasis on SMC. Additional analyses in SMC evaluated the effect of the interaction between APOE and [(18)F]Florbetapir amyloid positivity on CSF biomarkers. RESULTS: SMC ε4+ showed greater amyloid deposition than SMC ε4-, but no hypometabolism or medial temporal lobe (MTL) atrophy. SMC ε4+ showed lower amyloid beta 1-42 and higher tau/p-tau than ε4-, which was most abnormal in APOE ε4+ and cerebral amyloid positive SMC. DISCUSSION: SMC APOE ε4+ show abnormal changes in amyloid and tau biomarkers, but no hypometabolism or MTL neurodegeneration, reflecting the at-risk nature of the SMC group and the importance of APOE in mediating this risk.Item Assessment of white matter loss using bond-selective photoacoustic imaging in a rat model of contusive spinal cord injury(Mary Ann Liebert, 2014-12-15) Wu, Wei; Wang, Pu; Cheng, Ji-Xin; Xu, Xiao-Ming; Department of Neurological Surgery, IU School of MedicineWhite matter (WM) loss is a critical event after spinal cord injury (SCI). Conventionally, such loss has been measured with histological and histochemical approaches, although the procedures are complex and may cause artifact. Recently, coherent Raman microscopy has been proven to be an emerging technology to study de- and remyelination of the injured spinal cord; however, limited penetration depth and small imaging field prevent it from comprehensive assessments of large areas of damaged tissues. Here, we report the use of bond-selective photoacoustic (PA) imaging with 1730-nm excitation, where the first overtone vibration of CH2 bond is located, to assess WM loss after a contusive SCI in adult rats. By employing the first overtone vibration of CH2 bond as the contrast, the mapping of the WM in an intact spinal cord was achieved in a label-free three-dimensional manner, and the physiological change of the spinal cord before and after injury was observed. Moreover, the recovery of the spinal cord from contusive injury with the treatment of a neuroprotective nanomedicine ferulic-acid-conjugated glycol chitosan (FA-GC) was also observed. Our study suggests that bond-selective PA imaging is a valuable tool to assess the progression of WM pathology after SCI as well as neuroprotective therapeutics in a label-free manner.Item Association analysis of rare variants near the APOE region with CSF and neuroimaging biomarkers of Alzheimer's disease(Springer Nature, 2017-05-24) Nho, Kwangsik; Kim, Sungeun; Horgusluoglu, Emrin; Risacher, Shannon L.; Shen, Li; Kim, Dokyoon; Lee, Seunggeun; Foroud, Tatiana; Shaw, Leslie M.; Trojanowski, John Q.; Aisen, Paul S.; Petersen, Ronald C.; Jack, Clifford R., Jr.; Weiner, Michael W.; Green, Robert C.; Toga, Arthur W.; Saykin, Andrew J.; Radiology and Imaging Sciences, School of MedicineBACKGROUND: The APOE ε4 allele is the most significant common genetic risk factor for late-onset Alzheimer's disease (LOAD). The region surrounding APOE on chromosome 19 has also shown consistent association with LOAD. However, no common variants in the region remain significant after adjusting for APOE genotype. We report a rare variant association analysis of genes in the vicinity of APOE with cerebrospinal fluid (CSF) and neuroimaging biomarkers of LOAD. METHODS: Whole genome sequencing (WGS) was performed on 817 blood DNA samples from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Sequence data from 757 non-Hispanic Caucasian participants was used in the present analysis. We extracted all rare variants (MAF (minor allele frequency) < 0.05) within a 312 kb window in APOE's vicinity encompassing 12 genes. We assessed CSF and neuroimaging (MRI and PET) biomarkers as LOAD-related quantitative endophenotypes. Gene-based analyses of rare variants were performed using the optimal Sequence Kernel Association Test (SKAT-O). RESULTS: A total of 3,334 rare variants (MAF < 0.05) were found within the APOE region. Among them, 72 rare non-synonymous variants were observed. Eight genes spanning the APOE region were significantly associated with CSF Aβ1-42 (p < 1.0 × 10-3). After controlling for APOE genotype and adjusting for multiple comparisons, 4 genes (CBLC, BCAM, APOE, and RELB) remained significant. Whole-brain surface-based analysis identified highly significant clusters associated with rare variants of CBLC in the temporal lobe region including the entorhinal cortex, as well as frontal lobe regions. Whole-brain voxel-wise analysis of amyloid PET identified significant clusters in the bilateral frontal and parietal lobes showing associations of rare variants of RELB with cortical amyloid burden. CONCLUSIONS: Rare variants within genes spanning the APOE region are significantly associated with LOAD-related CSF Aβ1-42 and neuroimaging biomarkers after adjusting for APOE genotype. These findings warrant further investigation and illustrate the role of next generation sequencing and quantitative endophenotypes in assessing rare variants which may help explain missing heritability in AD and other complex diseases.Item Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health‐related comorbidities in a community‐dwelling cohort(Wiley, 2024) Rudolph, Marc D.; Sutphen, Courtney L.; Register, Thomas C.; Whitlow, Christopher T.; Solingapuram Sai, Kiran K.; Hughes, Timothy M.; Bateman, James R.; Dage, Jeffrey L.; Russ, Kristen A.; Mielke, Michelle M.; Craft, Suzanne; Lockhart, Samuel N.; Neurology, School of MedicineIntroduction: We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. Methods: We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). Results: Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. Discussion: eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. Highlights: Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.Item Associations Between Social Network Characteristics and Brain Structure Among Older Adults(Wiley, 2024) Manchella, Mohit K.; Logan, Paige E.; Perry, Brea L.; Peng, Siyun; Risacher, Shannon L.; Saykin, Andrew J.; Apostolova, Liana G.; Neurology, School of MedicineIntroduction: Social connectedness is associated with slower cognitive decline among older adults. Recent research suggests that distinct aspects of social networks may have differential effects on cognitive resilience, but few studies analyze brain structure. Methods: This study includes 117 cognitively impaired and 59 unimpaired older adults. The effects of social network characteristics (bridging/bonding) on brain regions of interests were analyzed using linear regressions and voxel-wise multiple linear regressions of gray matter density. Results: Increased social bridging was associated with greater bilateral amygdala volume and insular thickness, and left frontal lobe thickness, putamen, and thalamic volumes. Increased social bonding was associated with greater bilateral medial orbitofrontal and caudal anterior cingulate thickness, as well as right frontal lobe thickness, putamen, and amygdala volumes. Discussion: The associations between social connectedness and brain structure vary depending on the types of social enrichment accessible through social networks, suggesting that psychosocial interventions could mitigate neurodegeneration. Highlights: Distinct forms of social capital are uniquely linked to gray matter density (GMD). Bridging is associated with preserved GMD in limbic system structures. Bonding is associated with preserved GMD in frontal lobe regions. Bridging is associated with increased brain reserve in sensory processing regions. Bonding is associated with increased brain reserve in regions of stress modulation.Item Atypical Alzheimer Disease Variants(Wolters Kluwer, 2022) Polsinelli, Angelina J.; Apostolova, Liana G.; Neurology, School of MedicinePurpose of review: This article discusses the clinical, neuroimaging, and biomarker profiles of sporadic atypical Alzheimer disease (AD) variants, including early-onset AD, posterior cortical atrophy, logopenic variant primary progressive aphasia, dysexecutive variant and behavioral variant AD, and corticobasal syndrome. Recent findings: Significant advances are being made in the recognition and characterization of the syndromically diverse AD variants. These variants are identified by the predominant cognitive and clinical features: early-onset amnestic syndrome, aphasia, visuospatial impairments, dysexecutive and behavioral disturbance, or motor symptoms. Although understanding of regional susceptibility to disease remains in its infancy, visualizing amyloid and tau pathology in vivo and CSF examination of amyloid-β and tau proteins are particularly useful in atypical AD, which can be otherwise prone to misdiagnosis. Large-scale research efforts, such as LEADS (the Longitudinal Early-Onset Alzheimer Disease Study), are currently ongoing and will continue to shed light on our understanding of these diverse presentations. Summary: Understanding the clinical, neuroimaging, and biomarker profiles of the heterogeneous group of atypical AD syndromes improves diagnostic accuracy in patients who are at increased risk of misdiagnosis. Earlier accurate identification facilitates access to important interventions, social services and disability assistance, and crucial patient and family education.Item Autosomal Dominantly Inherited Alzheimer Disease: Analysis of genetic subgroups by Machine Learning(Elsevier, 2020-06) Castillo-Barne, Diego; Su, Li; Ramírez, Javier; Salas-Gonzalez, Diego; Martinez-Murcia, Francisco J.; Illan, Ignacio A.; Segovia, Fermin; Ortiz, Andres; Cruchaga, Carlos; Farlow, Martin R.; Xiong, Chengjie; Graff-Radford, Neil R.; Schofield, Peter R.; Masters, Colin L.; Salloway, Stephen; Jucker, Mathias; Mori, Hiroshi; Levin, Johannes; Gorriz, Juan M.; Neurology, School of MedicineDespite subjects with Dominantly-Inherited Alzheimer's Disease (DIAD) represent less than 1% of all Alzheimer's Disease (AD) cases, the Dominantly Inherited Alzheimer Network (DIAN) initiative constitutes a strong impact in the understanding of AD disease course with special emphasis on the presyptomatic disease phase. Until now, the 3 genes involved in DIAD pathogenesis (PSEN1, PSEN2 and APP) have been commonly merged into one group (Mutation Carriers, MC) and studied using conventional statistical analysis. Comparisons between groups using null-hypothesis testing or longitudinal regression procedures, such as the linear-mixed-effects models, have been assessed in the extant literature. Within this context, the work presented here performs a comparison between different groups of subjects by considering the 3 genes, either jointly or separately, and using tools based on Machine Learning (ML). This involves a feature selection step which makes use of ANOVA followed by Principal Component Analysis (PCA) to determine which features would be realiable for further comparison purposes. Then, the selected predictors are classified using a Support-Vector-Machine (SVM) in a nested k-Fold cross-validation resulting in maximum classification rates of 72-74% using PiB PET features, specially when comparing asymptomatic Non-Carriers (NC) subjects with asymptomatic PSEN1 Mutation-Carriers (PSEN1-MC). Results obtained from these experiments led to the idea that PSEN1-MC might be considered as a mixture of two different subgroups including: a first group whose patterns were very close to NC subjects, and a second group much more different in terms of imaging patterns. Thus, using a k-Means clustering algorithm it was determined both subgroups and a new classification scenario was conducted to validate this process. The comparison between each subgroup vs. NC subjects resulted in classification rates around 80% underscoring the importance of considering DIAN as an heterogeneous entity.