Browsing by Subject "Cognitive performance"
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Item 39. Viruses and Schizophrenia: Implications for Pathophysiology and Treatment(Oxford University Press, 2018-04) Breier, Alan; Psychiatry, School of MedicineOverall Abstract: The viral hypothesis of schizophrenia posits that viral infections disrupts cortical circuits that give rise to schizophrenia psychopathology. Prenatal viral exposure during key neurodevelopmental periods, either through direct effects on fetal brain or exposure to excessive maternal cytokines and other chemokines, have been implicated. In addition, abnormal activation of dormant neuro-viruses have been linked to the pathophysiology of schizophrenia. Activation of dormant viruses has potentially important treatment implication for therapies, such as valacyclovir, that suppress viral activity. Among the viruses that have been mostly frequently associated with schizophrenia include herpes simplex virus type 1 (HSV1) and Epstein-Barr virus (EBV). The purpose of this symposium is to focus on the role of viruses in the pathophysiology of schizophrenia and results of antiviral treatment trials in this illness.Item Alzheimer’s Disease Heterogeneity Explained by Polygenic Risk Scores Derived from Brain Transcriptomic Profiles(Wiley, 2023) Chung, Jaeyoon; Sahelijo, Nathan; Maruyama, Toru; Hu, Junming; Panitch, Rebecca; Xia, Weiming; Mez, Jesse; Stein, Thor D.; Alzheimer’s Disease Neuroimaging Initiative; Saykin, Andrew J.; Takeyama, Haruko; Farrer, Lindsay A.; Crane, Paul K.; Nho, Kwangsik; Jun, Gyungah R.; Radiology and Imaging Sciences, School of MedicineIntroduction: Alzheimer's disease (AD) is heterogeneous, both clinically and neuropathologically. We investigated whether polygenic risk scores (PRSs) integrated with transcriptome profiles from AD brains can explain AD clinical heterogeneity. Methods: We conducted co-expression network analysis and identified gene sets (modules) that were preserved in three AD transcriptome datasets and associated with AD-related neuropathological traits including neuritic plaques (NPs) and neurofibrillary tangles (NFTs). We computed the module-based PRSs (mbPRSs) for each module and tested associations with mbPRSs for cognitive test scores, cognitively defined AD subgroups, and brain imaging data. Results: Of the modules significantly associated with NPs and/or NFTs, the mbPRSs from two modules (M6 and M9) showed distinct associations with language and visuospatial functioning, respectively. They matched clinical subtypes and brain atrophy at specific regions. Discussion: Our findings demonstrate that polygenic profiling based on co-expressed gene sets can explain heterogeneity in AD patients, enabling genetically informed patient stratification and precision medicine in AD. Highlights: Co-expression gene-network analysis in Alzheimer's disease (AD) brains identified gene sets (modules) associated with AD heterogeneity. AD-associated modules were selected when genes in each module were enriched for neuritic plaques and neurofibrillary tangles. Polygenic risk scores from two selected modules were linked to the matching cognitively defined AD subgroups (language and visuospatial subgroups). Polygenic risk scores from the two modules were associated with cognitive performance in language and visuospatial domains and the associations were confirmed in regional-specific brain atrophy data.Item The Cognitive Change Index as a Measure of Self and Informant Perception of Cognitive Decline: Relation to Neuropsychological Tests(IOS Press, 2016-02-25) Rattanabannakit, Chatchawan; Risacher, Shannon L.; Gao, Sujuan; Lane, Kathleen A.; Brown, Steven A.; McDonald, Brenna C.; Unverzagt, Frederick W.; Apostolova, Liana G.; Saykin, Andrew J.; Farlow, Martin R.; Department of Neurology, IU School of MedicineBACKGROUND: The perception of cognitive decline by individuals and those who know them well ("informants") has been inconsistently associated with objective cognitive performance, but strongly associated with depressive symptoms. OBJECTIVE: We investigated associations of self-report, informant-report, and discrepancy between self- and informant-report of cognitive decline obtained from the Cognitive Change Index (CCI) with cognitive test performance and self-reported depressive symptoms. METHODS: 267 participants with normal cognition, mild cognitive impairment (MCI), or mild dementia were included from a cohort study and memory clinic. Association of test performance and self-rated depression (Geriatric Depression Scale, GDS) with CCI scores obtained from subjects (CCI-S), their informants (CCI-I), and discrepancy scores between subjects and informants (CCI-D; CCI-S minus CCI-I) were analyzed using correlation and analysis of covariance (ANCOVA) models. RESULTS: CCI-S and CCI-I scores showed high internal consistency (Cronbach alpha 0.96 and 0.98, respectively). Higher scores on CCI-S and CCI-I, and lower scores on the CCI-D, were associated with lower performance on various cognitive tests in both univariate and in ANCOVA models adjusted for age, gender, and education. Adjustment for GDS slightly weakened the relationships between CCI and test performance but most remained significant. CONCLUSION: Self- and informant-report of cognitive decline, as measured by the CCI, show moderately strong relationships with objective test performance independent of age, gender, education, and depressive symptoms. The CCI appears to be a valid cross-sectional measure of self and informant perception of cognitive decline across the continuum of functioning. Studies are needed to address the relationship of CCI scores to longitudinal outcome.Item Novel rare variant associations with late‐life cognitive performance(Wiley, 2025-01-09) Regelson, Alexandra N.; Archer, Derek B.; Durant, Alaina; Mukherjee, Shubhabrata; Lee, Michael L.; Choi, Seo-Eun; Scollard, Phoebe; Trittschuh, Emily H.; Mez, Jesse; Bush, William S.; Kuzma, Amanda B.; Cuccaro, Michael L.; Cruchaga, Carlos; Farrer, Lindsay A.; Wang, Li-San; Schellenberg, Gerard D.; Mayeux, Richard; Kukull, Walter A.; Keene, C. Dirk; Saykin, Andrew J.; Johnson, Sterling C.; Engelman, Corinne D.; Bennett, David A.; Barnes, Lisa L.; Larson, Eric B.; Nho, Kwangsik; Goate, Alison M.; Renton, Alan E.; Marcora, Edoardo; Fulton-Howard, Brian; Patel, Tulsi; Risacher, Shannon L.; DeStefano, Anita L.; Schneider, Julie A.; Habes, Mohamad; Seshadri, Sudha; Satizabal, Claudia L.; Maillard, Pauline; Toga, Arthur W.; Crawford, Karen; Tosun, Duygu; Vance, Jeffery M.; Mormino, Elizabeth; DeCarli, Charles S.; Montine, Thomas J.; Beecham, Gary; Biber, Sarah A.; De Jager, Philip L.; Vardarajan, Badri N.; Lee, Annie J.; Brickman, Adam M.; Reitz, Christiane; Manly, Jennifer J.; Lu, Qiongshi; Rentería, Miguel Arce; Deming, Yuetiva; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Crane, Paul K.; Hohman, Timothy J.; Dumitrescu, Logan C.; Medical and Molecular Genetics, School of MedicineBackground: Despite evidence that Alzheimer’s disease (AD) is highly heritable, there remains substantial “missing” heritability, likely due in part to the effect of rare variants and to the past reliance on case‐control analysis. Here, we leverage powerful endophenotypes of AD (cognitive performance across multiple cognitive domains) in a rare variant analysis to identify novel genetic drivers of cognition in aging and disease. Method: We leveraged 8 cohorts of cognitive aging with whole genome sequencing data from the AD Sequencing Project to conduct rare variant analyses of multiple domains of cognition (N = 9,317; mean age = 73; 56% female; 52% cognitively unimpaired). Harmonized scores for memory, executive function, and language were derived using confirmatory factor analysis models. Participants genetically similar to the 1000Genomes EUR reference panel were included in analysis. Variants included in the analysis had a minor allele frequency < 0.01, a minor allele count of ≥ 10, and were annotated as a high or moderate impact SNP using VEP. Associations of baseline scores in each cognitive domain were performed using SKAT‐O, including 92,905 rare variants among 16,243 genes. All tests were adjusted for sex, baseline age, sequencing center and platform, and genetic principal components. Correction for multiple comparisons was completed using the Benjamini‐Hochberg false discovery rate (FDR) procedure. Result: APOE was associated with baseline memory, language, and executive function, though only memory survived multiple‐test correction (p.FDR = 0.001). Outside of APOE, ITPKB was associated with baseline executive function (p.FDR = 0.048). AKTIP, SHCBP1L, and CCNF showed nominal associations with multiple domains of cognition that did not survive correction for multiple comparisons (p.FDRs<0.07). Conclusion: These results highlight novel rare variants associated with cognition. IPTKB is an AGORA nominated gene target for potential AD treatment. It is important in the regulation of immune cells and displays higher expression in the cortex of AD patients compared to controls. CCNF and AKTIP are brain eQTLs and have differential RNA expression in AD brains. Previously, variants in AKTIP have been associated with educational attainment, intelligence, and memory, while variants in CCNF have been associated with neuritic plaques and neurofibrillary tangles. Future analyses will incorporate longitudinal cognition and expand into additional populations.Item Robust Brain Correlates of Cognitive Performance in Psychosis and Its Prodrome(Elsevier, 2025) Ward, Heather Burrell; Beermann, Adam; Xie, Jing; Yildiz, Gulcan; Felix, Karlos Manzanarez; Addington, Jean; Bearden, Carrie E.; Cadenhead, Kristin; Cannon, Tyrone D.; Cornblatt, Barbara; Keshavan, Matcheri; Mathalon, Daniel; Perkins, Diana O.; Seidman, Larry; Stone, William S.; Tsuang, Ming T.; Walker, Elaine F.; Woods, Scott; Coleman, Michael J.; Bouix, Sylvain; Holt, Daphne J.; Öngür, Dost; Breier, Alan; Shenton, Martha E.; Heckers, Stephan; Halko, Mark A.; Lewandowski, Kathryn E.; Brady, Roscoe O., Jr.; Psychiatry, School of MedicineBackground: Neurocognitive impairment is a well-known phenomenon in schizophrenia that begins prior to psychosis onset. Connectome-wide association studies have inconsistently linked cognitive performance to resting-state functional magnetic resonance imaging. We hypothesized that a carefully selected cognitive instrument and refined population would allow identification of reliable brain-behavior associations with connectome-wide association studies. To test this hypothesis, we first identified brain-cognition correlations via a connectome-wide association study in early psychosis. We then asked, in an independent dataset, if these brain-cognition relationships would generalize to individuals who develop psychosis in the future. Methods: The Seidman Auditory Continuous Performance Task (ACPT) effectively differentiates healthy participants from those with psychosis. Our connectome-wide association study used the HCP-EP (Human Connectome Project for Early Psychosis) (n = 183) to identify links between connectivity and ACPT performance. We then analyzed data from the NAPLS2 (North American Prodrome Longitudinal Study 2) (n = 345), a multisite prospective study of individuals at risk for psychosis. We tested the connectome-wide association study-identified cognition-connectivity relationship in both individuals at risk for psychosis and control participants. Results: Our connectome-wide association study in early-course psychosis identified robust associations between better ACPT performance and higher prefrontal-somatomotor connectivity (p < .005). Prefrontal-somatomotor connectivity was also related to ACPT performance in at-risk individuals who would develop psychosis (n = 17). This finding was not observed in nonconverters (n = 196) or control participants (n = 132). Conclusions: This connectome-wide association study identified reproducible links between connectivity and cognition in separate samples of individuals with psychosis and at-risk individuals who would later develop psychosis. A carefully selected task and population improves the ability of connectome-wide association studies to identify reliable brain-phenotype relationships.Item Sex differences in cognitive performance and alcohol consumption in High Alcohol-Drinking (HAD-1) rats(Elsevier, 2020-03-02) Mittal, N.; Fleming, S.M.; Martinez, A.; Thakore, N.; Bell, Richard L.; Maddox, W.T.; Schallert, T.; Duvauchelle, C.L.; Psychiatry, School of MedicineExcessive alcohol (ethanol) consumption negatively impacts social, emotional, as well as cognitive function and well-being. Thus, identifying behavioral and/or biological predictors of excessive ethanol consumption is important for developing prevention and treatment strategies against alcohol use disorders (AUDs). Sex differences in alcohol consumption patterns are observed in humans, primates, and rodents. Selectively bred high alcohol-drinking rat lines, such as the “HAD-1” lines are recognized animal models of alcoholism. The present work examined sex differences in alcohol consumption, object recognition, and exploratory behavior in male and female HAD-1 rats. Naïve male and female HAD-1 rats were tested in an object recognition test (ORT) prior to a chronic 24 h intermittent ethanol access procedure for five weeks. Object recognition parameters measured included exploratory behavior, object investigation, and time spent near objects. During the initial training trial, rearing, active object investigation and amount of time spent in the object-containing section was significantly greater in female HAD-1 rats compared to their male counterparts. During the subsequent testing trial, time spent in the object-containing section was greater in female, compared to male, rats; but active object investigation and rearing did not statistically differ between females and males. In addition, female HAD-1 rats consumed significantly more ethanol than their male counterparts, replicating previous findings. Moreover, across all animals there was a significant positive correlation between exploratory behavior in ORT and ethanol consumption level. These results indicate there are significant sex differences in cognitive performance and alcohol consumption in HAD-1 rats, which suggests neurobiological differences as well.Item Sleep problems, fatigue, and cognitive performance in Chinese kindergarten children(Elsevier, 2012) Liu, Jianghong; Zhou, Guoping; Wang, Yingjie; Ai, Yuexian; Pinto-Martin, Jennifer; Liu, Xianchen; Pediatrics, School of MedicineObjective: To examine sleep problems and fatigue and their associations with cognitive performance in Chinese kindergarten children. Study design: A cross-sectional analysis of baseline data from Jintan Child Cohort Study was conducted, which includes a cohort of 1656 kindergarten children in Jintan City, Jiangsu Province, China. The sample used in the current study consisted of 1385 children (44.8% girls, mean age 5.72 [SD = 0.42] years) for whom data on sleep problems or cognitive performance were available. Child Behavior Checklist was used to measure child sleep problems and fatigue, and Wechsler Preschool and Primary Scale of Intelligence-Revised was used to assess child IQ. Results: Sleep problems were prevalent, ranging from 8.9% for difficulty maintaining sleep to 70.5% for unwilling to sleep alone. Other reported sleep problems were difficulty initiating sleep (39.4%), nightmares (31.6%), sleep talking (28%), sleeping less (24.7%), and sleep resistance (23.4%). Fatigue was also prevalent, with 29.6% of children reported to be overtired and 12.6% lack of energy. Children with difficulty maintaining sleep, sleep talking, sleep resistance, or nightmares scored 2-3 points lower in full IQ than children without sleep problems. Children reported to have fatigue scored 3-6 points lower in full IQ than those children without fatigue. Conclusions: Sleep problems and fatigue are prevalent in Chinese kindergarten children. Furthermore, sleep problems and fatigue are associated with poor cognitive performance.Item White Matter Abnormalities and Cognition in Aging and Alzheimer Disease(American Medical Association, 2025-06-09) Peter, Christopher; Sathe, Aditi; Shashikumar, Niranjana; Pechman, Kimberly R.; Workmeister, Abigail W.; Jackson, T. Bryan; Huo, Yuankai; Mukherjee, Shubhabrata; Mez, Jesse; Dumitrescu, Logan C.; Gifford, Katherine A.; Bolton, Corey J.; Gaynor, Leslie S.; Risacher, Shannon L.; Beason-Held, Lori L.; An, Yang; Arfanakis, Konstantinos; Erus, Guray; Davatzikos, Christos; Tosun-Turgut, Duygu; Habes, Mohamad; Wang, Di; Toga, Arthur W.; Thompson, Paul M.; Zhang, Panpan; Schilling, Kurt G.; Albert, Marilyn; Kukull, Walter; Biber, Sarah A.; Landman, Bennett A.; Bendlin, Barbara B.; Johnson, Sterling C.; Schneider, Julie; Barnes, Lisa L.; Bennett, David A.; Jefferson, Angela L.; Resnick, Susan M.; Saykin, Andrew J.; Crane, Paul K.; Cuccaro, Michael L.; Hohman, Timothy J.; Archer, Derek B.; Alzheimer’s Disease Sequencing Project Phenotype Harmonization Consortium (ADSP-PHC) Analyst Team; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Biomarkers of Cognitive Decline Among Normal Adults (BIOCARD) Study Team; Alzheimer’s Disease Sequencing Project (ADSP); Zaras, Dimitrios; Yang, Yisu; Durant, Alaina; Kanakaraj, Praitayini; Kim, Michael E.; Gao, Chenyu; Newlin, Nancy R.; Ramadass, Karthik; Khairi, Nazirah Mohd; Li, Zhiyuan; Yao, Tianyuan; Choi, Seo-Eun; Klinedinst, Brandon; Lee, Michael L.; Scollard, Phoebe; Trittschuh, Emily H.; Sanders, Elizabeth A.; Radiology and Imaging Sciences, School of MedicineImportance: There has yet to be a large-scale study quantifying the association between white matter microstructure and cognitive performance and decline in aging and Alzheimer disease (AD). Objective: To investigate the associations between tract-specific white matter microstructure and cognitive performance and decline in aging and AD-related cognitive impairment. Design, setting, and participants: This prognostic study of aging and AD, a secondary data analysis of multisite cohort studies, acquired data from 9 cohorts between September 2002 and November 2022. Participants were eligible if they had diffusion-weighted magnetic resonance imaging (dMRI) data, domain-specific cognitive composite z scores, demographic and clinical data, were aged 50 years or older, and passed neuroimaging quality control. Demographic and clinical covariates included age, sex, education, race and ethnicity, APOE haplotype status (ε2, ε3, ε4), and clinical status. The present study was conducted from June 2024 to February 2025. Exposures: White matter microstructure and cognitive performance and decline. Main outcomes and measures: Clinical diagnosis, imaging measures (dMRI, T1-weighted MRI, and amyloid and tau positron emission tomography), and cognitive tests. Results: Of 4467 participants who underwent 9208 longitudinal cognitive sessions, 2698 (60.4%) were female, and the mean age (SD) was 74.3 (9.2) years; 3213 were cognitively unimpaired, 972 had mild cognitive impairment, and 282 had AD dementia. White matter free water (FW) showed the strongest associations with cross-sectional cognitive performance and longitudinal cognitive decline across all domains, particularly memory. FW in limbic tracts, such as the cingulum, presented the strongest associations with both memory performance (cingulum: β = -0.718; P < .001; fornix: β = -1.069; P < .001) and decline (cingulum: β = -0.115; P < .001; fornix: β = -0.153; P < .001). White matter FW measures interacted with baseline diagnosis, gray matter atrophy, APOE ε4 status, and amyloid positivity to predict poorer cognitive performance and accelerated cognitive decline. Noteworthy interactions include fornix FW and hippocampal volume (β = 10.598; P < .001), cingulum FW and SPARE-AD index (β = -0.532; P < .001), and inferior temporal gyrus transcallosal tract FW and baseline diagnosis (β = -0.537; P < .001), all predicting poorer memory performance. Conclusions and relevance: White matter microstructural changes, particularly FW, play a critical role in cognitive decline in aging and AD-related cognitive impairment. These findings highlight the importance of FW correction in dMRI studies and highlight the limbic system, especially the cingulum and fornix, as key regions associated with cognitive decline; the interaction models highlight that integrating FW-corrected metrics with other AD biomarkers may further elucidate the biological mechanisms of neurodegeneration in aging.