Browsing by Subject "Phenotypes"

Now showing 1 - 6 of 6
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    Database queries for hospitalizations for acute congestive heart failure: flexible methods and validation based on set theory
    (Oxford University Press, 2014-03-01) Rosenman, Marc; He, Jinghua; Martin, Joel; Nutakki, Kavitha; Eckert, George; Lane, Kathleen; Gradus-Pizlo, Irmina; Hui, Siu L.; Department of Pediatrics, IU School of Medicine
    Background and objective Electronic health records databases are increasingly used for identifying cohort populations, covariates, or outcomes, but discerning such clinical ‘phenotypes’ accurately is an ongoing challenge. We developed a flexible method using overlapping (Venn diagram) queries. Here we describe this approach to find patients hospitalized with acute congestive heart failure (CHF), a sampling strategy for one-by-one ‘gold standard’ chart review, and calculation of positive predictive value (PPV) and sensitivities, with SEs, across different definitions. Materials and methods We used retrospective queries of hospitalizations (2002–2011) in the Indiana Network for Patient Care with any CHF ICD-9 diagnoses, a primary diagnosis, an echocardiogram performed, a B-natriuretic peptide (BNP) drawn, or BNP >500 pg/mL. We used a hybrid between proportional sampling by Venn zone and over-sampling non-overlapping zones. The acute CHF (presence/absence) outcome was based on expert chart review using a priori criteria. Results Among 79 091 hospitalizations, we reviewed 908. A query for any ICD-9 code for CHF had PPV 42.8% (SE 1.5%) for acute CHF and sensitivity 94.3% (1.3%). Primary diagnosis of 428 and BNP >500 pg/mL had PPV 90.4% (SE 2.4%) and sensitivity 28.8% (1.1%). PPV was <10% when there was no echocardiogram, no BNP, and no primary diagnosis. ‘False positive’ hospitalizations were for other heart disease, lung disease, or other reasons. Conclusions This novel method successfully allowed flexible application and validation of queries for patients hospitalized with acute CHF.
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    Dissociable spatial topography of neurodegeneration in Early‐onset and Late‐onset Alzheimer’s Disease: A head‐to‐head comparison of MRI‐derived atrophy measures between the LEADS and ADNI cohorts
    (Wiley, 2025-01-09) Katsumi, Yuta; Touroutoglou, Alexandra; Brickhouse, Michael; Eckbo, Ryan; La Joie, Renaud; Eloyan, Ani; Nudelman, Kelly N.; Foroud, Tatiana M.; Dage, Jeffrey L.; Carrillo, Maria C.; Rabinovici, Gil D.; Apostolova, Liana G.; Dickerson, Bradford C.; LEADS Consortium; Neurology, School of Medicine
    Background: Understanding how early‐onset Alzheimer’s disease (EOAD) differs from typical late‐onset AD (LOAD) is an important goal of AD research that may help increase the sensitivity of unique biomarkers for each phenotype. Building upon prior work based on small samples, here we leveraged two large, well‐characterized natural history study cohorts of AD patients (LEADS and ADNI3) to test the hypothesis that EOAD patients would show more prominent lateral and medial parietal and lateral temporal cortical atrophy sparing the medial temporal lobe (MTL), whereas LOAD patients would show prominent MTL atrophy. Method: We investigated differences in the spatial topography of cortical atrophy between EOAD and LOAD patients by analyzing structural MRI data collected from 211 patients with sporadic EOAD and 88 cognitively unimpaired (CU) participants from the LEADS cohort as well as 144 patients with LOAD and 365 CU participants from the ADNI3 cohort. MRI data were processed via FreeSurfer v6.0 to estimate cortical thickness for each participant. A direct comparison of cortical thickness was performed between EOAD and LOAD patients based on W‐scores (i.e., Z‐scores adjusted for age and sex relative to CU participants within each cohort) while controlling for MMSE total scores. All patients underwent amyloid PET with 18F‐Florbetaben or 18F‐Florbetapir and amyloid positivity was centrally determined by quantification‐supported visual read. Result: As expected, a direct comparison of cortical thickness between patients with EOAD and LOAD revealed a double dissociation between AD clinical phenotype and localization of cortical atrophy: EOAD patients showed greater atrophy in widespread cortical areas including the inferior parietal lobule (EOAD marginal mean W‐score ± SEM = ‐1.33±0.08 vs. LOAD = ‐0.52±0.09, p<.001, η2=.097), precuneus (‐1.66±0.09 vs. ‐0.59±0.10, p<.001, η2=.13), and caudal middle frontal gyrus (‐1.65±0.08 vs. ‐0.90±0.10, p<.001, η2=.074), whereas LOAD patients showed greater atrophy in the entorhinal/perirhinal cortex and temporal pole (‐1.00±0.09 vs. ‐1.41±0.11, p<.008, η2=.019). Conclusion: These findings demonstrate a clearly dissociable spatial pattern of neurodegeneration between EOAD and LOAD, supporting our previously developed LOAD and EOAD signatures of cortical atrophy, which underlies the distinct episodic memory and other cognitive characteristics of these AD clinical phenotypes.
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    Distinct mouse models correspond to distinct AD molecular subtypes
    (Wiley, 2025-01-03) Pandey, Ravi S.; Carter, Gregory W.; Howell, Gareth R.; Sasner, Michael; Kotredes, Kevin P.; Oblak, Adrian L.; Lamb, Bruce T.; Pharmacology and Toxicology, School of Medicine
    Background: Alzheimer’s disease (AD) is a complex, multifactorial pathology with high heterogeneity in biological alterations. Our understanding of cellular and molecular mechanisms from disease risk variants to various phenotypes is still limited. Mouse models of AD serve as indispensable platforms for comprehensively characterizing AD pathology, disease progression, and biological mechanisms. However, selection of the right model in preclinical research and translation of findings to clinical populations are intricate processes that require identification of pathophysiological resemblance between model organisms and humans. Many existing clinical trials that showed promising efficacy in one particular mouse model later do not align with human trial results, assuming that study had consisted of a heterogeneous group of participants, and individual animal models may only recapitulate features of a subgroup of human cases. To improve interspecies translation, it is necessary to comprehensively compare molecular signatures in mouse models with subgroup of human AD cases with distinct molecular signatures. Method: We performed transcriptomic and proteomics analysis on whole brain samples from mouse models carrying LOAD risk variants. To assess the human disease relevance of LOAD risk variants in mice, we determined the extent to which changes due to genetic perturbations in mice matched those observed in human AD subtypes and disease stages of AD in the ROS/MAP, Mayo and Mount Sinai Brain Bank cohorts. Genesets within these disease subtypes are highly co‐expressed and represent specific molecular pathways. Result: We have identified that distinct mouse models match to distinct human AD subtypes in age‐dependent manner. Specifically, mouse models carrying human AD risk variants such as Abca7*A1527G showed strong correlation with inflammatory AD subtypes, while mouse models carrying risk variant such as Plcg2*M28L exhibited transcriptomics changes similar to non‐inflammatory AD subtypes. Conclusion: In this study, we highlighted that mouse model of AD may match to a particular subset of human AD subtypes but not all subtypes simultaneously, and that risk for these subtypes may be influenced by distinct AD genetic factors. Additional work toward validating and better understanding the role of each subtype key regulator in its matching mouse model will provide great value and have a great impact on future studies of AD.
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    Heterogeneous clinical phenotypes of sporadic early-onset Alzheimer's disease: a neuropsychological data-driven approach
    (Springer Nature, 2025-02-06) Putcha, Deepti; Katsumi, Yuta; Touroutoglou, Alexandra; Eloyan, Ani; Taurone, Alexander; Thangarajah, Maryanne; Aisen, Paul; Dage, Jeffrey L.; Foroud, Tatiana; Jack, Clifford R., Jr.; Kramer, Joel H.; Nudelman, Kelly N. H.; Raman, Rema; Vemuri, Prashanthi; Atri, Alireza; Day, Gregory S.; Duara, Ranjan; Graff-Radford, Neill R.; Grant, Ian M.; Honig, Lawrence S.; Johnson, Erik C. B.; Jones, David T.; Masdeu, Joseph C.; Mendez, Mario F.; Musiek, Erik; Onyike, Chiadi U.; Riddle, Meghan; Rogalski, Emily; Salloway, Stephen; Sha, Sharon; Turner, R. Scott; Wingo, Thomas S.; Wolk, David A.; Womack, Kyle; Carrillo, Maria C.; Rabinovici, Gil D.; Dickerson, Bradford C.; Apostolova, Liana G.; Hammers, Dustin B.; LEADS Consortium; Neurology, School of Medicine
    Background: The clinical presentations of early-onset Alzheimer's disease (EOAD) and late-onset Alzheimer's disease are distinct, with EOAD having a more aggressive disease course with greater heterogeneity. Recent publications from the Longitudinal Early-Onset Alzheimer's Disease Study (LEADS) described EOAD as predominantly amnestic, though this phenotypic description was based solely on clinical judgment. To better understand the phenotypic range of EOAD presentation, we applied a neuropsychological data-driven method to subtype the LEADS cohort. Methods: Neuropsychological test performance from 169 amyloid-positive EOAD participants were analyzed. Education-corrected normative comparisons were made using a sample of 98 cognitively normal participants. Comparing the relative levels of impairment between each cognitive domain, we applied a cut-off of 1 SD below all other domain scores to indicate a phenotype of "predominant" impairment in a given cognitive domain. Individuals were otherwise considered to have multidomain impairment. Whole-cortex general linear modeling of cortical atrophy was applied as an MRI-based validation of these distinct clinical phenotypes. Results: We identified 6 phenotypic subtypes of EOAD: Dysexecutive Predominant (22% of sample), Amnestic Predominant (11%), Language Predominant (11%), Visuospatial Predominant (15%), Mixed Amnestic/Dysexecutive Predominant (11%), and Multidomain (30%). These phenotypes did not differ by age, sex, or years of education. The APOE ɛ4 genotype was enriched in the Amnestic Predominant group, who were also rated as least impaired. Cortical thickness analysis validated these clinical phenotypes with dissociations in atrophy patterns observed between the Dysexecutive and Amnestic Predominant groups. In contrast to the heterogeneity observed from our neuropsychological data-driven approach, diagnostic classifications for this same sample based solely on clinical judgment indicated that 82% of individuals were amnestic-predominant, 9% were non-amnestic, 4% met criteria for Posterior Cortical Atrophy, and 5% met criteria for Primary Progressive Aphasia. Conclusion: A neuropsychological data-driven method to phenotype EOAD individuals uncovered a more detailed understanding of the presenting heterogeneity in this atypical AD sample compared to clinical judgment alone. Clinicians and patients may over-report memory dysfunction at the expense of non-memory symptoms. These findings have important implications for diagnostic accuracy and treatment considerations.
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    Replication stress increases de novo CNVs across the malaria parasite genome
    (bioRxiv, 2024-12-31) Brown, Noah; Luniewski, Aleksander; Yu, Xuanxuan; Warthan, Michelle; Liu, Shiwei; Zulawinska, Julia; Ahmad, Syed; Congdon, Molly; Santos, Webster; Xiao, Feifei; Guler, Jennifer L.; Radiology and Imaging Sciences, School of Medicine
    Changes in the copy number of large genomic regions, termed copy number variations (CNVs), contribute to important phenotypes in many organisms. CNVs are readily identified using conventional approaches when present in a large fraction of the cell population. However, CNVs that are present in only a few genomes across a population are often overlooked but important; if beneficial under specific conditions, a de novo CNV that arises in a single genome can expand during selection to create a larger population of cells with novel characteristics. While the reach of single cell methods to study de novo CNVs is increasing, we continue to lack information about CNV dynamics in rapidly evolving microbial populations. Here, we investigated de novo CNVs in the genome of the Plasmodium parasite that causes human malaria. The highly AT-rich P. falciparum genome readily accumulates CNVs that facilitate rapid adaptation to new drugs and host environments. We employed a low-input genomics approach optimized for this unique genome as well as specialized computational tools to evaluate the de novo CNV rate both before and after the application of stress. We observed a significant increase in genomewide de novo CNVs following treatment with a replication inhibitor. These stress-induced de novo CNVs encompassed genes that contribute to various cellular pathways and tended to be altered in clinical parasite genomes. This snapshot of CNV dynamics emphasizes the connection between replication stress, DNA repair, and CNV generation in this important microbial pathogen.
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    The Long-term Characterization of Cognitive Phenotypes in Children with Seizures over 36 months
    (Elsevier, 2024) Eisner, Jordan; Harvey, Danielle; Dunn, David; Jones, Jana; Byars, Anna; Fastenau, Philip; Austin, Joan; Hermann, Bruce; Oyegbile-Chidi, Temitayo; Psychiatry, School of Medicine
    Rationale: Children with new-onset epilepsies often exhibit co-morbidities including cognitive dysfunction, which adversely affects academic performance. Application of unsupervised machine learning techniques has demonstrated the presence of discrete cognitive phenotypes at or near the time of diagnosis, but there is limited knowledge of their longitudinal trajectories. Here we investigate longitudinally the presence and progression of cognitive phenotypes and academic status in youth with new-onset seizures as sibling controls. Methods: 282 subjects (6-16 years) were recruited within 6 weeks of their first recognized seizure along with 167 unaffected siblings. Each child underwent a comprehensive neuropsychological assessment at baseline, 18 and 36 months later. Factor analysis of the neuropsychological tests revealed four underlying domains - language, processing speed, executive function, and verbal memory. Latent trajectory analysis of the mean factor scores over 36 months identified clusters with prototypical cognitive trajectories. Results: Three unique phenotypic groups with distinct cognitive trajectories over the 36-month period were identified: Resilient, Average, and Impaired phenotypes. The Resilient phenotype exhibited the highest neuropsychological factor scores and academic performance that were all similar to controls; while the Impaired phenotype showed the polar opposite with the worst performances across all test metrics. These findings remained significant and stable over 36 months. Multivariate logistic regression indicated that age of onset, EEG, neurological examination, and sociodemographic disadvantage were associated with phenotype classification. Conclusions: This study demonstrates the presence of diverse latent cognitive trajectory phenotypes over 36 months in youth with new-onset seizures that are associated with a stable neuropsychological and academic performance longitudinally.