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Browsing by Subject "Genome‐wide association"

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    Genetic associations with psychosis and affective disturbance in Alzheimer's disease
    (Wiley, 2024-05-23) Antonsdottir, Inga Margret; Creese, Byron; Klei, Lambertus; DeMichele-Sweet, Mary Ann A.; Weamer, Elise A.; Garcia-Gonzalez, Pablo; Marquie, Marta; Boada, Mercè; Alarcón-Martín, Emilio; Valero, Sergi; NIA-LOAD Family Based Study Consortium; Alzheimer's Disease Genetics Consortium (ADGC); AddNeuroMed Consortium; Liu, Yushi; Hooli, Basavaraj; Aarsland, Dag; Selbaek, Geir; Bergh, Sverre; Rongve, Arvid; Saltvedt, Ingvild; Skjellegrind, Håvard K.; Engdahl, Bo; Andreassen, Ole A.; Borroni, Barbara; Mecocci, Patrizia; Wedatilake, Yehani; Mayeux, Richard; Foroud, Tatiana; Ruiz, Agustín; Lopez, Oscar L.; Kamboh, M. Ilyas; Ballard, Clive; Devlin, Bernie; Lyketsos, Constantine; Sweet, Robert A.; Medical and Molecular Genetics, School of Medicine
    Introduction: Individuals with Alzheimer's disease (AD) commonly experience neuropsychiatric symptoms of psychosis (AD+P) and/or affective disturbance (depression, anxiety, and/or irritability, AD+A). This study's goal was to identify the genetic architecture of AD+P and AD+A, as well as their genetically correlated phenotypes. Methods: Genome-wide association meta-analysis of 9988 AD participants from six source studies with participants characterized for AD+P AD+A, and a joint phenotype (AD+A+P). Results: AD+P and AD+A were genetically correlated. However, AD+P and AD+A diverged in their genetic correlations with psychiatric phenotypes in individuals without AD. AD+P was negatively genetically correlated with bipolar disorder and positively with depressive symptoms. AD+A was positively correlated with anxiety disorder and more strongly correlated than AD+P with depressive symptoms. AD+P and AD+A+P had significant estimated heritability, whereas AD+A did not. Examination of the loci most strongly associated with the three phenotypes revealed overlapping and unique associations. Discussion: AD+P, AD+A, and AD+A+P have both shared and divergent genetic associations pointing to the importance of incorporating genetic insights into future treatment development. Highlights: It has long been known that psychotic and affective symptoms are often comorbid in individuals diagnosed with Alzheimer's disease. Here we examined for the first time the genetic architecture underlying this clinical observation, determining that psychotic and affective phenotypes in Alzheimer's disease are genetically correlated. Nevertheless, psychotic and affective phenotypes in Alzheimer's disease diverged in their genetic correlations with psychiatric phenotypes assessed in individuals without Alzheimer's disease. Psychosis in Alzheimer's disease was negatively genetically correlated with bipolar disorder and positively with depressive symptoms, whereas the affective phenotypes in Alzheimer's disease were positively correlated with anxiety disorder and more strongly correlated than psychosis with depressive symptoms. Psychosis in Alzheimer's disease, and the joint psychotic and affective phenotype, had significant estimated heritability, whereas the affective in AD did not. Examination of the loci most strongly associated with the psychotic, affective, or joint phenotypes revealed overlapping and unique associations.
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    Polytranscriptomic risk score for Alzheimer Disease in a large diverse multi‐center brain bank study
    (Wiley, 2025-01-03) Cieza, Basilio; Yang, Zikun; Reyes-Dumeyer, Dolly; Lee, Annie J.; Dugger, Brittany N.; Jin, Lee-Way; Murray, Melissa E.; Dickson, Dennis W.; Pericak-Vance, Margaret A.; Vance, Jeffery M.; Foroud, Tatiana M.; Mayeux, Richard; Tosto, Giuseppe; Neurology, School of Medicine
    Background: Alzheimer’s disease (AD) missing heritability remains extensive despite numerous genetic risk loci identified by genome‐wide association or sequencing studies. This has been attributed, at least partially, to mechanisms not currently investigated by traditional single‐marker/gene approaches. Polygenic Risk Scores (PRS) aggregate sparse genetic information across the genome to identify individual genetic risk profiles for disease prediction and patient risk stratification. Recent advancements have pivoted on innovative approaches utilizing OMICS data to construct such risk scores. Method: We employed a random forest algorithm to identify a list of gene candidates from bulk RNA sequencing data in prefrontal cortex from 565 AD brain samples (non‐Hispanic Whites, n = 399; Hispanics, n = 113; African American, n = 12) across six U.S. brain banks. Subsequently, we calculated their effect size on Braak staging using regression models to construct a polytranscriptomic risk score (PTRS). We employed two distinct models: “Ethnicity‐Agnostic” Model (randomly assigning samples to training and testing samples) and “Ethnicity‐Aware” Model (assigning NHW samples to training and Hispanics to testing sample). Analysis of variance and the receiver operating characteristics area under the curve (ROC AUC) was used to evaluate PTRS’s classification performances. We validated findings using the Religious Orders Study/Memory and Aging Project study (ROS/MAP, n = 1,095). Result: We found a significant difference in PTRS between samples with low vs. high Braak stages (≤4 vs. ≥5, p = 1*E‐04; Figure 1 upper panel). AUC was found to be 79‐81%, consistently in both Ethnicity‐Agnostic and Ethnicity‐Aware models (Figure 1 lower panel). Finally, the PTRS in ROS/MAP yielded a similar classification performance (p = 2*E‐04, AUC = 77%). Conclusion: Contrary to prior studies, we developed a PTRS with optimal transferability across ethnicities. This underscores the importance of developing novel tools to stratify and harmonize large brain repositories for AD.
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