Sex differences in the genetic architecture of cognitive resilience to Alzheimer\u27s disease

Approximately 30% of elderly adults are cognitively unimpaired at time of death despite the presence of Alzheimer\u27s disease neuropathology at autopsy. Studying individuals who are resilient to the cognitive consequences of Alzheimer\u27s disease neuropathology may uncover novel therapeutic targets to treat Alzheimer\u27s disease. It is well established that there are sex differences in response to Alzheimer\u27s disease pathology, and growing evidence suggests that genetic factors may contribute to these differences. Taken together, we sought to elucidate sex-specific genetic drivers of resilience. We extended our recent large scale genomic analysis of resilience in which we harmonized cognitive data across four cohorts of cognitive ageing, in vivo amyloid PET across two cohorts, and autopsy measures of amyloid neuritic plaque burden across two cohorts. These data were leveraged to build robust, continuous resilience phenotypes. With these phenotypes, we performed sex-stratified [n (males) = 2093, n (females) = 2931] and sex-interaction [n (both sexes) = 5024] genome-wide association studies (GWAS), gene and pathway-based tests, and genetic correlation analyses to clarify the variants, genes and molecular pathways that relate to resilience in a sex-specific manner. Estimated among cognitively normal individuals of both sexes, resilience was 20-25% heritable, and when estimated in either sex among cognitively normal individuals, resilience was 15-44% heritable. In our GWAS, we identified a female-specific locus on chromosome 10 [rs827389, β (females) = 0.08, P (females) = 5.76 × 10-09, β (males) = -0.01, P(males) = 0.70, β (interaction) = 0.09, P (interaction) = 1.01 × 10-04] in which the minor allele was associated with higher resilience scores among females. This locus is located within chromatin loops that interact with promoters of genes involved in RNA processing, including GATA3. Finally, our genetic correlation analyses revealed shared genetic architecture between resilience phenotypes and other complex traits, including a female-specific association with frontotemporal dementia and male-specific associations with heart rate variability traits. We also observed opposing associations between sexes for multiple sclerosis, such that more resilient females had a lower genetic susceptibility to multiple sclerosis, and more resilient males had a higher genetic susceptibility to multiple sclerosis. Overall, we identified sex differences in the genetic architecture of resilience, identified a female-specific resilience locus and highlighted numerous sex-specific molecular pathways that may underly resilience to Alzheimer\u27s disease pathology. This study illustrates the need to conduct sex-aware genomic analyses to identify novel targets that are unidentified in sex-agnostic models. Our findings support the theory that the most successful treatment for an individual with Alzheimer\u27s disease may be personalized based on their biological sex and genetic context

Novel genetic risk factor for Alzheimer's disease progression [abstract]

Researchers at Washington University have identified a novel genetic variant that strongly correlates with disease progression. Dr. Alison Goate and collaborators used an established biomarker for the decline of AD patients (cerebrospinal fluid tau phosphorylated at threonine 181, ptau181) to find genetic variants that influence levels of ptau181 in the cerebrospinal fluid. The study found a highly significant association between ptau181levels and the rs1868402 SNP located within a regulatory subunit of PPP3R1 (calcineurin B), a gene previously linked to AD pathogenesis. Carriers of the rs1868402 risk allele showed a 6-fold faster rate of disease progression than AD patients without the variant. In addition, individuals carrying allele rs1868402 and rs3785883, a second allele identified in the study, showed an even more pronounced rate of decline. Direct examination of brain samples from AD cases and controls revealed that rs1868402is in fact associated with reduced PPP3R1 mRNA levels and increased tangle formation, providing biological validation for the genome-wide association study and further implicating PPP3R1 in disease pathology. rs1868402 showed no association with risk for AD or age at onset, but there was a very significant association with rate of progression of disease that is consistent in two independent series. As the first genetic variant associated with rate of AD progression to be reported, its use in clinical trial design and patient care will translate into a significant benefit to patients. Potential Areas of Applications: * Diagnostic for individuals with rapid decline in Alzheimer's disease * New protein pathway for drug therapies for treating Alzheimer's disease progression Patent Status: Patent pending Inventor(s): Carlos Cruchaga, Alison Goate, David Holtzman Contact Info: Nichole Mercier, [email protected] (314) 747 190

Aplicaciones de Mecánica Computacional en la industria sidero-metalúrgica

En el presente trabajo se presentan aplicaciones de Mecánica Computacional en el ámbito de la industria sidero metalúrgica . Las aplicaciones que se presentan pueden ser divididas en : análisis de procesos de fabricación y análisis de la performance en servicio de productos siderúrgicos. En el primer caso el objetivo del modelado computacional es la optimización de procesos productivos y, en el segundo caso, el objetivo es la evaluación de la prestación que puede esperarse de diversos productos siderúrgicos, en particular se ha analizado la performance de tubos de acero sin costura para aplicaciones petroleras.Peer Reviewe

Aplicaciones de Mecánica Computacional en la industria sidero-metalúrgica

En el presente trabajo se presentan aplicaciones de Mecánica Computacional en el ámbito de la industria sidero metalúrgica . Las aplicaciones que se presentan pueden ser divididas en : análisis de procesos de fabricación y análisis de la performance en servicio de productos siderúrgicos. En el primer caso el objetivo del modelado computacional es la optimización de procesos productivos y, en el segundo caso, el objetivo es la evaluación de la prestación que puede esperarse de diversos productos siderúrgicos, en particular se ha analizado la performance de tubos de acero sin costura para aplicaciones petroleras.Peer Reviewe