Tests for genetic heterogeneity among 18 families with Alzheimer's disease

Neurology ◽  
1987 ◽  
Vol 37 (10) ◽  
pp. 1678-1678
Author(s):  
M. L. Marazita ◽  
M. A. Spence ◽  
A. Heyman
2017 ◽  
Vol 381 ◽  
pp. 771
Author(s):  
Y.S. Peng ◽  
H. Chang ◽  
C.W. Tang ◽  
Y.Y. Peng ◽  
Y.H. Tein ◽  
...  

GeroScience ◽  
2019 ◽  
Vol 41 (2) ◽  
pp. 137-154 ◽  
Author(s):  
Alireza Nazarian ◽  
Konstantin G. Arbeev ◽  
Arseniy P. Yashkin ◽  
Alexander M. Kulminski

Genome ◽  
1989 ◽  
Vol 31 (1) ◽  
pp. 390-397 ◽  
Author(s):  
George M. Martin

While it is important to search for unifying mechanisms of aging among a variety of model systems, evolutionary arguments suggest that the pathophysiological details of senescence may be, to some extent, species specific. Moreover, in species that are characterized by extensive genetic heterogeneity, such as our own, one is likely to find kindreds with both "private" and "public" markers of aging. Crude estimates of the number of loci with the potential to modulate aspects of the senescent phenotype of man suggest that thousands of genes could be involved. No single locus appears to modulate all features. Some affect predominately a single aspect ("unimodal progeroid syndromes"); familial Alzheimer's disease is discussed as a prototype. Linkage studies indicate genetic heterogeneity for autosomal dominant forms of the disease. Some loci affect multiple aspects of the phenotype ("segmental progeroid disorders"); the prototype is Werner's syndrome, an autosomal recessive. Cells from homozygotes behave like mutator strains and undergo accelerated senescence in vitro. Elucidation of the biochemical genetic basis of such abiotrophic disorders may shed light on specific aging processes in man.Key words: Homo sapiens, senescence, progeroid syndromes, Alzheimer's disease, linkage, Werner's syndrome, mutator strains.


2019 ◽  
Vol 84 ◽  
pp. 243.e1-243.e9 ◽  
Author(s):  
Min-Tzu Lo ◽  
Karolina Kauppi ◽  
Chun-Chieh Fan ◽  
Nilotpal Sanyal ◽  
Emilie T. Reas ◽  
...  

2020 ◽  
Author(s):  
Jorge J. Llibre‐Guerra ◽  
Yan Li ◽  
Ricardo F. Allegri ◽  
Patricio Chrem Mendez ◽  
Ezequiel I. Surace ◽  
...  

2020 ◽  
Author(s):  
Sharlee Climer ◽  
Alan R. Templeton ◽  
Michael Garvin ◽  
Daniel Jacobson ◽  
Matthew Lane ◽  
...  

AbstractIt is becoming increasingly evident that the efficacy of single-gene computational analyses for complex traits is nearly exhausted and future advances hinge on unraveling the intricate combinatorial interactions among multiple genes. However, the discovery of modules of genes working in concert to manifest a complex trait has been crippled by combinatorial complexity, genetic heterogeneity, and validation biases. We introduce Maestro, a novel network approach that employs a multifaceted correlation measure, which captures heterogeneity, and a rigorous validation method. Maestro’s utilization for Alzheimer’s disease (AD) reveals an expression pattern that has virtually zero probability of simultaneous expression by an individual, assuming independence. Yet this pattern is exhibited by 19.0% of AD cases and 7.3% of controls, establishing an unprecedented pattern of synchronized genetic activities in the human brain. This pattern is significantly associated with AD, with an odds ratio of 3.0. This study substantiates Maestro’s power for discovery of orchestrated genetic activities underlying complex traits. More generally, Maestro can be applied in diverse domains in which heterogeneity exists.HighlightsSynchronized genetic activities associated with Alzheimer’s diseaseNovel vector-based correlation measure that captures genetic heterogeneityEnhanced network model for revealing combinatorial genetic interactionsPro-survival genetic activities associated with Alzheimer’s diseaseGeneral approach for revealing patterns in data subject to heterogeneity


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