Identification and genomic analysis of pedigrees with exceptional longevity identifies candidate rare variants

Miller, Justin; Ward, Elizabeth; Staley, Lyndsay A.; Stevens, Jeffrey C.; Teerlink, Craig C.; Tavana, J.; Cloward, Matthew; Page, Madeline; Dayton, Louisa; Cannon-Albright, Lisa; Kauwe, John S. K.

doi:10.1016/j.nbd.2020.104972

Cited by 7 publications

(5 citation statements)

References 81 publications

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“…As noted above, when using erythrocytes as source material, several groups have demonstrated that the genetic signature of long-lived birds shows an enrichment of genes involved in stress defense mechanisms, cell growth and proliferation, and immune function. This agrees generally with data now available from other species with exceptional longevity [135,136], and from studies of long-versus short-lived individuals within species, including humans [137][138][139][140][141]. Genomic profiling has also proven to be a robust predictor of human aging [142].…”

Section: Avian Genomicssupporting

confidence: 88%

New Perspectives on Avian Models for Studies of Basic Aging Processes

Harper

Holmes

2021

Biomedicines

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Avian models have the potential to elucidate basic cellular and molecular mechanisms underlying the slow aging rates and exceptional longevity typical of this group of vertebrates. To date, most studies of avian aging have focused on relatively few of the phenomena now thought to be intrinsic to the aging process, but primarily on responses to oxidative stress and telomere dynamics. But a variety of whole-animal and cell-based approaches to avian aging and stress resistance have been developed—especially the use of primary cell lines and isolated erythrocytes—which permit other processes to be investigated. In this review, we highlight newer studies using these approaches. We also discuss recent research on age-related changes in neural function in birds in the context of sensory changes relevant to homing and navigation, as well as the maintenance of song. More recently, with the advent of “-omic” methodologies, including whole-genome studies, new approaches have gained momentum for investigating the mechanistic basis of aging in birds. Overall, current research suggests that birds exhibit an enhanced resistance to the detrimental effects of oxidative damage and maintain higher than expected levels of cellular function as they age. There is also evidence that genetic signatures associated with cellular defenses, as well as metabolic and immune function, are enhanced in birds but data are still lacking relative to that available from more conventional model organisms. We are optimistic that continued development of avian models in geroscience, especially under controlled laboratory conditions, will provide novel insights into the exceptional longevity of this animal taxon.

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Section: Avian Genomicssupporting

confidence: 88%

New Perspectives on Avian Models for Studies of Basic Aging Processes

Harper

Holmes

2021

Biomedicines

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“…RABEP1 was key for differentiating Control (upregulated) from AD or AsymAD (downregulated). RABEP1 is tied to longevity and AD [ 23 ]. C4A was key for differentiating AsymAD (downregulated) from AD (upregulated) or Control.…”

Section: Discussionmentioning

confidence: 99%

Machine Learning Selection of Most Predictive Brain Proteins Suggests Role of Sugar Metabolism in Alzheimer’s Disease

Tandon

Levey

Lah

et al. 2023

JAD

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Background: The complex and not yet fully understood etiology of Alzheimer’s disease (AD) shows important proteopathic signs which are unlikely to be linked to a single protein. However, protein subsets from deep proteomic datasets can be useful in stratifying patient risk, identifying stage dependent disease markers, and suggesting possible disease mechanisms. Objective: The objective was to identify protein subsets that best classify subjects into control, asymptomatic Alzheimer’s disease (AsymAD), and AD. Methods: Data comprised 6 cohorts; 620 subjects; 3,334 proteins. Brain tissue-derived predictive protein subsets for classifying AD, AsymAD, or control were identified and validated with label-free quantification and machine learning. Results: A 29-protein subset accurately classified AD (AUC = 0.94). However, an 88-protein subset best predicted AsymAD (AUC = 0.85) or Control (AUC = 0.89) from AD (AUC = 0.96). AD versus Control: APP, DHX15, NRXN1, PBXIP1, RABEP1, STOM, and VGF. AD versus AsymAD: ALDH1A1, BDH2, C4A, FABP7, GABBR2, GNAI3, PBXIP1, and PKAR1B. AsymAD versus Control: APP, C4A, DMXL1, EXOC2, PITPNB, REBEP1, and VGF. Additional predictors: DNAJA3, PTBP2, SLC30A9, VAT1L, CROCC, PNP, SNCB, PRKAR1B, ENPP6, HAPLN2, PSMD4, and CMAS. Conclusion: Biomarkers were dynamically separable across disease stages. Predictive proteins were significantly enriched to sugar metabolism.

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“…Extensive linked genealogic and disease registries existing in Utah have been used to identify and study thousands of Utah high-risk pedigrees [ 37 ]. We have previously used this same sequencing approach in affected cousins belonging to high-risk pedigrees to identify multiple candidate predisposition variants for several different phenotypes, including GOLM1 for melanoma [ 38 ], ERF for bladder cancer [ 36 ], FANCM for colorectal cancer [ 39 ], MEGF for osteoporosis [ 40 ], HOXC4 for Chiari Malformations [ 41 ], and multiple candidates for Alzheimer’s [ 42 ] and exceptional longevity [ 43 ], among others.…”

Section: Discussionmentioning

confidence: 99%

High-Risk Pedigree Study Identifies LRBA (rs62346982) as a Likely Predisposition Variant for Prostate Cancer

Cannon‐Albright

Stevens

Facelli

et al. 2023

Cancers

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There is evidence for contribution of inherited factors to prostate cancer, and more specifically to lethal prostate cancer, but few responsible genes/variants have been identified. We examined genetic sequence data for 51 affected cousin pairs who each died from prostate cancer and who were members of high-risk prostate cancer pedigrees in order to identify rare variants shared by the cousins as candidate predisposition variants. Candidate variants were tested for association with prostate cancer risk in UK Biobank data. Candidate variants were also assayed in 1195 additional sampled Utah prostate cancer cases. We used 3D protein structure prediction methods to analyze structural changes and provide insights into mechanisms of pathogenicity. Almost 4000 rare (<0.005) variants were identified as shared in the 51 affected cousin pairs. One candidate variant was also significantly associated with prostate cancer risk among the 840 variants with data in UK Biobank, in the gene LRBA (p = 3.2 × 10−5; OR = 2.09). The rare risk variant in LRBA was observed to segregate in five pedigrees. The overall predicted structures of the mutant protein do not show any significant overall changes upon mutation, but the mutated structure loses a helical structure for the two residues after the mutation. This unique analysis of closely related individuals with lethal prostate cancer, who were members of high-risk prostate cancer pedigrees, has identified a strong set of candidate predisposition variants which should be pursued in independent studies. Validation data for a subset of the candidates identified are presented, with strong evidence for a rare variant in LRBA.

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Identification and genomic analysis of pedigrees with exceptional longevity identifies candidate rare variants

Cited by 7 publications

References 81 publications

New Perspectives on Avian Models for Studies of Basic Aging Processes

New Perspectives on Avian Models for Studies of Basic Aging Processes

Machine Learning Selection of Most Predictive Brain Proteins Suggests Role of Sugar Metabolism in Alzheimer’s Disease

High-Risk Pedigree Study Identifies LRBA (rs62346982) as a Likely Predisposition Variant for Prostate Cancer

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