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Cited by 265

The DOI matches its Crossref record; 96 of the 96 references it cites were found in a registry or an index.

SIRT6: Novel Mechanisms and Links to Aging and Disease

Open access
Tasselli, Luisa, Zheng, Wei, Chua, Katrin F.·2017·Trends in Endocrinology & Metabolism

Abstract

SIRT6, a member of the Sirtuin family of NAD+-dependent enzymes, has established roles in chromatin signaling and genome maintenance. Through these functions, SIRT6 protects against aging-associated pathologies including metabolic disease and cancer, and can promote longevity in mice. Research from the last few years has revealed that SIRT6 is a complex enzyme with multiple substrates and catalytic activities, and uncovered novel SIRT6 functions in maintenance of organismal health span. Here, we review these new discoveries and models of SIRT6 biology in four areas: heterochromatin stabilization and silencing, stem cell biology, cancer initiation and progression, and regulation of metabolic homeostasis. We discuss possible implications of these findings for therapeutic interventions in aging and aging-related disease processes.

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Crossref · 10.1016/j.tem.2016.10.002

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Metadata

Authors
Tasselli, L., Zheng, W., & Chua, K. F.
Venue
Trends in Endocrinology & Metabolism
Publisher
Elsevier BV
Published
2017-03
Volume
28
Issue
3
Pages
168-185
ISSN
1043-2760 (ISSN-L)
OpenAlex
W2552184863
Cited by
265
References
96
FWCI
2.43
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: SIRT6: Novel Mechanisms and Links to Aging and Disease. https://app.cochat.ai/papers/10.1016/j.tem.2016.10.002
The paper
Tasselli, L., Zheng, W., & Chua, K. F. (2017). SIRT6: Novel Mechanisms and Links to Aging and Disease. Trends in Endocrinology & Metabolism. https://doi.org/10.1016/j.tem.2016.10.002

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.