The circadian rhythm: A key variable in aging? DOI Creative Commons
Patrick R. Winterhalter, Adrian‐Iustin Georgevici, Nitin Gharpure

и другие.

Aging Cell, Год журнала: 2024, Номер 23(11)

Опубликована: Июль 30, 2024

Abstract The determination of age‐related transcriptional changes may contribute to the understanding health and life expectancy. broad application results from age cohorts have limitations. Altering sample sizes per time point or sex, using a single mouse strain tissue, limited number replicates, omitting middle can bias surveys. To achieve higher general validity identify less distinctive players, bulk RNA sequencing cohort, including seven organs two strains both sexes 5 ages, was performed. Machine learning by bootstrapped variable importance selection methodology (Boruta) used common aging features where circadian rhythms (CiR) transcripts appear as promising markers in an unsupervised analysis. Pathways 11 numerically analyzed local network clusters were affected classified into four major gene expression profiles, whereby CiR proteostasis candidates particularly conspicuous with partially opposing changes. In data‐based interaction association network, CiR‐proteostasis axis occupies exposed central position, highlighting its relevance. computation 11,830 individual transcript associations provides potential superordinate contributors, such hormones, changes, CiR. hormone‐sensitive LNCaP cells, short‐term supraphysiologic levels sex hormones dihydrotestosterone estradiol increase Bhlhe40 associated senescence regulator Cdkn2b (p15). According these findings, bilateral dysregulation appears fundamental protagonist aging, whose could serve biological marker restoration therapeutic opportunity.

Язык: Английский

The circadian rhythm: A key variable in aging? DOI Creative Commons
Patrick R. Winterhalter, Adrian‐Iustin Georgevici, Nitin Gharpure

и другие.

Aging Cell, Год журнала: 2024, Номер 23(11)

Опубликована: Июль 30, 2024

Abstract The determination of age‐related transcriptional changes may contribute to the understanding health and life expectancy. broad application results from age cohorts have limitations. Altering sample sizes per time point or sex, using a single mouse strain tissue, limited number replicates, omitting middle can bias surveys. To achieve higher general validity identify less distinctive players, bulk RNA sequencing cohort, including seven organs two strains both sexes 5 ages, was performed. Machine learning by bootstrapped variable importance selection methodology (Boruta) used common aging features where circadian rhythms (CiR) transcripts appear as promising markers in an unsupervised analysis. Pathways 11 numerically analyzed local network clusters were affected classified into four major gene expression profiles, whereby CiR proteostasis candidates particularly conspicuous with partially opposing changes. In data‐based interaction association network, CiR‐proteostasis axis occupies exposed central position, highlighting its relevance. computation 11,830 individual transcript associations provides potential superordinate contributors, such hormones, changes, CiR. hormone‐sensitive LNCaP cells, short‐term supraphysiologic levels sex hormones dihydrotestosterone estradiol increase Bhlhe40 associated senescence regulator Cdkn2b (p15). According these findings, bilateral dysregulation appears fundamental protagonist aging, whose could serve biological marker restoration therapeutic opportunity.

Язык: Английский

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