Polyvalan - Crystallophore @teampolyvalan - Twitter Profile

All is intertwined… yet the microbiota pulls the strings Among the consequences elevated triglycerides and/or high cholesterol, sleep disturbances, diabetes, or hypothyroidism? @club_gut #GutMicrobiome #HealthyAging #Microbiota #GutHealth #HealthSpan #Butyrate #Urolithin #SIRT1 #SIRT3

TeamPolyvalan's tweet photo. All is intertwined… yet the microbiota pulls the strings Among the consequences elevated triglycerides and/or high cholesterol, sleep disturbances, diabetes, or hypothyroidism? @club_gut
#GutMicrobiome #HealthyAging #Microbiota #GutHealth #HealthSpan #Butyrate #Urolithin #SIRT1 #SIRT3

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Polyvalan - Crystallophore

@TeamPolyvalan

4 days ago

@carolinacpsj Mitochondria and therefore metabolism are driven by the gut https://t.co/mvychYDTl6

Polyvalan - Crystallophore

@TeamPolyvalan

8 days ago

@questmoosa Health versus diseases: a gut centered causal chain ? https://t.co/iaDwZGuBVD

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TeamPolyvalan retweeted

Daniel Tawfik

@dantawfik

5 days ago

A 500,000-person Nature study just mapped sleep duration against 23 biological aging clocks spanning brain, cardiovascular, metabolic, and immune systems. The pattern is stark: sleeping under 6 hours or over 8 hours accelerates aging across every organ system measured. Here's the consistent pattern the study found: U-shaped associations between sleep duration and biological age gaps across nine organ systems. Both short sleep (less than 6 hours) and long sleep (more than 8 hours) are associated with accelerated biological aging compared to optimal duration. Researchers from Stanford University and their collaborators analyzed UK Biobank data from 500,000 participants aged 37 to 84 years, using generalized additive models to assess nonlinear relationships between self-reported sleep duration and biological age gaps derived from in vivo imaging, plasma proteomics, and metabolomics. Biological age gaps measure the difference between your chronological age and your biological age as estimated by organ-specific aging clocks. A positive age gap means your organs are aging faster than expected. A negative gap means slower aging. The study examined 23 biological aging clocks: 11 derived from plasma proteomics (ProtBAG), 5 from metabolomics (MetBAG), and 7 from magnetic resonance imaging (MRIBAG). Each clock quantifies aging in specific organ systems, from brain to cardiovascular to metabolic. Across all three omics technologies—large-scale “omics” measurements such as genomics (DNA), transcriptomics (RNA), and proteomics/metabolomics (proteins and small molecules) used to profile biological processes, the same U-shaped pattern emerged. The lowest, sample-specific biological age gaps occurred between 6.4 and 7.8 hours of sleep, varying by organ system and sex. That variance somewhat matters because the optimal sleep duration isn't identical across all systems. - Brain aging clocks showed minimum biological age gaps around 7.1 hours for males and 7.3 hours for females. - Cardiovascular aging clocks showed optima around 6.8 hours for males and 7.0 hours for females. The deviations from optimal aren't symmetric. Long sleep duration (8 to 10 hours) showed stronger associations with accelerated aging than short sleep (4 to 6 hours) in several organ systems, particularly cardiovascular and metabolic clocks. Beyond aging clocks, the study examined disease associations. Short and long sleep duration, compared to normal (6 to 8 hours), were associated with increased risk of systemic diseases spanning multiple organ systems: cardiovascular disease, diabetes, depression, and cognitive decline. People vary in how much sleep they naturally tend to get, and genetics plays a role in these differences. This research suggests that the genetic influences behind short sleep and long sleep are not the same. A genome wide association study found different regions of the genome linked to a tendency toward shorter sleep compared with longer sleep, indicating partly separate biological pathways. A follow up analysis using MAGMA, a method that tests whether certain genes are more active in specific tissues, found that genes associated with short sleep are especially enriched in brain tissues. In contrast, genes associated with long sleep show a wider pattern of activity across multiple body systems, suggesting that longer sleep may reflect broader whole body processes rather than primarily brain specific ones. Genetic correlation analysis with 527 disease endpoints from FinnGen and Psychiatric Genomics Consortium revealed that short and long sleep duration patterns share genetic overlap with different disease clusters. Short sleep correlated with metabolic and psychiatric conditions. Long sleep correlated with neurodegenerative and cardiovascular diseases. The survival analysis included 726 disease endpoints. Both short and long sleep duration were associated with higher all-cause mortality compared to 6 to 8 hours, with hazard ratios increasing at the extremes of the distribution. The study then focused on late-life depression (LLD) to examine whether aging clocks mediate the relationship between sleep and disease. The pathways differ by sleep duration pattern. For long sleep duration, biological aging clocks partially mediate the association with LLD. The relationship runs: long sleep → accelerated biological aging → increased depression risk. This suggests that the effects of long sleep on mental health may operate through systemic aging processes. For short sleep duration, the pathway is more direct. Short sleep shows a stronger direct association with LLD that isn't fully mediated by aging clocks. This suggests short sleep may affect depression through acute neurobiological stress pathways rather than through chronic aging acceleration. Mendelian randomization analysis tested whether the relationships are causal. The analysis didn't provide strong evidence that disease causally affects sleep duration, but it can't completely exclude reverse causality. The directionality question remains partially unresolved. The self-reported sleep duration measure is less objective than actigraphy or polysomnography. These modalities capture different aspects of sleep biology and correlate only moderately. However, the large sample size (around 500,000 participants) enables robust identification of nonlinear associations that would be difficult to detect with smaller objective measurement cohorts. The consistency of the U-shaped pattern across imaging, proteomics, and metabolomics suggests the relationship isn't an artifact of a single measurement technology. The biological age gaps derived from molecular profiles reflect systemic changes that converge on similar optimal sleep durations. The sex differences in optimal sleep duration are modest but consistent. Females show slightly longer optimal durations across most organ systems (roughly 0.2 to 0.3 hours longer). The biological basis for this difference isn't fully characterized but may relate to hormonal influences on circadian regulation. The implications for sleep optimization are straightforward: the biological aging minimums occur in the range most public health guidelines already recommend. There's no evidence that optimizing sleep requires precision targeting of specific durations. Staying within the 6 to 8 hour range appears sufficient for most individuals. The long sleep findings are more complex. Excessive sleep duration is associated with worse outcomes, but it's unclear whether long sleep causes aging acceleration or whether underlying health conditions drive both long sleep need and biological aging.