bims-minfam Biomed News
on Inflammation and metabolism in ageing and cancer
Issue of 2023‒11‒05
ten papers selected by
Ayesh Seneviratne, Western University



  1. Cancer Discov. 2023 Nov 03. OF1
      SRCAP mutations promote clonal expansion of hematopoietic stem cells (HSC) in response to cellular stress.
    DOI:  https://doi.org/10.1158/2159-8290.CD-RW2023-175
  2. Age Ageing. 2023 Oct 28. 52(Supplement_4): iv3-iv5
      
    Keywords:  ageing; health; measurement; older people
    DOI:  https://doi.org/10.1093/ageing/afad118
  3. Chin Med J (Engl). 2023 Oct 27.
      ABSTRACT: Aging is accompanied by significant inhibition of hematopoietic and immune system function and disruption of bone marrow structure. Aging-related alterations in the inflammatory response, immunity, and stem cell niches are at the root of hematopoietic aging. Understanding the molecular mechanisms underlying hematopoietic and bone marrow aging can aid the clinical treatment of aging-related diseases. In particular, it is unknown how the niche reprograms hematopoietic stem cells (HSCs) in an age-dependent manner to maintain normal hematopoiesis in elderly individuals. Recently, specific inhibitors and blood exchange methods have been shown to reshape the hematopoietic niche and reverse hematopoietic aging. Here, we present the latest scientific discoveries related to hematopoietic aging and hematopoietic system rejuvenation, discuss the relationships between hematopoietic niche aging and HSC aging, and describe related studies on stem cell-mediated regulation of hematopoietic aging, aiming to provide new ideas for further study.
    DOI:  https://doi.org/10.1097/CM9.0000000000002871
  4. Trends Cell Biol. 2023 Oct 31. pii: S0962-8924(23)00207-6. [Epub ahead of print]
      Stem cells persist throughout the lifespan to repair and regenerate tissues due to their unique ability to self-renew and differentiate. Here we reflect on the recent discoveries in stem cells that highlight a mitochondrial metabolic checkpoint at the restriction point of the stem cell cycle. Mitochondrial activation supports stem cell proliferation and differentiation by providing energy supply and metabolites as signaling molecules. Concomitant mitochondrial stress can lead to loss of stem cell self-renewal and requires the surveillance of various mitochondrial quality control mechanisms. During aging, a mitochondrial protective program mediated by several sirtuins becomes dysregulated and can be targeted to reverse stem cell aging and tissue degeneration, giving hope for targeting the mitochondrial metabolic checkpoint for treating tissue degenerative diseases.
    Keywords:  NAD; NLRP3; SIRT2; SIRT3; SIRT7; aging
    DOI:  https://doi.org/10.1016/j.tcb.2023.10.003
  5. Expert Opin Ther Targets. 2023 Oct 30. 1-4
      
    Keywords:  Aging; Extracellular Mitochondria; Hallmarks of Aging; Health; Healthy Longevity; Induced Pluripotent Stem Cells (iPSCs); Longevity; Mitochondria; Mitochondrial DNA (mtDNA); Mitochondrial Transfer; Mitochondrial Transplant; Rejuvenation; Senescent Cells; Telomeres
    DOI:  https://doi.org/10.1080/14728222.2023.2277240
  6. BMC Geriatr. 2023 Nov 02. 23(1): 712
      BACKGROUND: Currently, there are few such studies about establishing the frailty prediction model on the basis of the research on the factors influencing frailty in older patients, which can better predict frailty and identify its risk factors, and then guide the formulation of intervention measures precisely, especially in the hospital setting in China. Meanwhile, comprehensive geriatric assessment (CGA) can provide measurable and substantial health improvements for frail older people. The study aimed to develop a nomogram model for frailty risk among hospitalised older people using CGA data and validated its predictive performance for providing a basis for medical staff to grasp the risk and risk factors of older inpatients' frailty conveniently and accurately, and to formulate reasonable nursing intervention plan.METHODS: We used CGA data of individuals over age 64. Demographic characteristics, geriatric syndrome assessment, and frailty assessment based on the FRAIL scale were included as potential predictors. Significant variables in univariate analysis were used to construct risk models by logistic regression analysis. We used the root mean square (rms) to develop the nomogram prediction model for frailty based on independent clinical factors. Nomogram performance was internally validated with Bootstrap resampling. The final model was externally validated using an independent validation data set and was assessed for discrimination and calibration.
    RESULTS: Data from 2226 eligible older inpatients were extracted. Five hundred sixty-two older inpatients (25.25%) suffered from frailty. The final prediction model included damaged skin, MNA-SF, GDS-15, Morse risk scores, hospital admission, ICI-Q-SF, Braden score, MMSE, BI scores, and Caprini scores. The prediction model displayed fair discrimination. The calibration curve demonstrated that the probabilities of frailty predicted by the nomogram were satisfactorily matched.
    CONCLUSIONS: The prediction model to identify hospitalised older people at high risk for frailty using comprehensive geriatric assessment data displayed fair discrimination and good predictive calibration. Therefore, it is inexpensive, easily applied, and accessible in clinical practice, containing variables routinely collected and readily available through consultation. It will be valuable for grasp older inpatients at high risk of frailty and risk factors in hospital setting to guide the formulation of intervention measures precisely for reversing and preventing frailty.
    Keywords:  Comprehensive geriatric assessment; Frailty; Frailty Nomogram prediction model; Frailty prediction; Frailty prevention
    DOI:  https://doi.org/10.1186/s12877-023-04426-8
  7. Cytogenet Genome Res. 2023 Oct 28.
      There is evidence that complex disease and mortality are associated with DNA methylation (DNAm) and age acceleration. Numerous epigenetic clocks, including Horvath, Hannum, DNA PhenoAge, DNA GrimAge, and DunedinPoAm continue to be developed in this young scientific field. The most well-known epigenetic clocks are presented here, along with information about how they relate to chronic disease. We examined all the literature until January 2023, investigating associations between measures of age acceleration and complex and age-related diseases. We focused on the scientific literature and researches that are most strongly associated with epigenetic clocks and that have shown promise as biomarkers for obesity, cardiovascular illness, type 2 diabetes, and neurodegenerative disease. Understanding the complex interactions between accelerated epigenetic clocks and chronic diseases may have significant effects on both the early diagnosis of disease and health promotion. Additionally, there is a lot of interest in developing treatment plans that can delay the onset of illnesses or, at the very least, alter the underlying causes of such disorders.
    DOI:  https://doi.org/10.1159/000534561
  8. Nat Commun. 2023 10 28. 14(1): 6895
      Genomic profiling of hematologic malignancies has augmented our understanding of variants that contribute to disease pathogenesis and supported development of prognostic models that inform disease management in the clinic. Tumor only sequencing assays are limited in their ability to identify definitive somatic variants, which can lead to ambiguity in clinical reporting and patient management. Here, we describe the MSK-IMPACT Heme cohort, a comprehensive data set of somatic alterations from paired tumor and normal DNA using a hybridization capture-based next generation sequencing platform. We highlight patterns of mutations, copy number alterations, and mutation signatures in a broad set of myeloid and lymphoid neoplasms. We also demonstrate the power of appropriate matching to make definitive somatic calls, including in patients who have undergone allogeneic stem cell transplant. We expect that this resource will further spur research into the pathobiology and clinical utility of clinical sequencing for patients with hematologic neoplasms.
    DOI:  https://doi.org/10.1038/s41467-023-42585-9