Steven R Cummings’s research while affiliated with University of California, San Francisco and other places

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Publications (753)


Frequency and methylation status of CpG mutation events
a, Percentage of genome-wide somatic mutations classified as CpG (n = 467,079 mutations) or non-CpG (n = 2,990,796 mutations). Expected percentages were calculated supposing mutation probability to be uniform across the genome (Methods). b, Diagram showing two categories of CpG sites: those where no individual is mutated (nonmutated CpG site, gray) and those where a mutation has occurred in at least one individual (mutated CpG site, red; bottom) and the remaining individuals are nonmutated (blue; top). c, Distribution of CpG methylation values for the categories of CpG sites from b. The methylation fractions of mutated individuals (red) and nonmutated individuals (blue) are shown for the 1,000 CpG sites with the highest MAF (corresponding to MAF > 0.53; Methods). d, Methylation change between mutated and nonmutated individuals at n = 8,037 mutated CpG sites. Methylation change is the difference between the median methylation fraction in mutated individuals and the median methylation fraction in nonmutated individuals of matched age and tissue. CpG sites are binned into five groups based on MAF, with violin plots summarizing the distribution of methylation changes within each group. Vertical bars inside each violin represent the interquartile range. The two-sided P value was calculated based on the exact distribution of Pearson’s r modeled as a beta function. MAF, mutant allele fraction.
Association of mutations with regional methylation patterns
a, Example mutated site where the individual TCGA-GV-A3QI has a C > T mutation at chr16:56,642,556 of the hg19 human genome. Top, ideogram of chromosome 16, with a red bar indicating the location of the mutated site. The first underlying track shows hg19 base-pair coordinates, the second the documented genes in the region (encoding five metallothionein factors) and the third the locations of CpG sites measured on the Illumina 450k methylation array (vertical bars). Bottom, heatmap of CpG methylation fractions. Rows are samples (1 mutated, 28 matched), and columns are the measured CpGs within a ±50-kb window proximal to the mutation (n = 62 CpG sites). Color corresponds to the methylation fraction of each CpG. The mutated sample row and mutated site column are labeled in red, with the mutation event indicated by a lightning bolt. b, Calculation of the change in methylation fraction (ΔMF) with reference to a specific mutated site. Left, heatmap of methylation fractions of the mutated site and CpGs in the surrounding window, replicated from a. Right, heatmap of the corresponding differences in methylation between each sample (row) and all other samples in the matrix (median of other rows), computed separately for each site in the window (columns). The final ΔMF value was calculated as the overall methylation change of the mutated sample, taking the median across all sites in the window (Methods). Matched background samples were defined as those without any somatic mutations in the window and that were of the same tissue type and approximate age (±5 years) as the mutated sample. UCSC, University of California, Santa Cruz.
Magnitude and extent of methylation changes near somatic mutations
a, Absolute ΔMF1 kb as the window center is moved away from the mutated site (n = 2,600, red). This quantity is also shown for nonmutated random control sites (n = 260,000, blue) (Methods). Points indicate the mean value, and error bars denote the 95% confidence interval. A significant difference in the distribution of absolute ΔMF1 kb values (two-sided t test) is marked (***P ≤ 0.001, **P ≤ 0.01). Other comparisons are nonsignificant (NS, P > 0.05). b, Probability distribution of ΔMF10 kb values calculated in a ±10-kb window surrounding mutated (red) versus random control (blue) sites. Mutated sites include n = 2,600 mutated sites with MAF ≥ 0.8, ≥15 matched individuals (individuals of the same tissue type within ±5 years of age) and one or more measured CpGs within the window. Random control sites include n = 260,000 nonmutated sites (Methods). The same was found when controlling for the initial methylation state of mutated and random loci (Extended Data Fig. 3b,c). The P value is shown for a two-sided Mann–Whitney test for a difference in median absolute deviation (MAD) of ΔMF10 kb between the mutated and nonmutated random control loci. c, Line plot depicting the fold enrichment for mutated over nonmutated sites as a function of ΔMF10 kb. Fold enrichment is the ratio of the probability of observing a given ΔMF10 kb for mutated sites versus the probability of that ΔMF10 kb for nonmutated control sites. ΔMF10 kb is divided into equally spaced bins from −0.4 to 0.4. d, Enrichment of extreme ΔMF10 kb values at CpG sites and CpG islands. Top versus bottom bar charts show the 25% of mutations with the most positive versus most negative ΔMF10 kb values in a (n = 650 mutations each). The enrichment of these mutations (bars, y axis) was considered for different types of sites, depending on whether the site is a CpG and/or falls within a CpG island (x-axis categories). Enrichment was compared to the genomic baseline (Methods), with significance determined by a one-sided binomial test. Significant enrichment (P ≤ 0.001) is marked with asterisks (***) and nonsignificant (P > 0.01) with ‘NS’. CpG islands are defined as genomic regions with ≥200 bp, ≥50% GC content and a high CpG occurrence. e, Boxplot of the absolute ΔMF10 kb value as a function of the MAF. The plot includes all mutated sites with ≥15 matched samples and one or more measured CpGs within ±10 kb (n = 3,880 mutated loci). The two-sided P value was calculated based on the exact distribution of Pearson’s r modeled as a beta function. The central line represents the median; the edges of the box represent the interquartile range; the whiskers indicate 1.5 times the interquartile range; and the points represent all ΔMF10 kb values outside these ranges.
Association among mutation age, methylation age and chronological age
a, Methylation clock: the methylation fractions of CpGs are used in a gradient boosted tree model to predict chronological age. Mutation clock: the count of mutations around the same CpGs are used in an identical model to predict chronological age. Both models incorporate similar covariates and whole-genome features (Methods). b, Scatter plot of human individuals, showing age predictions from the mutation model versus their chronological age. The plot includes n = 1,601 individuals with samples from five tissues (Methods). c, Similar to b but showing age predictions from the methylation rather than mutation model for the same individuals. d, Violin plots of the methylation age residual versus the mutation age residual (Methods). The plot includes the same individuals as in b and c. Pearson’s r refers to the correlation between the methylation age residual and the mutation age residual (that is, partial correlation, P = 1.48 × 10⁻⁸², two-sided P value calculated based on the exact distribution of Pearson’s r modeled as a beta function). The central line of the inner boxplot represents the median; the edges of the box represent the interquartile range; and the whiskers represent 1.5 times the interquartile range. e, Distribution of methylation age residuals for the same individuals as in b and c, computed according to each of four previous methylation clocks. ‘This study’ refers to the methylation clock shown in c (Methods). For each clock, the 20% (n = 320) of individuals with the youngest mutation age for their chronological age are shown in a lighter color (low mutation age residual), and the 20% (n = 320) of individuals with the oldest mutation age for their chronological age are shown in a darker color (high mutation age residual). The asterisks (***) indicate a significant (P ≤ 10⁻⁵¹) difference in distribution between the low and high mutation residual age groups, based on a two-sided Mann–Whitney U test. f, Bar plot depicting the ratio of observed versus expected overlap between sets of age-associated CpG sites. For the same individuals and CpG sites as in c, the CpGs with maximal (top 1%, 5% and 10%) Pearson’s correlation between local mutation burden (±10 kb) and age and between methylation fraction and age were chosen. The intersection (overlap) between these sets was compared to the expected intersection assuming random selection (Methods). Significant enrichment based on a two-sided binomial test (P ≤ 10⁻⁵, Bonferroni corrected) is marked with asterisks (***). g, Mean mutation burden (left y axis) or mean methylation fraction (right y axis) plotted versus chronological age (x axis) for CpG site cg19236454. Data were from brain (LGG, low grade-glioma) samples, considering individuals with a nonzero mutation burden (±10 kb) at this site (n = 67). Pearson’s correlation with chronological age: mutation burden = 0.18, methylation = −0.18. Error bars denote the standard error. h, Diagram summarizing the relationships among three measures of age: mutation, methylation and chronological time. The variance explained was calculated as the squared Pearson’s correlation between each pair of measures for the same individuals as in b and c. MAE, mean absolute error.
Somatic mutation as an explanation for epigenetic aging
  • Article
  • Publisher preview available

January 2025

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20 Reads

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2 Citations

Nature Aging

Zane Koch

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Adam Li

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Daniel S. Evans

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[...]

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Trey Ideker

DNA methylation marks have recently been used to build models known as epigenetic clocks, which predict calendar age. As methylation of cytosine promotes C-to-T mutations, we hypothesized that the methylation changes observed with age should reflect the accrual of somatic mutations, and the two should yield analogous aging estimates. In an analysis of multimodal data from 9,331 human individuals, we found that CpG mutations indeed coincide with changes in methylation, not only at the mutated site but with pervasive remodeling of the methylome out to ±10 kilobases. This one-to-many mapping allows mutation-based predictions of age that agree with epigenetic clocks, including which individuals are aging more rapidly or slowly than expected. Moreover, genomic loci where mutations accumulate with age also tend to have methylation patterns that are especially predictive of age. These results suggest a close coupling between the accumulation of sporadic somatic mutations and the widespread changes in methylation observed over the course of life.

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MITOCHONDRIAL ENERGETICS IN SKELETAL MUSCLE ARE ASSOCIATED WITH LEG POWER AND CARDIORESPIRATORY FITNESS IN SOMMA

December 2024

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2 Reads

Innovation in Aging

Mitochondrial energetics are an important property of aging muscle, as generation of energy is pivotal to the execution of muscle contraction. However, its association with functional outcomes, including leg power and cardiorespiratory fitness, is largely understudied. In the Study of Muscle, Mobility and Aging, we collected vastus lateralis biopsies from older adults (n = 879, 70–94 years, 59.2% women). Maximal State 3 respiration (Max OXPHOS) was assessed in permeabilized fiber bundles by high-resolution respirometry. Capacity for maximal adenosine triphosphate production (ATPmax) was measured in vivo by 31 P magnetic resonance spectroscopy. Leg extension power was measured with a Keiser press system, and VO2peak was determined using a standardized cardiopulmonary exercise test. Gender-stratified multivariate linear regression models were adjusted for age, race, technician/site, adiposity, and physical activity with beta coefficients expressed per 1-SD increment in the independent variable. Max OXPHOS was associated with leg power for both women (β = 0.12 Watts/kg, p <.001) and men (β = 0.11 Watts/kg, p <.050). ATPmax was associated with leg power for men (β = 0.09 Watts/kg, p <.05) but was not significant for women (β = 0.03 Watts/kg, p =.11).


RACE DIFFERENCES IN WALK SPEED, CARDIORESPIRATORY FITNESS, AND MUSCLE MITOCHONDRIAL RESPIRATION

December 2024

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3 Reads

Innovation in Aging

Older adults who self-identify as Black have a disproportionately higher incidence of mobility disability. Whether older adults who are Black also have lower fitness and mitochondrial energetics compared to those who are White has not been adequately investigated. The Study of Muscle, Mobility and Aging (SOMMA) examined 879 older adults (≥70 years old), including 116 who self-identified as Black, who could complete a 400m walk within 15 minutes. Mitochondrial respiration (MaxOXPHOS) was measured in permeabilized fibers from biopsies of the vastus lateralis. A cardiopulmonary exercise test assessed maximum oxygen consumption (VO2peak). Education, income, financial resources, race, sex and age were determined by self-report. Propensity score matching was used to match Blacks with Whites with a 1:1 ratio. Black (n=90) and White (n=90) groups were well matched for age, sex, SOMMA multimorbidity index, BMI, muscle mass, physical activity, marital status, educational achievement, and whether financial needs were met (all p>0.05). Despite being well matched, those who identified as Black had a slower 400m walking speed (0.97 vs. 1.03 m/s, p=0.014), lower MaxOXPHOS (50.8 vs. 60.9 (pmol/(s*mg)), p< 0.001), and lower cardiorespiratory fitness (1391 vs 1566 ml/min, p=0.007), when compared to those who identified as White. Multivariate regression showed that VO2peak and MaxOXPHOS, but not socioeconomic factors, attenuated the race difference in 400m walking speed. In conclusion, while the etiology of race differences in mobility is multifactorial, our data indicate that muscle mitochondrial respiration and cardiorespiratory fitness may contribute to slower walking speed of individuals who identify as Black compared to White.


Fig. 1 Forest plot of relative hazards for associations between senescence biomarkers and clinical outcomes, adjusted for age, sex, and race using the lowest quartile as the reference group.
Fig. 1 (continued)
Fig. 2 C-statistics comparing prediction of outcomes by age, sex, and race (ASR), SASP factors alone, and ASR plus SASP factors. SASP factors, selected by lasso regression, for each comparison are described in Supplemental Table S9-S15
Summary of the C-statistics (95% CI) for outcomes with models adjusted for clinical covariates and clinical covariates with serum concentrations of senescence biomarkers
Biomarkers of cellular senescence and major health outcomes in older adults

December 2024

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31 Reads

GeroScience

The geroscience hypothesis proposes that underlying biological processes, such as the accumulation of senescent cells, have deleterious effects on multiple tissues and increase the risk of many chronic conditions with aging. Senescent cells produce heterogenous biomarkers, also called senescence-associated secretory phenotype (SASP). Circulating concentrations of senescence biomarkers may reflect an underlying burden of senescent cells in various tissues. Plasma levels of these proteins have been associated with increased mortality and poorer physical function. The associations of them with the incidence of major age-related conditions including heart failure, cardiovascular disease, stroke, and dementia, have not been studied. We measured 35 senescence biomarkers in baseline plasma samples from 1678 participants aged 70–79 years old in the longitudinal Health ABC cohort study. Clinical outcomes were ascertained and validated over an average 11.5 year follow-up. In models adjusted for age, sex, and race, higher levels of most of senescence biomarkers were associated with increased risk of all-cause mortality, mobility limitation, and heart failure. Several were also associated with an increased risk of coronary heart disease, stroke, and dementia. Very few were associated with the risk of cancer. Proteins that were selected by Lasso regression for each outcome that commonly included GDF15 and IL6, significantly improved the prediction of mortality, mobility limitation, and heart failure compared with age, sex, and race alone. These results indicate that levels of senescence biomarkers predict an increased risk of several age-related clinical outcomes and may identify individuals most likely to benefit from senotherapeutics.


Association of Delayed Denosumab Dosing with Increased Risk of Fractures: A Population-Based Retrospective Study

November 2024

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1 Read

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1 Citation

Endocrinology and Metabolism

Background: Inhibitory effects of denosumab on bone remodeling are reversible and disappear once treatment is discontinued. Herein, we examined whether and to what extent delayed denosumab administration is also associated with fracture risk using nation- wide data. Methods: The study cohort included women aged 45 to 89 years who were started on denosumab for osteoporosis between October 2017 and December 2019 using data from the Korean Health Insurance Review and Assessment service. Participants were stratified according to the time of their subsequent denosumab administration from the last denosumab administration, including those with within 30 days early dosing (ED30), within the planned time of 180-210 days (referent), within 30-90 days of delayed dosing (DD90), within 90-180 days of delayed dosing (DD180), and longer than 181 days of delayed dosing (DD181+). The primary outcome was the incidence of all clinical fractures. Results: A total of 149,199 participants included and 2,323 all clinical fractures (including 1,223 vertebral fractures) occurred. The incidence of all fractures was significantly higher in the DD90 compared to reference group (hazard ratio [HR], 1.2; 95% confidence interval [CI], 1.1 to 1.4). The risk of all fracture was even higher in the longer delayed DD180 group (HR, 1.9; 95% CI, 1.6 to 2.3) and DD181+ group (HR, 1.8; 95% CI, 1.5 to 2.2). Increased risks of fractures with delayed dosing were consistently observed for vertebral fractures. Conclusion: Delayed denosumab dosing, even by 1 to 3 months, was significantly associated with increased fracture risk. Maintaining the correct dosing schedule should be emphasized when starting denosumab.


Sex differences in the association between skeletal muscle energetics and perceived physical fatigability: the Study of Muscle, Mobility and Aging (SOMMA)

October 2024

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22 Reads

GeroScience

Greater perceived physical fatigability and lower skeletal muscle energetics are both predictors of mobility decline. Characterizing associations between muscle energetics and perceived fatigability may provide insight into potential targets to prevent mobility decline. We examined associations of in vivo (maximal ATP production, ATPmax) and ex vivo (maximal carbohydrate supported oxidative phosphorylation [max OXPHOS] and maximal fatty acid supported OXPHOS [max FAO OXPHOS]) measures of mitochondrial energetics with two measures of perceived physical fatigability, Pittsburgh Fatigability Scale (PFS, 0–50, higher = greater) and Rating of Perceived Exertion (RPE Fatigability, 6–20, higher = greater) after a slow treadmill walk. Participants from the Study of Muscle, Mobility and Aging (N = 873) were 76.3 ± 5.0 years old, 59.2% women, and 85.3% White. Higher muscle energetics (both in vivo and ex vivo) were associated with lower perceived physical fatigability, all p < 0.03. When stratified by sex, higher ATPmax was associated with lower PFS Physical for men only; higher max OXPHOS and max FAO OXPHOS were associated with lower RPE Fatigability for both sexes. Higher skeletal muscle energetics were associated with 40–55% lower odds of being in the most (PFS ≥ 25, RPE Fatigability ≥ 12) vs least (PFS 0–4, RPE Fatigability 6–7) severe fatigability strata, all p < 0.03. Being a woman was associated with 2–3 times higher odds of being in the most severe fatigability strata when controlling for ATPmax but not the ex vivo measures (p < 0.05). Better mitochondrial energetics were linked to lower fatigability and less severe fatigability in older adults. Findings imply that improving skeletal muscle energetics may mitigate perceived physical fatigability and prolong healthy aging.


Figure 1. Correlations of recalled pain and movement-evoked pain measures.
Greater recalled pain and movement-evoked pain are associated with longer 400-meter walk and repeat stair climb time: the Study of Muscle, Mobility and Aging

October 2024

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21 Reads

Background. Musculoskeletal pain frequently accompanies the development of mobility disability and falls in old age. To better understand this, we aimed to quantify the impact of different pain measures—recalled pain and movement-evoked pain—on 400-meter walk and stair climb time in older adults participating in the Study of Muscle, Mobility and Aging (SOMMA). Methods. In SOMMA (N=879, age=76.3 ± 5.0 years, 59% women, 84% Non-Hispanic White), participants completed usual pace 400m walk (avg=6.6 ± 1.2 min.) and repeat stair climb tests (avg=26.6 ± 7.2 sec.). Assessments of recalled pain included the Brief Pain Inventory short form (BPI-sf), total lower body pain (lower back, hips, knees, feet/ankles), stiffness (hip or knee), and Neuropathy Total Symptom Score (NTSS-6). Movement-evoked pain was assessed separately before and after the 400m walk and repeat stair climb tasks. Multivariable linear regression modeled the associations of pain with time to complete the tasks, reported as β[95%CI] expressed per SD increment of pain measure or β[95%CI] per pain categories, adjusted for age, sex, race, ethnicity, body mass index, prescription medications, and depressive symptoms. Results. Greater degree of any pain measure was associated with longer physical performance time, though intercorrelations between recalled pain measures varied (r=0.13-0.57, p<0.05 for all). For each SD increment in lower body pain, participants had longer walk time (by 10.5 sec [6.1, 14.8]) and stair climb (by 0.6 sec [0.1, 1.1]). Compared to participants with no change in pain upon movement, walk time was longer in those with more pain upon movement (19.5 sec [10.3, 28.7]) (p<0.001) but not those with less pain upon movement; stair climb showed similar patterns. Conclusions. Recalled and movement-evoked pain measures were weakly correlated with one another but similarly associated with time to complete 400m walk and stair climb tests. Different pain assessments capture different functional domains of pain but have similar associations with physical performance in these older adults.





Citations (51)


... economy [3][4][5][6][7][8][9] but also by the geographical environment 10,11 . The geographical environment is comprised of a multitude of interacting components, including rock, soil, water, atmosphere and biological elements. ...

Reference:

Understanding the coupled relationship between regional longevity and physical geographical environment in Hechi, Guangxi, China
Biomarkers of aging for the identification and evaluation of longevity interventions
  • Citing Article
  • August 2023

Cell

... A 1-month delay of DNB must be authorized by the bone specialist. Indeed, patients cannot always accurately report the date of the last DNB injection, and while a delay of up to 30 days does not expose the patient to an increased risk of fracture, a delay of even a few days longer significantly increased fractures risk, especially in patients who have been taking DNB for longer and who typically develop a greater rebound [92,93]. Communication between the bone specialist (i.e., drug prescriber) and oral and maxillofacial surgeons is essential to protect patients from the risk of severe rebound-associated vertebral fractures (RAVFs) and ensure the achievement of optimal treatment outcomes [55,94]. ...

Association of Delayed Denosumab Dosing with Increased Risk of Fractures: A Population-Based Retrospective Study
  • Citing Article
  • November 2024

Endocrinology and Metabolism

... Interestingly, prior research on epigenetic effects of early childhood positive parenting interventions has shown divergent findings for these two distinct epigenetic aging outcomes. (Gladyshev et al., 2024), the most relevant health-related outcomes for benchmarking aging biomarkers (Herzog et al., 2024), and the limited attention on biological aging during childhood and adolescence (Raffington, 2024). ...

Challenges and recommendations for the translation of biomarkers of aging
  • Citing Article
  • September 2024

Nature Aging

... De cara a su abordaje, en las guías internacionales revisadas en los últimos 15 años se han ido perfilando herramientas de evaluación del riesgo absoluto de fractura, estratificando los pacientes con relación a la presencia de fractura previa, especialmente si esta ha ocurrido en los dos años previos (lo que se conoce como riesgo inminente de fractura) 6 ; y su densidad mineral ósea (DMO). Identificando a los pacientes como de riesgo moderado, alto o muy alto riesgo, de presentar una nueva fractura 7 . ...

Goal-directed osteoporosis treatment: ASBMR/BHOF task force position statement 2024
  • Citing Article
  • July 2024

Journal of bone and mineral research: the official journal of the American Society for Bone and Mineral Research

... Notably, we did not find a direct relationship between microheteroplasmies and dementia risk which was in line with previous data that heteroplasmies were not associated with brain pathologies [11]. One recent study examines mtDNA variation and cognitive function, but it is limited to 16 mitochondrial-related regions [30]. Future studies are warranted to examine whether specific allelic mutations in mtDNA are implicated in the development of all-cause dementia and subtypes. ...

Joint and Individual Mitochondrial DNA Variation and Cognitive Outcomes in Black and White Older Adults
  • Citing Article
  • July 2024

The Journals of Gerontology Series A Biological Sciences and Medical Sciences

... To maintain balance and minimize the deleterious effects of oxidative stress (e.g., on proteins, lipids, DNA), free radicals are readily scavenged by the enzymatic and non-enzymatic antioxidants. Further, production and antioxidant capacity are seemingly dependent on many factors including mitochondrial capacity, physical fitness, and even exercise performance 34 . When it comes to exercise training, it has been well documented that chronic participation in exercise decreases blood and tissue oxidative stress, seemingly by increasing the efficiency of the antioxidant system(s) 35,36 . ...

Expression of mitochondrial oxidative stress response genes in muscle is associated with mitochondrial respiration, physical performance, and muscle mass in the Study of Muscle, Mobility, and Aging

... Other cross-sectional research studying correlations between physical function tests and the muscle transcriptome also report differential correlations between gene expression and specific types of physical function tests (e.g. walking speed and leg power) [61,62]. This observation suggests muscle biomarkers can reflect specific muscle functions. ...

Higher expression of denervation‐responsive genes is negatively associated with muscle volume and performance traits in the study of muscle, mobility, and aging (SOMMA)

... Importantly, these incentives may come from opportunities for career advancement, financial compensation or providing protected time for intensivists to conduct research. By implementing this culture, we may come closer to the ideal scenario of clinical research more closely embedded within clinical practice, (6) which would benefit the healthcare system. We may also provide a potential solution to the increasing prevalence of burnout among intensivists, as clinical research is a nonclinical activity that may bring meaning and joy for intensivists who are enthusiastic about research. ...

The Integration of Clinical Trials With the Practice of Medicine: Repairing a House Divided
  • Citing Article
  • June 2024

JAMA The Journal of the American Medical Association

... Due to proximity to the muscle fiber, muscle adiposity may impact local muscle metabolism as well as systemic metabolism by impairment of myokine secretion and/or by increased production of pro-inflammatory adipokines and with increased macrophage invasion in the muscle. 36,37 Mitochondrial dysfunction has been previously linked to greater myosteatosis 38 and could also play a role in cognitive decline for individuals with higher amounts of myosteatosis. Thus, in addition to impaired glucose and insulin resistance, increased secretion of pro-inflammatory myokines and adipokines and poor mitochondrial function could be additional mechanisms underlying an association of greater myosteatosis and cognitive decline, but further study is needed. ...

Associations between regional adipose tissue distribution and skeletal muscle bioenergetics in older men and women
  • Citing Article
  • May 2024

Obesity

... The shape of these domains is controlled by mitochondrial fusion and fission. An RNA sequencing of muscle from participants in the Study of Muscle, Mobility, and Aging found that dynamics-related genes (DNM1L, OPA1) are positively correlated with peak VO2, maximal OXPHOS, and 400-meter walking speed, and revealed a potential relationship between kinetics and skeletal muscle oxidation levels [118]. These suggest that mitochondrial dynamics may regulate the distribution of mitochondria in skeletal muscle to correspond to the body's need for energy supply. ...

Autophagy gene expression in skeletal muscle of older individuals is associated with physical performance, muscle volume and mitochondrial function in the study of muscle, mobility and aging (SOMMA)