Biology subjects

Kraus, W.

Publications and source records attributed to Kraus, W..

6 recordsLinked to original sources

bioRxiv2026

Regulation of Small RNAs by Exercise and Their Role in Insulin Sensitivity

We investigated effects of three aerobic exercise interventions, varying in amount and intensity with durations of 8-9-months on small RNA (smRNA) expression and regulatory pathways in skeletal muscle and plasma from 120 participants. Using untargeted smRNA sequencing focused on miRNAs and piRNAs, adjusting for demographics and bodyweight, we identified 124 muscle smRNAs altered by exercise amount and 15 by intensity, and 47 plasma smRNAs altered by intensity and one by amount. These smRNAs were enriched in metabolic, transcriptional, translational, and cell cycle pathways. Exercise-induced changes in several smRNAs-six from muscle and five from plasma-and exercise-induced reduction in body weight, aligned with improvement in insulin sensitivity (p<0.05). These findings demonstrate tissue-specific regulation of smRNAs by exercise and identify potential candidates for exercise mimetics to modulate muscle insulin sensitivity.

physiology↗

bioRxiv2026

Biological Mechanisms of Strength Preservation During Calorie Restriction-Induced Weight Loss Among Young- to Middle-Aged Adults without Obesity

PurposeWeight loss is often pursued to improve cardiometabolic health and quality of life. However, rapid weight loss can lead to reductions in lean soft tissue mass and strength to compromise body composition and functional ability. Thus, identifying molecular predictors of muscular strength preservation during weight loss is critical to mitigating these effects. MethodsWe conducted a secondary analysis of the CALERIETM (Comprehensive Assessment of Long-term Effects of Reducing Intake of Energy) trial, a two-year randomized controlled study of caloric restriction (CR) or ad-libitum intake in healthy adults without obesity. Among 198 participants, changes in whole-body mass and knee extensor strength were assessed over the first 12 months of the study which was primarily characterized by weight loss. Transcriptomic profiling was conducted in a subset of 42 participants who provided skeletal muscle samples. Linear regression was used to model the relationship between strength change and gene expression change, while controlling for changes in whole-body mass. Gene set enrichment analysis (GSEA) was performed using Hallmark pathways. Individual-level pathway analysis was performed via gene set variation analysis (GSVA). ResultsWe identified 96 out of 198 individuals (48.5%) who maintained or improved strength relative to body mass during weight loss (i.e. individuals with residuals > 0). Transcriptomics analysis on a subset of 42 individuals revealed 151 genes significantly associated with change in strength after accounting for change in whole-body mass (p < 0.01). Hub genes were identified as HSP90AA1 ({beta} = 34.45, SE = 7.32, p <0.001), EIF3A ({beta} = 36.14, SE = 10.27, p < 0.001), EIF5B ({beta} = 49.94, SE = 11.28, p < 0.001), and H3C1 ({beta} = -15.87, SE = 4.85, p < 0.001). GSEA revealed significant involvement of pathways related to cellular proliferation, immune regulation, protein secretion, and checkpoint control processes. GSVA identified a similar set of pathways. ConclusionsThese findings highlight molecular pathways supporting strength retention during CR-induced weight loss. Heat-shock protein, HSP90AA1, warrants further investigation as a candidate target for preserving muscle strength during interventions aimed at weight reduction.

molecular biology↗

bioRxiv2025

Temporal Multi-Omic Analysis Uncovers Sex-Biased Molecular Programs Underlying Skeletal Muscle Adaptation to Endurance Training

BackgroundExercise training is known to benefit health and reduce disease risk. While skeletal muscle adaptations are fundamental to many of the health benefits of exercise training, the common and sex-specific molecular regulators that mediate these adaptations remain to be fully elucidated. MethodsTo this end, we leveraged skeletal muscle multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), where 6 month-old male and female rats endurance trained for 1, 2, 4, or 8 weeks. Our objective was to identify shared and sex-specific multi-omic molecular responses to endurance training in skeletal muscle, and relate them to phenotypic adaptations. ResultsWe identified largely sexually-conserved transcriptomic and proteomic pathway enrichments in the gastrocnemius, which correlated with skeletal muscle responses from a published exercise study in humans. We uncovered sex-consistent post-translational modifications, including decreased oxidation of MYH2 and deacetylation of the {beta}-oxidation enzyme HADHA. Pathway enrichment analyses revealed sex-specific remodeling across the acetylome, redox proteome, and phosphoproteome; females decreased mitochondrial protein cysteine oxidation and increased mitochondrial cristae proteins, indicative of enhanced redox buffering and mitochondrial efficiency. Despite decreases in cysteine oxidation of key mitochondrial proteins, females displayed increases in the cysteine oxidation of proteins involved in glucose catabolism relative to males after 8 weeks of training, suggestive of sex-biased subcellular reactive oxygen species generation. Males demonstrated earlier induction of mitochondrial transcripts and predicted activation of mTOR. Although the increase in mitochondrial protein abundance was more modest in males, there was greater oxidation of mitochondrial proteins in response to training compared to females. ConclusionsThis work shows a large portion of the adaptive response to endurance training in skeletal muscle is shared between females and males, while there are distinct and nuanced sex-specific adaptations that are evident, particularly at the level of post-translational regulation.

physiology↗

bioRxiv2024

The CALERIE™ Genomic Data Resource

Caloric restriction (CR) slows biological aging and prolongs healthy lifespan in model organisms. Findings from CALERIE-2 - the first ever randomized, controlled trial of long-term CR in healthy, non-obese humans - broadly supports a similar pattern of effects in humans. To expand our understanding of the molecular pathways and biological processes underpinning CR effects in humans, we generated a series of genomic datasets from stored biospecimens collected from n=218 participants during the trial. These data constitute the first publicly-accessible genomic data resource for a randomized controlled trial of an intervention targeting the biology of aging. Datasets include whole-genome SNP genotypes, and three-timepoint-longitudinal DNA methylation, mRNA, and small RNA datasets generated from blood, skeletal muscle, and adipose tissue samples (total sample n=2327). The CALERIE Genomic Data Resource described in this article is available from the Aging Research Biobank. This multi-tissue, multi-omic, longitudinal data resource has great potential to advance translational geroscience.

genomics↗

bioRxiv2024

Synchronization of Human Circadian Genes Between in vivo and Cultured Blood Samples

Transcriptomic studies of human circadian rhythm are limited in efficacy by the invasiveness of sampling. Studies of circadian dynamics should ideally use multiple blood samples drawn at regular intervals over the course of a day. This is difficult to achieve, particularly at night, without disrupting the very circadian rhythm that is being studied. We propose a method by which blood is drawn at a single initial timepoint, then cultured and repeatedly sampled over the course of a day. This method is minimally invasive to the subject. Our results demonstrate that the expression levels of circadian genes are more closely correlated between the cultured (ex vivo) cells and live (in vivo) samples than non-circadian genes, suggesting that this method can be used for effective circadian analysis.

genomics↗

bioRxiv2018

Evaluating DNA methylation age on the Illuminas methylationEPIC BeadChip

DNA methylation age (DNAm age) has become a widely utilized epigenetic biomarker for the aging process. The Horvath method for determining DNAm age is perhaps the most widely utilized and validated DNA methylation age assessment measure. Horvath DNAm age is calculated based on methylation measurements at 353 loci which were present on Illuminas 450k and 27k DNA methylation microarrays. With the increasing use of the more recently developed Illumina MethylationEPIC (850k) microarray, it is worth revisiting this widely used aging measure to evaluate differences in DNA methylation age estimation based on array design. Of the requisite 353 loci, 17 are missing from the current 850k microarray. Using 17 datasets with 27k, 450k, and/or 850k methylation data, we calculated and compared each samples epigenetic age estimated from all 353 loci required from the Horvath DNAm age calculator (full), and using only the 336 loci present on the 27k, 450k, and 850k arrays (reduced). In 450k/27k data, missing loci caused underestimation of epigenetic age when compared with the full clock. Underestimation of full epigenetic age grew from ages 0 to ~20, remaining stable thereafter (mean= -3.46 y, SD=1.13) years for individuals [≥]20 years. Underestimation of DNAm age by the reduced 450k/27k data was similar to the underestimation observed in the 850k data indicating that array differences in DNAm age estimation are primarily driven by missing probes. Correlations between age and DNAm age were not dependent on missing probes or on array designs and consequently associations between DNAm age and outcomes such as sex remained the same independent of missing probes and probe design. In conclusion, DNAm age estimations are array dependent driven by missing probes between arrays. Though correlations and associations with DNAm age may remain the same, researchers should exercise caution when interpreting results based on absolute differences in DNAm age or when mixing samples assayed on different arrays.\n\nDisclaimerThis paper has been reviewed by the National Health and Environmental Effects Research Laboratory, U.S. EPA, and is approved for publication. Approval does not signify that the contents necessarily reflect the views and policies of the agency, nor does mention of trade names or commercial products constitute endorsement or recommendation for use. The authors declare they have no competing financial interests.

bioinformatics↗