bims-agalsp 2023-02-19 papers

bims-agalsp

Biomed News

on Ageing and alternative splicing

Issue of 2023‒02‒19
eleven papers selected by
Dongmeng Wang
King’s College

The landscape of expression and alternative splicing variation across human traits.
Integrated Analysis of Transcriptome Changes in Osteoarthritis: Gene Expression, Pathways and Alternative Splicing.
Molecular mechanisms of coronary artery disease risk at the PDGFD locus.
Clinical traits impacting human tissue transcriptomes.
Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate COPD.
Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging.
Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response.
Longitudinal associations of anticholinergic medications on cognition and possible mitigating role of physical activity.
The lipidomes of C. elegans with mutations in asm-3/acid sphingomyelinase and hyl-2/ceramide synthase show distinct lipid profiles during aging.
Ageotypes revisited: The brain and central nervous system dysfunction as a major nutritional and lifestyle target for healthy aging.
Contribution of Biological Age-Predictive Biomarkers to Nutrition Research: A Systematic Review of the Current Evidence and Implications for Future Research and Clinical Practice.

Cell Genom. 2023 Jan 11. 3(1): 100244

The landscape of expression and alternative splicing variation across human traits.

Raquel García-Pérez, Jose Miguel Ramirez, Aida Ripoll-Cladellas, Ruben Chazarra-Gil, Winona Oliveros, Oleksandra Soldatkina, Mattia Bosio, Paul Joris Rognon, Salvador Capella-Gutierrez, Miquel Calvo, Ferran Reverter, Roderic Guigó, François Aguet, Pedro G Ferreira, Kristin G Ardlie, Marta Melé.

  Understanding the consequences of individual transcriptome variation is fundamental to deciphering human biology and disease. We implement a statistical framework to quantify the contributions of 21 individual traits as drivers of gene expression and alternative splicing variation across 46 human tissues and 781 individuals from the Genotype-Tissue Expression project. We demonstrate that ancestry, sex, age, and BMI make additive and tissue-specific contributions to expression variability, whereas interactions are rare. Variation in splicing is dominated by ancestry and is under genetic control in most tissues, with ribosomal proteins showing a strong enrichment of tissue-shared splicing events. Our analyses reveal a systemic contribution of types 1 and 2 diabetes to tissue transcriptome variation with the strongest signal in the nerve, where histopathology image analysis identifies novel genes related to diabetic neuropathy. Our multi-tissue and multi-trait approach provides an extensive characterization of the main drivers of human transcriptome variation in health and disease.

Keywords:  BMI; age; alternative splicing; ancestry; diabetes; gene expression; human traits; sex; tissue; transcriptome

DOI:  https://doi.org/10.1016/j.xgen.2022.100244
Cartilage. 2023 Feb 17. 19476035231154511

Integrated Analysis of Transcriptome Changes in Osteoarthritis: Gene Expression, Pathways and Alternative Splicing.

Congming Li, Pengli Wei, Lei Wang, Qiang Wang, Hong Wang, Yangjun Zhang.

  OBJECTIVE: Osteoarthritis (OA) is the most prevalent joint disease characterized by the degeneration of articular cartilage and the remodeling of its underlying bones, resulting in pain and loss of function in the knees and hips. As far as we know, no curative treatments are available except for the joint replacement. The precise molecular mechanisms which are involved in the degradation of cartilage matrix and development of osteoarthritis are still unclear.DESIGN: By analyzing RNA-seq data, we found the molecular changes at the transcriptome level such as alternative splicing, gene expression, and molecular pathways in OA knees cartilage.
RESULTS: Expression analysis have identified 457 differential expressed genes including 266 up-regulated genes such as TNFSF15, ST6GALNAC5, TGFBI, ASPM, and TYM, and 191 down-regulated genes such as ADM, JUN, IRE2, PIGA, and MAFF. Gene set enrichment analysis (GSEA) analysis identified down-regulated pathways related to translation, transcription, immunity, PI3K/AKT, and circadian as well as disturbed pathways related to extracellular matrix and collagen. Splicing analysis identified 442 differential alternative splicing events within 284 genes in osteoarthritis, including genes involved in extracellular matrix (ECM) and alternative splicing, and TIA1 was identified as a key regulator of these splicing events.
CONCLUSIONS: These findings provide insights into disease etiology, and offer favorable information to support the development of more effective interventions in response to the global clinical challenge of osteoarthritis.

Keywords:  alternative splicing; molecular pathway; osteoarthritis; transcriptome

DOI:  https://doi.org/10.1177/19476035231154511
Nat Commun. 2023 Feb 15. 14(1): 847

Molecular mechanisms of coronary artery disease risk at the PDGFD locus.

Hyun-Jung Kim, Paul Cheng, Stanislao Travisano, Chad Weldy, João P Monteiro, Ramendra Kundu, Trieu Nguyen, Disha Sharma, Huitong Shi, Yi Lin, Boxiang Liu, Saptarsi Haldar, Simon Jackson, Thomas Quertermous.

Genome wide association studies for coronary artery disease (CAD) have identified a risk locus at 11q22.3. Here, we verify with mechanistic studies that rs2019090 and PDGFD represent the functional variant and gene at this locus. Further, FOXC1/C2 transcription factor binding at rs2019090 is shown to promote PDGFD transcription through the CAD promoting allele. With single cell transcriptomic and histology studies with Pdgfd knockdown in an SMC lineage tracing male atherosclerosis mouse model we find that Pdgfd promotes expansion, migration, and transition of SMC lineage cells to the chondromyocyte phenotype. Pdgfd also increases adventitial fibroblast and pericyte expression of chemokines and leukocyte adhesion molecules, which is linked to plaque macrophage recruitment. Despite these changes there is no effect of Pdgfd deletion on overall plaque burden. These findings suggest that PDGFD mediates CAD risk by promoting deleterious phenotypic changes in SMC, along with an inflammatory response that is primarily focused in the adventitia.

DOI: https://doi.org/10.1038/s41467-023-36518-9
Cell Genom. 2023 Jan 11. 3(1): 100245

Clinical traits impacting human tissue transcriptomes.

Kaur Alasoo.

In this issue of Cell Genomics, Garcia-Perez et al.1 report a comprehensive and careful association analysis between gene expression and splicing measured by the GTEx Consortium2 in 46 human tissues and 21 demographic and clinical traits.

DOI: https://doi.org/10.1016/j.xgen.2022.100245
Am J Respir Cell Mol Biol. 2023 Feb 13.

Integrating Genetics, Transcriptomics, and Proteomics in Lung Tissue to Investigate COPD.

Yu-Hang Zhang, Michael H Cho, Jarrett D Morrow, Peter J Castaldi, Craig P Hersh, Mukul K Midha, Michael R Hoopmann, Sharon M Lutz, Robert L Moritz, Edwin K Silverman.

  The integration of transcriptomic and proteomic data from lung tissue with chronic obstructive pulmonary disease (COPD)-associated genetic variants could provide insight into the biological mechanisms for COPD. Here, we assessed associations between lung transcriptomics and proteomics with COPD in 98 subjects from the Lung Tissue Research Consortium. Low correlations between transcriptomics and proteomics were generally observed, but higher correlations were found for COPD-associated proteins. We integrated COPD risk SNPs or SNPs near COPD-associated proteins with lung transcripts and proteins to identify regulatory cis quantitative trait loci (QTLs). Significant expression QTLs (eQTLs) and protein QTLs (pQTLs) were found regulating multiple COPD-associated biomarkers. We investigated mediated associations from significant protein quantitative trait loci through transcripts to protein levels of COPD-associated proteins. We also attempted to identify colocalized effects between GWAS, eQTL, and pQTL signals. Evidence for colocalization between COPD GWAS signals and pQTL for RHOB and eQTL for DSP was found. We applied Weighted Gene Co-Expression Network Analysis (WGCNA) to find consensus COPD-associated network modules. Two network modules generated by consensus WGCNA were associated with COPD with FDR < 0.05. One network module is related to the catenin complex, and the other module is related to plasma membrane components. In summary, multiple cis-acting effects for transcripts and proteins associated with COPD were identified. Colocalization analysis, mediation analysis, and correlation-based network analysis of multiple Omics data may identify key genes and proteins that work together to influence COPD pathogenesis.

Keywords:  chronic obstructive pulmonary disease; multi-Omics analyses; quantitative trait locus; weighted gene co-expression network analysis

DOI:  https://doi.org/10.1165/rcmb.2022-0302OC
Hum Genomics. 2023 02 11. 17(1): 8

Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging.

Daigo Okada, Jian Hao Cheng, Cheng Zheng, Tatsuro Kumaki, Ryo Yamada.

  BACKGROUND: Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown.RESULT: We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging in a data-driven manner. We applied the proposed method to large-scale, public DNA methylation data to explore the potential patterns of age-related changes in methylation intensity. The results showed that not only linear, but also nonlinear changes in DNA methylation patterns exist. A monotonous demethylation pattern during aging, with its rate decreasing at around age 60, was identified as the candidate stable nonlinear pattern. We also analyzed the age-related changes in methylation variability. The results showed that the variability of methylation intensity tends to increase with age at age-associated sites. The representative variability pattern is a monotonically increasing pattern that accelerates after middle age.
CONCLUSION: DICNAP was able to identify the potential patterns of the changes in the landscape of DNA methylation during aging. It contributes to an improvement in our theoretical understanding of the aging process.

Keywords:  Aging; Biomarker; Computational biology; DNA methylation; Epigenomics; Functional data analysis

DOI:  https://doi.org/10.1186/s40246-023-00453-z
Diabetologia. 2023 Feb 15.

Skeletal muscle and intermuscular adipose tissue gene expression profiling identifies new biomarkers with prognostic significance for insulin resistance progression and intervention response.

Dominik Lutter, Stephan Sachs, Marc Walter, Anna Kerege, Leigh Perreault, Darcy E Kahn, Amare D Wolide, Maximilian Kleinert, Bryan C Bergman, Susanna M Hofmann.

  AIMS/HYPOTHESIS: Although insulin resistance often leads to type 2 diabetes mellitus, its early stages are often unrecognised, thus reducing the probability of successful prevention and intervention. Moreover, treatment efficacy is affected by the genetics of the individual. We used gene expression profiles from a cross-sectional study to identify potential candidate genes for the prediction of diabetes risk and intervention response.METHODS: Using a multivariate regression model, we linked gene expression profiles of human skeletal muscle and intermuscular adipose tissue (IMAT) to fasting glucose levels and glucose infusion rate. Based on the expression patterns of the top predictive genes, we characterised and compared individual gene expression with clinical classifications using k-nearest neighbour clustering. The predictive potential of the candidate genes identified was validated using muscle gene expression data from a longitudinal intervention study.
RESULTS: We found that genes with a strong association with clinical measures clustered into three distinct expression patterns. Their predictive values for insulin resistance varied substantially between skeletal muscle and IMAT. Moreover, we discovered that individual gene expression-based classifications may differ from classifications based predominantly on clinical variables, indicating that participant stratification may be imprecise if only clinical variables are used for classification. Of the 15 top candidate genes, ST3GAL2, AASS, ARF1 and the transcription factor SIN3A are novel candidates for predicting a refined diabetes risk and intervention response.
CONCLUSION/INTERPRETATION: Our results confirm that disease progression and successful intervention depend on individual gene expression states. We anticipate that our findings may lead to a better understanding and prediction of individual diabetes risk and may help to develop individualised intervention strategies.

Keywords:  Computational health; Diabetes subtypes; Glucose intolerance; Insulin resistance; Intermuscular adipose tissue; Obesity; Personalised medicine; Response to treatment prediction; Type 2 diabetes

DOI:  https://doi.org/10.1007/s00125-023-05874-y
J Am Geriatr Soc. 2023 Feb 14.

Longitudinal associations of anticholinergic medications on cognition and possible mitigating role of physical activity.

Amani M Norling, Aleena Bennett, Michael Crowe, D Leann Long, Sara A Nolin, Terina Myers, Victor A Del Bene, Ronald M Lazar, Adam Gerstenecker.

  BACKGROUND: Many older adults take at least one prescription medication with anticholinergic (ACH) activity, which can impact the central nervous system and can lead to cognitive decline and impairment especially in an aging population susceptible to cognitive changes. We examined this relationship between ACH burden and cognitive function in middle-aged and older adults. We further determined if increased activity levels mitigated the relationships between ACH burden and cognition.METHODS: Data from The Reasons for Geographic and Racial Differences in Stroke project were used. We included 20,575 adults aged ≥45 years with longitudinal cognitive testing. The anticholinergic cognitive burden (ACB) scale was used to assess for ACH use and overall burden. Cognitive data included an overall composite score, a memory, and verbal fluency composites. Mixed effects models were conducted to determine if cognitive function worsened over time for participants with higher ACB (>3) scores. The full model adjusted for age, sex, race, education, diabetes, hypertension, cardiovascular disease, congestive heart failure, and dyslipidemia, self-reported physical activity (PA) and depressive symptoms.
RESULTS: A significant relationship between ACH burden and composite cognitive scores was found (p = <0.001), with those with higher ACB showing more rapid cognitive decline over time. There was an effect of age for participants with higher ACB (>3) scores and ACB as a continuous variable. Baseline PA level was associated with less cognitive decline over time and this effect was greater in older cohorts.
CONCLUSIONS: We observed an effect of ACHs on cognition in adults ≥45 years old that worsened with age. ACH users showed more cognitive effects, whereas PA emerged as a possible mitigating factor.

Keywords:  ACB; aging; anticholinergics; cognition; physical activity

DOI:  https://doi.org/10.1111/jgs.18279
Aging (Albany NY). 2023 Feb 13. 15

The lipidomes of C. elegans with mutations in asm-3/acid sphingomyelinase and hyl-2/ceramide synthase show distinct lipid profiles during aging.

Trisha A Staab, Grace McIntyre, Lu Wang, Joycelyn Radeny, Lisa Bettcher, Melissa Guillen, Margaret P Peck, Azia P Kalil, Samantha P Bromley, Daniel Raftery, Jason P Chan.

  Lipid metabolism affects cell and physiological functions that mediate animal healthspan and lifespan. Lipidomics approaches in model organisms have allowed us to better understand changes in lipid composition related to age and lifespan. Here, using the model C. elegans, we examine the lipidomes of mutants lacking enzymes critical for sphingolipid metabolism; specifically, we examine acid sphingomyelinase (asm-3), which breaks down sphingomyelin to ceramide, and ceramide synthase (hyl-2), which synthesizes ceramide from sphingosine. Worm asm-3 and hyl-2 mutants have been previously found to be long- and short-lived, respectively. We analyzed longitudinal lipid changes in wild type animals compared to mutants at 1-, 5-, and 10-days of age. We detected over 700 different lipids in several lipid classes. Results indicate that wildtype animals exhibit increased triacylglycerols (TAG) at 10-days compared to 1-day, and decreased lysophoshatidylcholines (LPC). We find that 10-day hyl-2 mutants have elevated total polyunsaturated fatty acids (PUFA) and increased LPCs compared to 10-day wildtype animals. These changes mirror another short-lived model, the daf-16/FOXO transcription factor that is downstream of the insulin-like signaling pathway. In addition, we find that hyl-2 mutants have poor oxidative stress response, supporting a model where mutants with elevated PUFAs may accumulate more oxidative damage. On the other hand, 10-day asm-3 mutants have fewer TAGs. Intriguingly, asm-3 mutants have a similar lipid composition as the long-lived, caloric restriction model eat-2/mAChR mutant. Together, these analyses highlight the utility of lipidomic analyses to characterize metabolic changes during aging in C. elegans.

Keywords:  C. elegans; aging; fatty acid metabolism; lipidomics; sphingolipid metabolism

DOI:  https://doi.org/10.18632/aging.204515
Maturitas. 2023 Feb 06. pii: S0378-5122(23)00022-1. [Epub ahead of print]170 51-57

Ageotypes revisited: The brain and central nervous system dysfunction as a major nutritional and lifestyle target for healthy aging.

Maria G Grammatikopoulou, Efstathios Skoufas, Spyridon Kanellakis, Despina Sanoudou, Georgios A Pavlopoulos, Aristides G Eliopoulos, Kalliopi K Gkouskou.

  Undeniably, biological age can significantly differ between individuals of similar chronological age. Longitudinal, deep multi-omic profiling has recently enabled the identification of individuals with distinct aging phenotypes, termed 'ageotypes'. This effort has provided a plethora of data and new insights into the diverse molecular mechanisms presumed to drive aging. Translational opportunities stemming from this knowledge continue to evolve, providing an opportunity for the provision of nutritional interventions aiming to decelerate the aging process. In this framework, the contemporary ageotypes classification was revisited via in silico analyses, with the brain and nervous system being identified as the primary targets of age-related biomolecules, acting through inflammatory and metabolic pathways. Nutritional and lifestyle factors affecting these pathways in the brain and central nervous system that could help guide personalized recommendations for the attainment of healthy aging are discussed.

Keywords:  Bioinformatics; Brain; CNS; Genetics; Inflammaging; Nutriomics; Nutrition; Omics; ageotype; in silico

DOI:  https://doi.org/10.1016/j.maturitas.2023.01.013
Adv Nutr. 2022 Sep;pii: S2161-8313(23)00049-2. [Epub ahead of print]13(5): 1930-1946

Contribution of Biological Age-Predictive Biomarkers to Nutrition Research: A Systematic Review of the Current Evidence and Implications for Future Research and Clinical Practice.

George Siopis, Judi Porter.

  The global population is living longer; however, not everyone ages at the same rate with regard to their physical and cognitive abilities and their vulnerability to certain diseases and death. This review aimed to synthesize the contribution of biological age-predictive biomarkers to nutrition research and highlight the implications for future research and clinical practice. MEDLINE, CINAHL, and Cochrane CENTRAL were systematically searched on 30 September 2021 for randomized controlled trials and cross-sectional studies examining the association between nutrition and biological age in older adults reporting on genetic, clinical, or molecular biomarkers of biological aging. Cochrane's ROB 2 and ROBINS-I were used to assess the quality of included studies. Synthesis was undertaken narratively. Of 1245 records identified from the search, 13 studies from 8 countries and territories, involving 5043 participants, were included. Seven studies assessed associations between nutrient food intake and telomere attrition, reporting protective effects for branched-chain amino acids, calcium and vitamin D, and a diet of a lower inflammatory index; whereas they found shorter telomeres in people consuming more processed foods and arachidonic acid and other proinflammatory compounds. Five studies examined the associations between plasma nutrition biomarkers and cognitive function, and found a protective effect for HDL cholesterol, lycopene, carotenoids, ω-3 and ω-6 fatty acids, and vitamins B, C, D, and E; whereas trans fatty acids and fibrinogen correlated with a decline in cognitive function. One study used Horvath's clock and reported the epigenetic rejuvenation effect of a Mediterranean diet. In conclusion, biological aging was negatively associated with an anti-inflammatory diet. However, a few studies did not control for the confounding effect of other lifestyle factors. Future research should address this and also assess the synergistic effect of different nutrients, their combinations, and evaluate their dose-response relations. Nutrition practice can incorporate updated screening procedures for older people that include relevant biological aging nutrition markers, leading to anti-aging precision nutrition therapy. The methodology of this systematic review was registered in PROSPERO (CRD42021288122).

Keywords:  aging; cognitive function; diet; dietetics; epigenetics; geriatrics; gerontology; nutritional epidemiology; telomere length

DOI:  https://doi.org/10.1093/advances/nmac060