BACKGROUND: Dilated cardiomyopathy (DCM) is associated with shifts in cardiac metabolism. However, those shifts vary widely across patients, likely reflecting the diverse underlying causes of the disease. Identifying metabolic subtypes, or metabotypes, in DCM patients could help tailor treatments to patient needs. Hence, having a practical approach to identify these metabotypes would be a significant advance toward precision medicine in DCM. METHODS: We present a systems biology approach to uncover metabotypes directly from widely available transcriptomic data. We use in silico metabolic modeling methods that we have optimized for cardiac research to predict metabolic function activities from enzyme expression, followed by a hierarchical clustering approach. To demonstrate its power, we applied our method to publicly available cardiac data from end-stage DCM patients (N=164) and nonfailing controls (N=160). RESULTS: We identified 2 distinct metabotypes in end-stage DCM patients. These metabotypes are characterized by unique metabolic changes, notably in calcium handling, amino acid oxidation, and the pentose phosphate pathway. Strikingly, 1 DCM metabotype showed greater metabolic divergence from healthy controls, suggesting a greater metabolic contribution to its underlying etiology—even though disease severity was similar between the 2 identified DCM metabotypes. Further transcriptome-wide analysis revealed immune-related differences between metabotypes, suggesting an underlying interplay between inflammation, the immune response, and metabolism. CONCLUSIONS: Our results imply the presence of distinct metabotypes in end-stage DCM. Our systems biology approach offers an exciting opportunity to uncover novel insights into DCM, paving the way for a deeper understanding of its progression and heterogeneity.

Context Insulin resistance (IR) can develop in multiple organs, representing distinct etiologies toward cardiometabolic disease.Objective This study aimed to investigate which proteins and pathways are specific for liver IR or muscle IR in individuals with overweight or obesity of the Diet, Obesity, and Genes cohort (n = 535) (NCT00390637, ClinicalTrials.gov).Methods First, independent associations between muscle and liver IR and protein abundance levels were assessed. In the analysis, we corrected for study center, sex, body mass index, and age, whereby the analyses on liver IR were adjusted for muscle IR and vice versa. Differentially abundant proteins were then subjected to pathway enrichment analysis.Results Muscle IR was associated with 160 proteins, and liver IR was associated with 81 proteins. Of these, 12 were shared between both forms of IR. Pathway enrichment analysis identified 51 enriched pathways for muscle IR, characterized by a strong inflammatory profile, including chemokine signaling, interleukin-6 signaling, and complement system-related pathways. In contrast, liver IR was associated with 11 enriched pathways, primarily related to the complement system.Conclusion Understanding the processes underlying these distinct IR phenotypes could inform the development of personalized prevention strategies.

MOTIVATION:Huntington's disease (HD) exhibits substantial variability in age of onset and disease progression that is not fully explained by CAG repeat length alone. Part of this residual variation is heritable, implicating additional genetic mechanisms. cis-regulatory variation, genetic variants that alter transcription and splicing of nearby genes, represents one such mechanism that can be quantified through allele-specific expression (ASE) analysis. However, methods for integrating ASE profiles into patient stratification frameworks remain underdeveloped, particularly for rare diseases with small cohorts and sparse data. RESULTS:We adapt a network-based stratification algorithm, originally developed for somatic tumour mutations, to ASE data. By propagating gene-level ASE imbalance profiles through a protein-protein interaction network, we stratified 20 HD patients into three distinct biological patient subgroups. Differential gene expression analysis highlights neuroinflammatory pathways, including microglial activation, immune cell activation, and cytokine regulation, as key sources of inter-patient heterogeneity, while differential ASE analysis implicates proteasomal and ubiquitin-dependent protein catabolic processes, immune activation, and central nervous system development. Intersection of differentially imbalanced and expressed genes identified FAM181B as a candidate gene with potential eQTL-mediated regulation, supported by independent cis-eQTL evidence for rs3780 in the caudate and putamen, the primary HD-affected striatal regions. FAM181B encodes a nuclear protein expressed in neural tissues acting as an interactor of the Hippo pathway TEAD transcription factors, implicating transcriptional regulatory variation as a potential contributor to molecular heterogeneity between patient subgroups. Differences in cortical and striatal neuropathological scores between clusters, even when adjusted for CAG repeat length, provide clinical support for the biological relevance of the identified subgroups. AVAILABILITY:All analysis code, Docker containers, and conda environments are available at https://github.com/macsbio/HD-ASE-NBS.

Preclinical research suggests that the mucosal symbiont Akkermansia muciniphila prevents diet-induced obesity. In this randomized controlled trial, adults with overweight/obesity (n = 90) underwent an 8-week low-energy diet for ≥8% weight loss, followed by a 24-week healthy ad libitum diet with daily supplementation of pasteurized A. muciniphila MucT or placebo. The primary outcome was change in body weight during the maintenance period. Here we show that MucT led to lower body weight regain versus placebo at the end of the weight maintenance period (MucT: 1.2 ± 0.7 kg, placebo: 3.2 ± 0.4 kg, P = 0.012). Additionally, the MucT group had a greater net weight loss from baseline to end of maintenance than the placebo group (3.1 ± 0.7 kg, P = 0.009). Initial Akkermansia spp. abundance was associated with cardiometabolic response to MucT. No serious adverse events related to the treatment were observed. The relative short-term intervention and absence of groups receiving modified strains of MucT lacking active components are limitations that should be addressed in the future. Our findings suggest pasteurized A. muciniphila MucT as a strategy for weight loss maintenance. ClinicalTrials.gov: NCT05417360 .

Dilated cardiomyopathy (DCM) is associated with shifts in cardiac metabolism. Those shifts are inconsistent between patients, possibly due to heterogeneity in DCM etiologies. Identifying metabolic subtypes, or metabotypes, in DCM patients may open personalized treatment opportunities. Developing a methodology to identify metabotypes would be a boon in this regard. Here, we describe a metabotyping pipeline, integrating advanced metabolic modeling methods optimized for cardiac research, to uncover these subtypes using widely available transcriptomics data. We applied our method to publicly available cardiac data of end-stage DCM patients and non-failing controls, identifying two metabotypes in the DCM group. These metabotypes are characterized by unique metabolic alterations, notably in calcium handling, amino-acid oxidation, and the pentose phosphate pathway. Strikingly, one metabotype exhibited a greater deviation from healthy controls, suggesting a greater metabolic contribution to its underlying etiology. Further transcriptome-wide analysis revealed immune-related differences between metabotypes, suggesting an interplay between inflammation, immune response and metabolism in these DCM subtypes. Our study uncovers cardiometabolic heterogeneity in DCM and underscores the potential of transcriptome-derived metabotyping in cardiovascular research. ### Competing Interest Statement The authors have declared no competing interest.

CONTEXT:Fetuin B is a steatosis-responsive hepatokine that induces glucose intolerance in mice. Recently, we found that fetuin B in white adipose tissue was positively associated with peripheral insulin resistance in mice and a small study population, possibly through a fetuin B-induced inflammatory response in adipocytes. OBJECTIVE:This translational study aimed to investigate the link between plasma fetuin B and the adipose tissue transcriptome and plasma proteome in a large cohort of humans. METHODS:Continuous linear regression analysis in R was applied to investigate the link between plasma fetuin B and the adipose tissue transcriptome (n = 207) and plasma proteome (n = 558) in humans, after adjustment for sex, age, and study center (model 1); model 1 + BMI (model 2); and model 2 + insulin sensitivity (Matsuda index) (model 3). RESULTS:Plasma fetuin B was associated with more than 100 genes in white adipose tissue, belonging to pathways related to cytokine/chemokine signaling (models 1 and 2) and insulin signaling (all models), and with more than 146 plasma proteins involved in pathways related to metabolic processes and insulin signaling (all models). CONCLUSION:Plasma fetuin B is related to adipose tissue genes and plasma proteins involved in metabolic processes and insulin signaling. Our findings provide evidence for the involvement of white adipose tissue in fetuin B-induced insulin resistance.

Mitochondrial dynamics is crucial for cellular homeostasis. However, not all proteins involved are known. Using a protein-protein interaction (PPI) approach, we identified ITPRIPL2 for involvement in mitochondrial dynamics. ITPRIPL2 co-localizes with intermediate filament protein vimentin, supported by protein simulations. ITPRIPL2 knockdown reveals mitochondrial elongation, disrupts vimentin processing, intermediate filament formation, and alters vimentin-related pathways. Interestingly, vimentin knockdown also leads to mitochondrial elongation. These findings highlight ITPRIPL2 as vimentin-associated protein essential for intermediate filament structure and suggest a role for intermediate filaments in mitochondrial morphology. Our study demonstrates that PPI analysis is a powerful approach for identifying novel mitochondrial dynamics proteins.

Obesity and cardiometabolic disease often, but not always, coincide. Distinguishing sub-populations within which cardiometabolic risk diverges from the risk expected for a given body mass index (BMI) may facilitate precision prevention of cardiometabolic diseases. Accordingly, we performed unsupervised clustering in four European population-based cohorts (N ~ 173K). We detected five discordant profiles consisting of individuals with cardiometabolic biomarkers higher or lower than expected given their BMI, in total representing ~20% of the total population. Persons with discordant profiles differed from concordant individuals in prevalence and future risk of major adverse cardiovascular events (MACE) and diabetes. Subtle BMI-discordances in biomarkers affected disease risk. For instance, a 10% higher probability of having a discordant lipid profile was associated with a 5% higher risk of MACE (HR in women: 1.05, 95% CI: 1.03, 1.06, p = 4.19x10-10; HR in men: 1.05, 95% CI: 1.04, 1.06, p= 9.33x10-14). Multivariate prediction models for MACE and diabetes performed better when incorporating discordant profile information (likelihood ratio test P < 0.001). This enhancement represents an additional net benefit of 4 to 15 additional correct interventions, and 37 to 135 additional unnecessary interventions correctly avoided for every 10,000 individuals tested.

Continuous glucose monitoring (CGM) is a promising, minimally invasive alternative to plasma glucose measurements for calibrating physiology-based mathematical models of insulin-regulated glucose metabolism, reducing the reliance on in-clinic measurements. However, the use of CGM glucose, particularly in combination with insulin measurements, to develop personalized models of glucose regulation remains unexplored. Here, we simultaneously measured interstitial glucose concentrations using CGM as well as plasma glucose and insulin concentrations during an oral glucose tolerance test (OGTT) in individuals with overweight or obesity to calibrate personalized models of glucose-insulin dynamics. We compared the use of interstitial glucose with plasma glucose in model calibration, and evaluated the effects on model fit, identifiability, and model parameters’ association with clinically relevant metabolic indicators. Models calibrated on both plasma and interstitial glucose resulted in good model fit, and the parameter estimates associated with metabolic indicators such as insulin sensitivity measures in both cases. Moreover, practical identifiability of model parameters was improved in models estimated on CGM glucose compared to plasma glucose. Together these results suggest that CGM glucose may be considered as a minimally invasive alternative to plasma glucose measurements in model calibration to quantify the dynamics of glucose regulation.

Background Tissue-specific insulin resistance (IR) predominantly in muscle (muscle IR) or liver (liver IR) has previously been linked to distinct fasting metabolite profiles, but postprandial metabolite profiles have not been investigated in tissue-specific IR yet. Given the importance of postprandial metabolic impairments in the pathophysiology of cardiometabolic diseases, we compared postprandial plasma metabolite profiles in response to a high-fat mixed meal between individuals with predominant muscle IR or liver IR. Methods This cross-sectional study included data from 214 women and men with BMI 25–40 kg/m 2 , aged 40–75 years, and with predominant muscle IR or liver IR. Tissue-specific IR was assessed using the muscle insulin sensitivity index (MISI) and hepatic insulin resistance index (HIRI), which were calculated from the glucose and insulin responses during a 7-point oral glucose tolerance test. Plasma samples were collected before (T = 0) and after (T = 30, 60, 120, 240 min) consumption of a high-fat mixed meal and 247 metabolite measures, including lipoproteins, cholesterol, triacylglycerol (TAG), ketone bodies, and amino acids, were quantified using nuclear magnetic resonance spectroscopy. Differences in postprandial plasma metabolite iAUCs between muscle and liver IR were tested using ANCOVA with adjustment for age, sex, center, BMI, and waist-to-hip ratio. P -values were adjusted for a false discovery rate (FDR) of 0.05 using the Benjamini–Hochberg method. Results Sixty-eight postprandial metabolite iAUCs were significantly different between liver and muscle IR. Liver IR was characterized by greater plasma iAUCs of large VLDL ( p = 0.004), very large VLDL ( p = 0.002), and medium-sized LDL particles ( p = 0.026), and by greater iAUCs of TAG in small VLDL ( p = 0.025), large VLDL ( p = 0.003), very large VLDL ( p = 0.002), all LDL subclasses (all p < 0.05), and small HDL particles ( p = 0.011), compared to muscle IR. In liver IR, the postprandial plasma fatty acid (FA) profile consisted of a higher percentage of saturated FA ( p = 0.013), and a lower percentage of polyunsaturated FA ( p = 0.008), compared to muscle IR. Conclusion People with muscle IR or liver IR have distinct postprandial plasma metabolite profiles, with more unfavorable postprandial metabolite responses in those with liver IR compared to muscle IR.

Mitochondria are dynamic organelles and the main source of cellular energy. Their dynamic nature is crucial to meet cellular requirements. However, the processes and proteins involved in mitochondrial dynamics are not fully understood. Using a computational protein-protein interaction approach, we identified ITPRIPL2, which caused mitochondrial elongation upon knockdown. ITPRIPL2 co-localizes with the intermediate filament protein vimentin and interacts with vimentin according to protein simulations. ITPRIPL2 knockdown alters vimentin processing, disrupts intermediate filaments and transcriptomics analysis revealed changes in vimentin-related pathways. Our data illustrates that ITPRIPL2 is essential for vimentin related intermediate filament structure. Interestingly, like ITPRIPL2 knockdown, vimentin knockdown results in mitochondrial elongation. Our data highlights ITPRIPL2 as a vimentin-associated protein and reveals a role for intermediate filaments in mitochondrial dynamics, improving our understanding of mitochondrial dynamics regulators. Moreover, our study demonstrates that protein- protein interaction analysis is a powerful approach for identifying novel mitochondrial dynamics proteins. ### Competing Interest Statement The authors have declared no competing interest.

An established hallmark of cancer cells is metabolic reprogramming, largely consisting in the exacerbated glucose uptake. Adipocytes in the tumor microenvironment contribute toward breast cancer (BC) progression and are highly responsive to metabolic fluctuations. Metabolic conditions characterizing obesity and/or diabetes associate with increased BC incidence and mortality. To explore BC-adipocytes interaction and define the impact of glucose in such dialogue, Mammary Adipose-derived Mesenchymal Stem Cells (MAd-MSCs) were differentiated into adipocytes and co-cultured with ER+ BC cells while exposed to glucose concentration resembling hyperglycemia or normoglycemia in humans (25mM or 5.5mM). The transcriptome of both cell types in co-culture as in mono-culture was profiled by RNA-Seq to define the impact of adipocytes on BC cells and viceversa (i), the action of glucose on BC cells, adipocytes (ii) and their crosstalk (iii). Noteworthy, we provided evidence that co-culture with adipocytes in a glucose-rich environment determined a re-program of BC cell transcriptome driving lipid accumulation, a hallmark of BC aggressiveness, promoting stem-like properties and reducing Tamoxifen responsiveness. Moreover, our data point out to a transcriptional effect through which BC cells induce adipocytes de-lipidation, paralleled by pluripotency gain, as source of lipids when glucose lowering occurs. Thus, modulating plasticity of peri-tumoral adipocytes may represent a key point for halting BC progression in metabolically unbalanced patients.

The intricate dependency structure of biological "omics" data, particularly those originating from longitudinal intervention studies with frequently sampled repeated measurements renders the analysis of such data challenging. The high-dimensionality, inter-relatedness of multiple outcomes, and heterogeneity in the studied systems all add to the difficulty in deriving meaningful information. In addition, the subtle differences in dynamics often deemed meaningful in nutritional intervention studies can be particularly challenging to quantify. In this work we demonstrate the use of quantitative longitudinal models within the repeated-measures ANOVA simultaneous component analysis+ (RM-ASCA+) framework to capture the dynamics in frequently sampled longitudinal data with multivariate outcomes. We illustrate the use of linear mixed models with polynomial and spline basis expansion of the time variable within RM-ASCA+ in order to quantify non-linear dynamics in a simulation study as well as in a metabolomics data set. We show that the proposed approach presents a convenient and interpretable way to systematically quantify and summarize multivariate outcomes in longitudinal studies while accounting for proper within subject dependency structures.

Dilated cardiomyopathy is a heterogeneous disease characterized by multiple genetic and environmental etiologies. The majority of patients are treated the same despite these differences. The cardiac transcriptome provides information on the patient's pathophysiology, which allows targeted therapy. Using clustering techniques on data from the genotype, phenotype, and cardiac transcriptome of patients with early- and end-stage dilated cardiomyopathy, more homogeneous patient subgroups are identified based on shared underlying pathophysiology. Distinct patient subgroups are identified based on differences in protein quality control, cardiac metabolism, cardiomyocyte function, and inflammatory pathways. The identified pathways have the potential to guide future treatment and individualize patient care.

Summary: Dilated cardiomyopathy is a heterogeneous disease characterized by multiple genetic and environmental etiologies. The majority of patients are treated the same despite these differences. The cardiac transcriptome provides information on the patient's pathophysiology, which allows targeted therapy. Using clustering techniques on data from the genotype, phenotype, and cardiac transcriptome of patients with early- and end-stage dilated cardiomyopathy, more homogeneous patient subgroups are identified based on shared underlying pathophysiology. Distinct patient subgroups are identified based on differences in protein quality control, cardiac metabolism, cardiomyocyte function, and inflammatory pathways. The identified pathways have the potential to guide future treatment and individualize patient care.

HomeCirculation: Genomic and Precision MedicineVol. 16, No. 1Titin Allelic Expression and Protein Processing Pathways in Early-Stage Dilated Cardiomyopathy Patients With Truncating Titin Variants Free AccessLetterPDF/EPUBAboutView PDFView EPUBSections ToolsAdd to favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessLetterPDF/EPUBTitin Allelic Expression and Protein Processing Pathways in Early-Stage Dilated Cardiomyopathy Patients With Truncating Titin Variants Sophie L.V.M. Stroeks, Daan van Beek, Michiel E. Adriaens and Job A.J. Verdonschot Sophie L.V.M. StroeksSophie L.V.M. Stroeks https://orcid.org/0000-0003-0965-6359 Department of Cardiology, Cardiovascular Research Institute (CARIM), Maastricht, The Netherlands (S.L.V.M.S., J.A.J.V.). KU Leuven, Cardiovascular Sciences, Belgium (S.L.V.M.S.). , Daan van BeekDaan van Beek https://orcid.org/0000-0002-1273-9756 Maastricht Centre for Systems Biology, Maastricht University, The Netherlands (D.v.B., M.E.A.). , Michiel E. AdriaensMichiel E. Adriaens Maastricht Centre for Systems Biology, Maastricht University, The Netherlands (D.v.B., M.E.A.). and Job A.J. VerdonschotJob A.J. Verdonschot Correspondence to: Job A.J. Verdonschot, MD, PhD, Department of Cardiology, Maastricht University Medical Center, PO Box 5800, 6202 AZ Maastricht, The Netherlands. Email E-mail Address: [email protected] https://orcid.org/0000-0001-5549-1298 Department of Cardiology, Cardiovascular Research Institute (CARIM), Maastricht, The Netherlands (S.L.V.M.S., J.A.J.V.). Department of Clinical Genetics, Maastricht University Medical Center, The Netherlands (J.A.J.V.). Originally published30 Jan 2023https://doi.org/10.1161/CIRCGEN.122.003901Circulation: Genomic and Precision Medicine. 2023;16Other version(s) of this articleYou are viewing the most recent version of this article. Previous versions: January 30, 2023: Ahead of Print Truncating titin variants (TTNtv) are the most frequent genetic cause of dilated cardiomyopathy (DCM).1 The main disease mechanism was thought to be TTN (titin) haploinsufficiency caused by nonsense-mediated decay of mutant TTN mRNA, until 2 independent studies recently showed the presence of truncated TTN proteins in the hearts of patients with end-stage heart failure who carried a TTNtv.2,3 These findings suggest that the presence of truncated TTN proteins as poison peptides and TTN haploinsufficiency both contribute to the pathogenesis of disease in TTNtv cardiomyopathy. The presence of a TTNtv did not affect allelic balance of the TTN allele, indicating that the wild-type and the TTNtv allele were both equally expressed, where expression of the TTNtv allele results in a truncated protein.2 Both studies used cardiac tissue from patients with end-stage DCM, acknowledging that these findings preclude any conclusions about the early stages of pathogenesis, hypothesizing that nonsense-medicated mRNA decay may be an important disease mechanism in the early stage. We aimed to determine allelic balance in the hearts from patients with early-stage DCM with and without a TTNtv.To investigate the impact of TTNtv on TTN expression, we used a previously generated dataset from genome-wide RNA sequencing of endomyocardial biopsies from 67 patients with DCM, of which 23 had a TTNtv.4 All biopsies were obtained during the diagnostic work-up of patients with early-stage DCM. We did not have access to cardiac tissue from nonfailing hearts. We calculated the allelic imbalance ratios for all heterozygous loci in TTN while filtering on loci with a minor allelic read depth of at least 102. Furthermore, unbiased enrichment analysis of Kyoto Encyclopedia of Genes and Genomes pathways was performed on the differentially expressed genes (upregulated, Log2FC >1, P-value <0.01) of the sequencing dataset using The Database for Annotation, Visualization and Integrated Discovery. The study was approved by the institutional Medical Ethics Committee. All patients gave written informed consent.No major differences in patient clinical characteristics were observed between TTNtv− and TTNtv+ patients. The average age of diagnosis was 58 and 54 years in TTNtv− and TTNtv+ patients, respectively (P=0.11). The TTNtv+ group consisted of more male patients (87%) compared to the TTNtv− groups (67.4%; P=0.09). At first presentation, 17.4% of TTNtv+ patients and 11.6% in TTNtv− patients presented with an NYHA class ≥3 (P=0.55). The mean LVEF was 25.7% (SD 10.2) in TTNtv+ patients compared to 31% (SD 11.3) in TTNtv− patients (P=0.07).There was a marginal allelic imbalance of TTN in both early-stage TTNtv and non-TTNtv DCM cardiac tissue (Figure [A]), but no significant difference in allelic imbalance ratio between the 2 groups. However, the plot in Figure (A) indicates a difference and with a larger sample size this would be significant. The allelic expression did not correlate with any clinical parameter. A previously published article by McAfee et al2 also showed marginal allelic imbalance of TTN in end-stage TTNtv+ DCM hearts compared to end-stage TTNtv− DCM hearts, but concluded that the presence of TTNtv has little impact on TTN allele expression. Our results combined with the results of McAfee et al indicate that irrespective of disease stage, there is little to no allelic imbalance in TTNtv cardiomyopathy patients.Download figureDownload PowerPointFigure. TTN transcript allelic imbalance ratio and pathway enrichment analysis in TTNtv− DCM patients and TTNtv+ DCM patients. A, No differential allelic imbalance in early disease stage TTNtv+ compared to TTNtv− DCM hearts (P=0.14, n=67). Allelic imbalance is shown as the ratio between the major and minor allele, where 1 indicates equal expression. P-value was determined by Mann-Whitney Wilcoxon test. B, Significant enriched KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways of upregulated differentially expressed genes involved in protein synthesis and quality control, comparing early-stage TTNtv− DCM patients to TTNtv+ DCM patients. Enriched nonprotein synthesis-related pathways are not shown here. DCM indicates dilated cardiomyopathy; TTN, titin; and TTNtv, truncating titin variants.Pathway analysis of RNA isolated from the hearts of early-stage TTNtv− and TTNtv+ DCM patients revealed upregulated pathways of protein synthesis and protein quality control, like ribosome (biosynthesis), spliceosome, and proteasome in those with a TTNtv (Figure [B]). Although these results are not specific for the TTN protein synthesis and quality control, the major changes that are observed in TTNtv+ hearts could suggest that they are caused by translation and possible break-down of a large protein such as TTN. We hypothesize that the lack of functional TTN in the sarcomere results in a feedback loop to upregulate ribosome biogenesis and translation of TTNtv mRNA. Altogether, these upregulated pathways in early-stage TTNtv DCM patients are suggestive of truncated protein translation, a mechanism that could contribute to the pathogenesis in early-stage TTNtv DCM.In conclusion, our results show that there is no difference in the processing of mutant and healthy RNA in the majority of early-stage DCM patients with a TTNtv, which indicate that nonsense-mediated decay is not a common disease mechanism in these patients. As shown by McAfee et al and Fomin et al, truncated TTN proteins are present in end-stage TTNtv DCM cardiac tissue encoded by the TTNtv containing allele. Combined with our transcriptomics data, this may suggest that even in early disease stage DCM patients, a dominant-negative or poison peptide mechanism contributes to the phenotype. However, functional studies in early-stage TTNtv DCM heart tissue, including proteomics and gel electrophoresis, are needed to affirm the presence of truncated TTN proteins as a key disease mechanism in TTNtv cardiomyopathy irrespective of the disease stage.Article InformationSources of FundingThis work was supported by the Netherlands Heart Foundation (grant 2020B005 DOUBLE-DOSE). Dr Verdonschot is supported by a Dutch Heart Foundation Dekker – Clinical Scientist grant. The views expressed in this work are those of the authors and not necessarily those of the funders.Disclosures None.FootnotesFor Sources of Funding and Disclosures, see page 91.Correspondence to: Job A.J. Verdonschot, MD, PhD, Department of Cardiology, Maastricht University Medical Center, PO Box 5800, 6202 AZ Maastricht, The Netherlands. Email job.verdonschot@mumc.nlReferences1. Verdonschot JAJ, Hazebroek MR, Krapels IPC, Henkens M, Raafs A, Wang P, Merken JJ, Claes GRF, Vanhoutte EK, van den Wijngaard A, et al. Implications of genetic testing in dilated cardiomyopathy.Circ Genom Precis Med. 2020; 13:476–487. doi: 10.1161/CIRCGEN.120.003031LinkGoogle Scholar2. McAfee Q, Chen CY, Yang Y, Caporizzo MA, Morley M, Babu A, Jeong S, Brandimarto J, Bedi KC, Flam E, et al. Truncated titin proteins in dilated cardiomyopathy.Sci Transl Med. 2021; 13:eabd7287. doi: 10.1126/scitranslmed.abd7287CrossrefMedlineGoogle Scholar3. Fomin A, Gärtner A, Cyganek L, Tiburcy M, Tuleta I, Wellers L, Folsche L, Hobbach AJ, von Frieling-Salewsky M, Unger A, et al. Truncated titin proteins and titin haploinsufficiency are targets for functional recovery in human cardiomyopathy due to TTN mutations.Sci Transl Med. 2021; 13:eabd3079. doi: 10.1126/scitranslmed.abd3079CrossrefMedlineGoogle Scholar4. Verdonschot JAJ, Merlo M, Dominguez F, Wang P, Henkens M, Adriaens ME, Hazebroek MR, Masè M, Escobar LE, Cobas-Paz R, et al. Phenotypic clustering of dilated cardiomyopathy patients highlights important pathophysiological differences.Eur Heart J. 2021; 42:162–174. doi: 10.1093/eurheartj/ehaa841CrossrefMedlineGoogle Scholar eLetters(0)eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.Sign In to Submit a Response to This Article Previous Back to top Next FiguresReferencesRelatedDetails February 2023Vol 16, Issue 1 Advertisement Article InformationMetrics © 2023 American Heart Association, Inc.https://doi.org/10.1161/CIRCGEN.122.003901PMID: 36716182 Originally publishedJanuary 30, 2023 KeywordsallelescardiomyopathyhaploinsufficiencyRNAsequence analysisPDF download Advertisement SubjectsComputational Biology

Computational models of human glucose homeostasis can provide insight into the physiological processes underlying the observed inter-individual variability in glucose regulation. Modelling approaches ranging from "bottom-up" mechanistic models to "top-down" data-driven techniques have been applied to untangle the complex interactions underlying progressive disturbances in glucose homeostasis. While both approaches offer distinct benefits, a combined approach taking the best of both worlds has yet to be explored. Here, we propose a sequential combination of a mechanistic and a data-driven modeling approach to quantify individuals' glucose and insulin responses to an oral glucose tolerance test, using cross sectional data from 2968 individuals from a large observational prospective population-based cohort, the Maastricht Study. The best predictive performance, measured by R2 and mean squared error of prediction, was achieved with personalized mechanistic models alone. The addition of a data-driven model did not improve predictive performance. The personalized mechanistic models consistently outperformed the data-driven and the combined model approaches, demonstrating the strength and suitability of bottom-up mechanistic models in describing the dynamic glucose and insulin response to oral glucose tolerance tests.

The regenerative capacity of corneal endothelial cells (CECs) differs between species; in bigger mammals, CECs are arrested in a non-proliferative state. Damage to these cells can compromise their function causing corneal opacity. Corneal transplantation is the current treatment for the recovery of clear eyesight, but the donor tissue demand is higher than the availability and there is a need to develop novel treatments. Interestingly, rabbit CECs retain a high proliferative profile and can repopulate the endothelium. There is a lack of fundamental knowledge to explain these differences. Gaining information on their transcriptomic variances could allow the identification of CEC proliferation drivers. In this study, human, sheep, and rabbit CECs are analyzed at the transcriptomic level. To understand the differences across each species, a pipeline for the analysis of pathways with different activities is generated. The results reveal that 52 pathways have different activity when comparing species with non-proliferative CECs (human and sheep) to species with proliferative CECs (rabbit). The results show that Notch and TGF- β pathways have increased activity in species with non-proliferative CECs, which might be associated with their low proliferation. Overall, this study illustrates transcriptomic pathway-level differences that can provide leads to develop novel therapies to regenerate the corneal endothelium.

Precision nutrition based on metabolic phenotype may increase the effectiveness of interventions. In this proof-of-concept study, we investigated the effect of modulating dietary macronutrient composition accord-ing to muscle insulin-resistant (MIR) or liver insulin-resistant (LIR) phenotypes on cardiometabolic health. Women and men with MIR or LIR (n = 242, body mass index [BMI] 25-40 kg/m2, 40-75 years) were random-ized to phenotype diet (PhenoDiet) group A or B and followed a 12-week high-monounsaturated fatty acid (HMUFA) diet or low-fat, high-protein, and high-fiber diet (LFHP) (PhenoDiet group A, MIR/HMUFA and LIR/LFHP; PhenoDiet group B, MIR/LFHP and LIR/HMUFA). PhenoDiet group B showed no significant im-provements in the primary outcome disposition index, but greater improvements in insulin sensitivity, glucose homeostasis, serum triacylglycerol, and C-reactive protein compared with PhenoDiet group A were observed. We demonstrate that modulating macronutrient composition within the dietary guidelines based on tissue-specific insulin resistance (IR) phenotype enhances cardiometabolic health improvements. Clinicaltrials.gov registration: NCT03708419, CCMO registration NL63768.068.17.

The metabolic axis linking the gut microbiome and heart is increasingly being researched in the context of cardiovascular health. The gut microbiota-derived trimethylamine/trimethylamine N-oxide (TMA/TMAO) pathway is responsible along this axis for the bioconversion of dietary precursors into TMA/TMAO and has been implicated in the progression of heart failure and dysbiosis through a positive-feedback interaction. Systems biology approaches in the context of researching this interaction offer an additional dimension for deepening the understanding of metabolism along the gut-heart axis. For instance, genome-scale metabolic models allow to study the functional role of pathways of interest in the context of an entire cellular or even whole-body metabolic network. In this mini review, we provide an overview of the latest findings on the TMA/TMAO super pathway and summarize the current state of knowledge in a curated pathway map on the community platform WikiPathways. The pathway map can serve both as a starting point for continual curation by the community as well as a resource for systems biology modeling studies. This has many applications, including addressing remaining gaps in our understanding of the gut-heart axis. We discuss how the curated pathway can inform a further curation and implementation of the pathway in existing whole-body metabolic models, which will allow researchers to computationally simulate this pathway to further understand its role in cardiovascular metabolism.