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Introduction The discovery of MAPK/ERK pathway mutations has revolutionized the care for patients with histiocytic neoplasms. However, mutational analysis on biopsy specimens is often limited by low tumor cellularity leading to testing failure or disease involvement of difficult-to-reach sites (e.g., central nervous system). Recently, molecular analysis of cell-free DNA (cfDNA) has shown promise as a viable tool for discovering driver mutations in multiple cancers. A recent study of mainly BRAF-mutated non-Langerhans cell histiocytosis (LCH) showed 50% concordance between tumor and plasma cfDNA analysis for BRAF-V600E. However, it is unknown whether cfDNA has a role in the evaluation of cases that harbor mutations beyond BRAF-V600E. We conducted this study to address this unanswered question using a large cohort of individuals with diverse histiocytic neoplasms from a tertiary-care institution. Methods We included 40 cases with histiocytic neoplasms with stored plasma and germline DNA in this study. Tissue molecular analysis was conducted using a targeted next generation sequencing (NGS) using commercial assays or whole exome sequencing (WES) using an in-house assay. A custom panel of 226 genes, including exonic and intronic regions, was used for the cfDNA assay in this study. To avoid cfDNA false positives, germline mutations identified from normal DNA sequencing were filtered using a BostonGene ®-developed error reduction algorithm.The total length of the analyzed genomic regions was 1.56 MB. For samples with an input greater than 30 ng, a 0.2% variant allele frequency (VAF) limit of detection (LOD) was used; a 0.4% VAF LOD was used for samples less than 30 ng. Results The final analysis cohort included 38 patients with histiocytic neoplasms after exclusion of 2 cases (failure of germline DNA library preparation and mismatch of germline and somatic DNA, respectively). Disease types included Erdheim-Chester disease (ECD; n=13, 34%), Langerhans cell histiocytosis (LCH; n=13, 34%), and Rosai-Dorfman disease (RDD; n=12, 32%). 24 cases were multisystem (63%), and the remaining were single-system. Commonly involved organs included bone (n=25, 66%), kidney (n=12, 32%), skin (n=8, 21%), central nervous system (n=7, 18%), and pituitary (n=7, 18%). Most cases (n=31, 82%) underwent plasma collection pre-treatment, 5 cases underwent collection after histiocytosis-directed therapy, and 2 while on treatment. Tissue NGS/WES data were available for 28 (74%) cases; 5 cases (13%) had insufficient tissue cellularity, and 5 (13%) did not undergo any tissue sequencing. Among those who underwent successful tissue sequencing assays, the most common common driver alterations was BRAF V600E (n=5, 26%). Other alterations included those in MAP2K1 (n=4, 21%), BRAF-fusions (n=3, 10%; partners UBDT2, RNF11, and LMTK2, respectively), and single cases of KRAS, NRAS and BRAF indel, respectively. cfDNA analysis showed at least one variant in 23 cases (60%). Correlation between tissue and cfDNA for known driver mutations was poor and concordant findings were only seen in one case with ECD harboring BRAF V600E in tissue as well as plasma (VAF 0.5%). Among the 5 cases where tissue mutational analysis had failed, cfDNA showed mutations in MUTYH, PTCH2, NOTCH3 SDHD, and TMEM127, respectively (Figure 1). Among the 5 cases where tissue molecular assessment could not be undertaken due to various reasons, cfDNA showed alterations in 4 cases, encompassing NOTCH1, TET2, BRCA1, MSH6, PIK3CD, and FUS genes. Conclusions In a large cohort of adults with diverse histiocytic neoplasms, we found poor correlation between tumor and plasma cfDNA molecular findings. The reason for the lack of correlation may be related to low tumor shedding especially among non- BRAF V600E cases. cfDNA analysis may have a role to identify potential drivers of pathogenesis among cases that are unable to successfully undergo tissue molecular analysis. Further studies are underway to characterize other novel alterations that were discovered in the cfDNA analysis.

Background: Anaplastic large cell lymphomas (ALCLs) are CD30-positive T-cell lymphomas that share pathologic features but differ in clinical presentation, outcome, and molecular features. The World Health Organization (WHO) and International Consensus Classification (ICC) classify ALCLs by presence or absence of ALK rearrangements (R) and clinical presentation (systemic, cutaneous [c], or breast implant-associated [BIA]). ICC, but not WHO, recognizes DUSP22-R as defining a new genetic subtype of ALK- ALCL. The classifications otherwise do not reflect additional molecular heterogeneity in genetics (e.g., TP63-R) or therapeutic vulnerabilities (e.g., JAK-STAT3 pathway activation). Methods: ALCLs (N=689) underwent expert consensus review (WHO/ICC) through the Lymphoma/Leukemia Molecular Profiling Project (LLMPP). All cases also underwent genetic subtyping (ALK, DUSP22, TP63, and triple-negative [TN]) using fluorescence in situ hybridization (FISH) and immunohistochemistry (IHC), as well as IHC for phospho-STAT3 Tyr705 (pSTAT3). RNAseq was performed and evaluable in 393 cases; the remaining cases had insufficient tissue, tumor content, RNA yield or quality, and/or sequencing data quality. Sequenced and non-sequenced sub-cohorts had similar demographics and subtype distribution. Results: Unsupervised gene expression profiling (GEP) identified 2 main molecular types of ALCL. Type I ALCLs predominantly included ALK+ ALCLs, BIA-ALCLs, and a subset of TN ALCLs (designated TN-I), whereas Type II ALCLs predominantly included ALCLs with DUSP22-R, TP63-R, or both (double-hit; DH), and the remaining TN ALCLs (TN-II). Type I ALCLs were strongly associated with pSTAT3 expression (74.2±26.4% positive malignant cells vs 9.9±22.7% for Type II; P<0.0001). An independently derived pSTAT3 staining threshold of 30% assigned Type I vs II with 91% accuracy. A third cluster of ALCLs, mostly cALCL, showed an epithelial GEP signature rather than a lymphoma signature; these cases were assigned to Types I or II based on pSTAT3 IHC. Distinct sub-signatures were identified for ALK+, DUSP22-R, TP63-R, and BIA ALCL (Fig. 1), but not ALK- ALCL or cALCL. Gene set enrichment analysis showed Type I ALCLs to be enriched for JAK-STAT3 signaling genes (normalized enrichment score [NES], 2.22; FDR<0.0001) and related pathways, such as TNFα-NFκB signaling (NES, 2.21; FDR<0.0001). In contrast, Type II ALCLs were enriched for cell cycle, DNA repair, epigenetic, and metabolic pathway genes, but not for major tyrosine kinase-mediated signaling pathway genes. Enriched epigenetic pathways included chromatin modifying enzymes (NES, -1.86; FDR=0.002) and histone methylation (NES, -1.71; FDR=0.002). EZH2 was the most overexpressed gene in Type II ALCLs (fold-change, 7.74; FDR=8.84×10 -306). At the protein level, EZH2 IHC H-scores were 275±45 in Type II and 168±70 in Type I ALCLs (P<0.0001); H3K27me3 H-scores were 170±81 and 76±63, respectively (P<0.001). The top metabolic gene set involved cholesterol biosynthesis (NES, -1.88; FDR=0.002). Overall survival (OS) data were available in 257 systemic ALCL patients (145 sequenced and 112 non-sequenced; cALCL and BIA-ALCL were excluded). Non-sequenced TN ALCLs were assigned to TN-I or TN-II using pSTAT3 IHC. The results supported earlier data indicating favorable prognosis of DUSP22-R ALCL (5 y OS, 95%) and ALK+ ALCL (87%), intermediate prognosis of TN ALCL (TN-I, 52% and TN-II, 38%; P=NS), and poor prognosis of TP63-R/DH ALCL (0%)(P<0.0001; Fig. 2). Conclusions: Two overarching molecular types of ALCL exist, predominantly associated with the presence (Type I) or absence (Type II) of the JAK-STAT3 signaling program. Distinct GEP signatures exist for ALK+ ALCL and BIA-ALCL (predominantly Type I), and DUSP22-R ALCL and TP63-R ALCL (predominantly Type II). TN ALCLs lacking ALK-R, DUSP22-R, and TP63-R can be stratified into TN-I and TN-II subtypes. pSTAT3 IHC has >90% accuracy as a surrogate for GEP-based subtyping. ALK- ALCL and cALCL cluster by molecular subtype rather than by defining GEP signatures. Type II ALCLs are enriched for targetable epigenetic and metabolic pathways, including EZH2/histone methylation and cholesterol biosynthesis. This molecular classification is diagnostically, prognostically, and potentially therapeutically relevant, and can be applied using FISH and IHC in routine practice and in the clinical trial setting.

Purpose: The understanding of cardiac-involved ECD (ECD-CV) and how this affects outcomes and pre-existing diseases remains limited. We aimed to determine the association, burden, and severity of pre-existing and de novo cardiovascular (CV) comorbidities with ECD-CV compared to patients (pts) without cardiac-involved ECD (ECD-noCV). Methods: Records of pts with ECD diagnosed from Jan-1990 to Dec-2021, consecutively seen at Mayo Clinic, AZ, FL, and MN were reviewed. Cardiac involvement was diagnosed by imaging. CV comorbidities were captured before and after ECD diagnosis. CTCAE v3.0 based grading system was used to assess CV comorbidities which graded the conditions as mild (grade 1), moderate (grade 2), severe (grade 3), and life-threatening or disabling (grade 4). Chi-square test was used to determine if having ECD-CV worsens pre-existing CV comorbidities in pts with ECD. As per the established methods, the cumulative CV disease burden was defined after considering 8 CV morbidities that are known to have direct structural and functional implications on the heart, including hypertension (HTN), coronary artery disease (CAD), myocardial infarction (MI), congestive heart failure (CHF), atrial fibrillation (afib), pericardial effusion, valvular disease, and conduction disorders. A composite CV morbidity grade was assigned based on the highest grade in one of the 8 CV comorbidities (Oeffinger, NEJM, 2006). Lastly, a multivariant analysis was conducted using the presence of BRAFV600E mutation, smoking, age ≥ 60 years (yr), conventional vs targeted therapy, and ECD-CV in pts with a composite grade of 4. Results: Among 106 ECD pts, 38% (n=40) had cardiac involvement. The median age at diagnosis of ECD was 57 yr (range: 49-67); 61% were males. The median follow-up was 5 yr (95% CI: 3.5-6.1), and 4.1 yr (95% CI: 3.2-6.5) for ECD-CV and ECD-noCV pts, respectively p=0.92. The median time of CV diagnoses for the entire cohort before and after ECD diagnosis was 4.8 yr (range: 0.06-42.5) and 3.4 yr (range: 0.05-18.7), respectively. BRAFV600E mutation was present in 65% (n=26) of ECD-CV vs 42% (n=28) of ECD-noCV, p=0.02. Eight pts with ECD-CV died; one from sudden cardiac death, while 9 ECD-noCV pts died, p=0.39. Smoking was present in 43% (n=18) of ECD-CV pts compared to 24% with ECD-noCV (n=16), p=0.05. In comparison to ECD-noCV pts, increased prevalence of pre-existing HTN [59% (n=23) vs 35% (n=23), p=0.016] and MI [10% (n=4) vs 2% (n=1), p=0.046] was seen in ECD-CV. There was no difference in hyperlipidemia, diabetes mellitus, CAD, CHF, valvular disease, afib, and conduction disorders among the two cohorts. After ECD diagnosis, de novo diagnosis of hyperlipidemia [67% (n=26) vs 38% (n=25); p=0.004] and CHF [35% (n=14) vs 7% (n=5); p=<0.001] was seen more frequently in ECD-CV pts compared to ECD-noCV. Following the diagnosis of ECD, the severity of pre-existing conditions did not change in pts with or without ECD-CV. ECD-CV pts had a greater cumulative CV disease burden as the total number of CV morbidities was greater in ECD-CV pts both before and after ECD diagnosis (Table 1). Additionally, pts with ECD-CV had greater severity of CV morbidity (composite grade ≥4) than ECD-noCV before (35% v 3%; p=<0.001) and after (42.5% vs 7.6%; p=<0.001) ECD diagnosis. The composite grade of 4 before ECD diagnosis was most attributable to pericardial effusion (42% in pts with ECD-CV vs 0% in pts with ECD-noCV) and CAD (50% in pts with ECD-CV vs 100% in pts with ECD-noCV); after ECD diagnosis pericardial effusion (42% in pts with ECD-CV vs 0% in pts with ECD-noCV) and CAD (41% in pts with ECD-CV vs 100% in pts with ECD-noCV). After considering BRAFV600E mutation, age ≥60, smoking, ECD-CV, and first-line therapy (conventional vs targeted therapy), ECD-CV was the only factor independently associated with a composite grade of ≥4, before (OR 25.6, 95% CI: 4.8-137) and after (OR 9.7, 95% CI: 3.0-30.8) ECD diagnosis. Nonetheless, smoking, age >60, and ECD-CV were independent factors associated when considered a composite grade of ≥3, before and after ECD diagnosis. Conclusion: ECD-CV did not prognosticate pts and did not worsen the pre-existing CV conditions compared to pts with ECD-noCV. However, ECD-CV pts had a higher cumulative CV disease burden and a higher grade of pre-existing and de novo CV morbidities compared to ECD-noCV. The presence of cardiac involvement in ECD was independently associated with a severe cumulative CV disease burden grade.

Introduction: Waldenström macroglobulinemia (WM) is a rare B-cell lymphoma that may be preceded by an asymptomatic IgM-monoclonal gammopathy of undetermined significance (MGUS). The mechanisms underlying the progression from IgM-MGUS to WM remain to be fully elucidated; however, the stepwise accumulation of genomic abnormalities has been suggested as a potential driver. Currently, the role of epigenetic regulation of DNA remains underexplored in this disease spectrum. Aberrant DNA methylation is a hallmark of oncogenesis that plays an important role in hematologic malignancies. The aim of this study was to assess differential DNA methylation in WM compared to IgM-MGUS and identify hyper- and hypomethylated pathways that may alter key cellular functions. Methods: This study included 15 patients with WM and 6 with IgM-MGUS. Bone marrow samples were prospectively collected and CD19+ and/or CD138+ B cells were positively selected. Subsequently, genome-wide DNA methylation analysis was performed. CpG methylation ratios were segmented into 200-bp regions and differentially methylated regions (DMRs) comparing WM to IgM-MGUS were identified. DMRs with a Q-value <0.05 and absolute methylation difference of ≥20% were considered significant and utilized for analysis. DMRs were annotated according to genomic regions of interest (promotors, 3'UTR, 5'UTR, introns, exons, CpG islands, CpG shores). Next, genes with significant promotor hyper- or hypomethylation were assessed using the Ingenuity Pathway Analysis. Pathways with a corrected p-value<0.05 were considered statistically significant and a Z-value was calculated based on the degree of differential methylation. Results: Genome-wide DNA methylation analysis revealed a significant number of DMRs (n= 15691, hyper: 8248; hypo: 7443) in WM compared to IgM-MGUS. Assessing genomic regions, promotors (hyper: 1379; hypo: 2403), introns (hyper: 1548; hypo: 2292), CpG shores (hyper: 587; hypo: 849) and 3'UTR (hyper: 66; hypo: 193) regions were observed to have a significantly greater number of hypomethylated DMRs (all comparisons, p<0.001) in WM compared to IgM-MGUS (Figure A). While exons (hyper: 1686; hypo: 1378), CpG islands (hyper: 2128; hypo: 82), and 5'UTR (hyper: 854; hypo: 246) regions had a significantly greater number of hypermethylated DMRs (all comparisons, p<0.001) (Figure A). Next, promotor methylation-based pathway analysis revealed differential methylation of multiple cellular pathways important in WM pathogenesis (Figure B). These included pathways involved in intracellular signaling and the regulation of cellular proliferation, such as the STAT3 and CXCR4 pathways which were hypomethylated, and the PTEN signaling pathway which was hypermethylated. Of interest, we have previously demonstrated the transcription factor, STAT3, to have an increased expression in WM and to be implicated in IgM secretion (Elsawa, 2011). Next, multiple cytokine signaling pathways were observed to be hypomethylated in WM compared to IgM-MGUS including members of the interleukin (IL) family (IL-1, IL-8, IL-15, IL-23), VEGF, and TGF-β. Of relevance, previous studies have demonstrated the elevation of IL-8, IL-15, and increased expression of angiogenic cytokines, including VEGF, in patients with WM (Lewicki, 2010; Anagnostopoulos, 2007). Furthermore, our group has also shown miRNA-based epigenetic regulation of IL-8 and IL-15 in WM compared to IgM-MGUS (Chohan, 2023). Lastly, several pathways critical in the regulation of the cell structure and the extracellular matrix (ECM) were found to be hypomethylated including the FGF, actin cytoskeleton, PAK, and FAK signaling pathways. Of note, the FGF/FGFR axis has been demonstrated to be dysregulated in WM, and its targeting has been shown to halt WM cell growth (Sacco, 2021). Conclusions: This study demonstrates differential DNA methylation of key genomic regions in WM compared to IgM-MGUS. Promotor methylation-based analysis reveals hypomethylation of several important cellular pathways involved in cytokine signaling, cell structure/ECM, and intracellular signaling. These results underscore the influence of epigenetics in the IgM-gammopathy disease spectrum and suggest the potential role of aberrant DNA methylation underlying the malignant progression from IgM-MGUS to WM.

A substantial subset of follicular lymphoma (FL) patients has an early relapse with a poor outcome. We showed that this unfavorable group displays increased expression of IRF4, dysregulated immune signaling and an immunosuppressive microenvironment. At the molecular level, IRF4 controls expression of antigen presentation and immune molecules (e.g. HLA-DR, CD40, PDL1). Furthermore, silencing of IRF4 triggers anti-lymphoma immunity ( Mondello P et al, Blood 2022;140 Suppl 1:168-169). However, little is known on the molecular mechanisms whereby IRF4 controls the crosstalk between B and T cells. To address this question, first we performed RNA-seq, ATAC-seq and CUT&TAG of active (H3K27Ac, H3K4me3) and repressive (H3K27me3, H3K4me1) histone marks in TMD8 and HBL1 (lymphoma cells with high IRF4 expression) transfected with two pairs of siIRF4 or siCtr for 72 hours. Gene expression revealed a broad change in transcription, with 432 upregulated genes and 136 downregulated genes in siIRF4 compared to siCtr. Notably, the genes with increased expression following IRF4 silencing coded for antigen presentation, immune molecules and cytokines (e.g. HLA-DR, CD86, IL6, IL10). Accordingly, we observed significant enrichment of antigen presentation, interferon and immune response signatures ( Fig 1A). Integrating RNA-seq with chromatin accessibility showed a significant shift towards transcriptional upregulation at genes nearest to upregulated ATAC peaks, with significant enrichment at enhancers (n=771). Conversely, transcriptional suppression was enriched at enhancers (n=2,458) of downregulated peaks. k-means analyses of all union peaks, generated by merging ATAC with CUT&TAG peaks, revealed a significant gain of H3K4me3, with concordant loss of H3K4me1 at enhancers with upregulated gene expression. In contrast, H3K4me3 was severely decreased at suppressed peaks. TF motif analysis revealed an enrichment for PU.1 and E2A at IRF4-bound regions, suggesting their cooperation in regulating immune signaling. Since antigen presentation and other immune molecules are critical components of the immune synapse, we explored the role of IRF4 on the interaction between germinal center (GC) B and T cells by crossing irf4 fl/fl mice with conditional deletion of irf4 ( Klein et al, Nat Immunol 2006) and Cγ 1cre mice ( Cγ 1cre; irf4 fl/fl) to induce recombination in GC B cells. After 10 days of immunization (GC reaction peak), Cγ 1cre; irf4 fl/fl and Cγ 1cre; irf4 fl/+ GC B cells showed significant increase of HLA-DR and CD40 expression compared to WT. As expected, Cγ 1cre; irf4 fl/fl mice displayed a significantly skewed light-zone:dark-zone ratio in favor of increased dark-zone, which are the cells that most reflect the action of BCL6, with concordant suppression of plasma cells. Additionally, we observed a significant increase of CD4 + T cells after partial or complete deletion of irf4, with upregulation of T FH cells and decrease of T reg cells ( Fig 1B). Notably, mice with loss of irf4 showed a significant decrease in exhausted T FH cells. To test if this effect was dependent on MHC:TCR interaction, we cocultured CD4 + T cells with TMD8 cells transfected with two siIRF4 or siCtr in presence of blocking antibodies for MHC class I, MHC class II or both. Blocking one or the other MHC class I or II partially rescued the IRF4 effect on T reg and T FH cells respectively as well as reduced anti-lymphoma cytotoxicity. Further experiments blocking IRF4-dependent IL6 and IL10 identified these two cytokines as responsible for the additional effects on T cells. To confirm this as an antigen-dependent immune response we coculture sorted GC B cells from NP-OVA-immunized Cγ 1cre; irf4 fl/fl, Cγ 1cre; irf4 fl/+ and WT mice with CSFE-labeled OVA-specific OT-II CD4 + T cells at a ratio of 2:1 in an organoid system for 5 days. We observed induced antigen specific proliferation of CD4 + T cells in the presence of Cγ 1cre; irf4 fl/fl and Cγ 1cre; irf4 fl/+ GC B cellscompared to WT,as indicated by decrease in CSFE expression . We confirmed an increase of T FH cells and a decrease of T reg cells, supporting the conclusion that IRF4 directly controls the antigen-dependent immune response . In summary, IRF4 expression in GC and lymphoma B cells regulates immune signaling with PU.1 and E2A, thereby modulating antigen-dependent immune responses with potential implications for lymphomagenesis. Future studies investigating targeting of IRF4 in lymphoma are warranted.

Abstract Background: Precursor plasma cell disorders such as monoclonal gammopathy of undetermined significance (MGUS) always precede the development of active malignancies such as multiple myeloma (MM). There is a need for novel biomarkers to identify those patients with such precursor plasma cell disorders who rapidly progress to MM. Plasma-derived extracellular vesicles (EVs) may serve as a reservoir of potential biomarkers that can shed light on the pathogenesis and disease biology in MM. Methods: This study isolated small EVs (SEVs) and large EVs (LEVs) from the platelet-poor peripheral blood plasma of MGUS (n=9) and MM (n=12) patients using the size exclusion chromatography (SEC)-based method and evaluated their proteome using a label-free proteomics workflow. Results: In total, 2,055 proteins were identified in SEVs, while 2,794 proteins were identified in LEVs. The transferrin receptor (TFRC or CD71) protein was upregulated in both populations of EVs derived from MM patients compared to MGUS patients and was of prognostic significance. Similarly, three isoforms of serum amyloid A (SAA) protein, SAA1, SAA2, and SAA4, were also highly upregulated in SEVs within MM patients relative to MGUS patients. Finally, CD40 expression was also higher within the LEVs derived from MM patients than MGUS patients. Conclusions: This study demonstrates the feasibility of successfully isolating both SEVs and LEVs from the peripheral blood of patients with plasma cell disorders and quantifying protein biomarkers within these EVs that could be of prognostic and diagnostic interest.

There is evidence that the anabolic response to exercise is blunted in skeletal muscle in older adults. Older adults also exhibit reduced mitochondrial content and lower oxidative capacity. Since mitochondria provide chemical energy for muscle protein synthesis, it is possible that age‐related changes to mitochondrial physiology may contribute to anabolic resistance. We evaluated this possibility by measuring mitochondrial function and anabolic responses to exercise in 12 young (19–34 yrs) and 12 older (67–83 yrs) adults. Serial vastus lateralis biopsies were collected during an infusion of 13 C 6 phenylalanine to measure muscle protein synthesis at baseline and 16 hours after a single bout of unaccustomed resistance exercise (unilateral knee extension, 8 sets, 10 repetitions at 70% of 1‐repetition maximum). Real‐time PCR and RNA sequencing were used to evaluate the transcriptional response to acute exercise in muscle tissue. Respiratory capacity of isolated mitochondria was measured by high‐resolution respirometry. Mitochondrial respiratory capacity was significantly lower in older adults (4.67±0.47 pmol/s/ug) compared to young (6.60±0.70 pmol/s/ug, p=0.024). Postabsorptive protein synthesis rates were similar in young and old for mixed muscle (Y: 0.067±0.005 %/hr, O: 0.104±0.030 %/hr, p=0.13), mitochondrial (Y: 0.076±0.014 %/hr, O: 0.089±0.017 %/hr, p=0.58), and myofibrillar fractions (Y: 0.073±0.005 %/hr, O: 0.072±0.015 %/hr, p=0.94). Exercise increased protein synthesis similarly in young and old for mixed muscle (Fold changes Y: 1.45±0.16, O: 1.46±0.18, p=0.98), mitochondrial (Y: 0.90±0.28, O: 1.74±0.41, p=0.11), and myofibrillar (Y: 1.35±0.13, O: 1.37±0.18, p=0.93). These data demonstrate older adults have lower mitochondrial respiratory capacity yet exhibit similar anabolic responses to resistance exercise compared to young. Protein synthesis does not appear limited by the decreased mitochondrial capacity with age.

We investigated the link between enhancement of SI (by hyperinsulinemic–euglycemic clamp) and muscle metabolites after 12 weeks of aerobic (high-intensity interval training [HIIT]), resistance training (RT), or combined training (CT) exercise in 52 lean healthy individuals. Muscle RNA sequencing revealed a significant association between SI after both HIIT and RT and the branched-chain amino acid (BCAA) metabolic pathway. Concurrently with increased expression and activity of branched-chain ketoacid dehydrogenase enzyme, many muscle amino metabolites, including BCAAs, glutamate, phenylalanine, aspartate, asparagine, methionine, and γ-aminobutyric acid, increased with HIIT, supporting the substantial impact of HIIT on amino acid metabolism. Short-chain C3 and C5 acylcarnitines were reduced in muscle with all three training modes, but unlike RT, both HIIT and CT increased tricarboxylic acid metabolites and cardiolipins, supporting greater mitochondrial activity with aerobic training. Conversely, RT and CT increased more plasma membrane phospholipids than HIIT, suggesting a resistance exercise effect on cellular membrane protection against environmental damage. Sex and age contributed modestly to the exercise-induced changes in metabolites and their association with cardiometabolic parameters. Integrated transcriptomic and metabolomic analyses suggest various clusters of genes and metabolites are involved in distinct effects of HIIT, RT, and CT. These distinct metabolic signatures of different exercise modes independently link each type of exercise training to improved SI and cardiometabolic risk. Article Highlights We aimed to understand the link between skeletal muscle metabolites and cardiometabolic health after exercise training. Although aerobic, resistance, and combined exercise training each enhance muscle insulin sensitivity as well as other cardiometabolic parameters, they disparately alter amino and citric acid metabolites as well as the lipidome, linking these metabolomic changes independently to the improvement of cardiometabolic risks with each exercise training mode. These findings reveal an important layer of the unique exercise mode–dependent changes in muscle metabolism, which may eventually lead to more informed exercise prescription for improving SI.

Abstract Objectives Diagnosis of light chain amyloidosis (AL) requires demonstration of amyloid deposits in a tissue biopsy followed by appropriate typing. Previous studies demonstrated increased dimerization of monoclonal serum free light chains (FLCs) as a pathological feature of AL. To further examine the pathogenicity of FLC, we aimed at testing amino acid sequence homology between circulating and deposited light chains (LCs). Methods Matched tissue biopsy and serum of 10 AL patients were subjected to tissue proteomic amyloid typing and nephelometric FLC assay, respectively. Serum FLC monomers (M) and dimers (D) were analyzed by Western blotting (WB) and mass spectrometry (MS). Results WB of serum FLCs showed predominance of either κ or λ type, in agreement with the nephelometric assay data. Abnormal FLC M–D patterns typical of AL amyloidosis were demonstrated in 8 AL-λ patients and in one of two AL-κ patients: increased levels of monoclonal FLC dimers, high D/M ratio values of involved FLCs, and high ratios of involved to uninvolved dimeric FLCs. MS of serum FLC dimers showed predominant constant domain sequences, in concordance with the tissue proteomic amyloid typing. Most importantly, variable domain sequence homology between circulating and deposited LC species was demonstrated, mainly in AL-λ cases. Conclusions This is the first study to demonstrate homology between circulating FLCs and tissue-deposited LCs in AL-λ amyloidosis. The applied methodology can facilitate studying the pathogenicity of circulating FLC dimers in AL amyloidosis. The study also highlights the potential of FLC monomer and dimer analysis as a non-invasive screening tool for this disease.