Polygenic subtype identified in ACCORD trial displays a favorable type 2 diabetes phenotype in the UKBiobank population.

INTRODUCTION: We previously identified a genetic subtype (C4) of type 2 diabetes (T2D), benefitting from intensive glycemia treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Here, we characterized the population of patients that met the C4 criteria in the UKBiobank cohort. RESEARCH DESIGN AND METHODS: Using our polygenic score (PS), we identified C4 individuals in the UKBiobank and tested C4 status with risk of developing T2D, cardiovascular disease (CVD) outcomes, and differences in T2D medications. RESULTS: C4 individuals were less likely to develop T2D, were slightly older at T2D diagnosis, had lower HbA1c values, and were less likely to be prescribed T2D medications (P < .05). Genetic variants in MAS1 and IGF2R, major components of the C4 PS, were associated with fewer overall T2D prescriptions. CONCLUSION: We have confirmed C4 individuals are a lower risk subpopulation of patients with T2D.

HHEX promotes myeloid transformation in cooperation with mutant ASXL1.

Additional sex combs-like 1 (ASXL1), an epigenetic modulator, is frequently mutated in myeloid neoplasms. Recent analyses of mutant ASXL1 conditional knockin (ASXL1-MT-KI) mice suggested that ASXL1-MT alone is insufficient for myeloid transformation. In our previous study, we used retrovirus-mediated insertional mutagenesis, which exhibited the susceptibility of ASXL1-MT-KI hematopoietic cells to transform into myeloid leukemia cells. In this screening, we identified the hematopoietically expressed homeobox (HHEX) gene as one of the common retrovirus integration sites. In this study, we investigated the potential cooperation between ASXL1-MT and HHEX in myeloid leukemogenesis. Expression of HHEX enhanced proliferation of ASXL1-MT-expressing HSPCs by inhibiting apoptosis and blocking differentiation, whereas it showed only modest effect in normal HSPCs. Moreover, ASXL1-MT and HHEX accelerated the development of RUNX1-ETO9a and FLT3-ITD leukemia. Conversely, HHEX depletion profoundly attenuated the colony-forming activity and leukemogenicity of ASXL1-MT-expressing leukemia cells. Mechanistically, we identified MYB and ETV5 as downstream targets for ASXL1-MT and HHEX by using transcriptome and chromatin immunoprecipitation-next-generation sequencing analyses. Moreover, we found that expression of ASXL1-MT enhanced the binding of HHEX to the promoter loci of MYB or ETV5 via reducing H2AK119ub. Depletion of MYB or ETV5 induced apoptosis or differentiation in ASXL1-MT-expressing leukemia cells, respectively. In addition, ectopic expression of MYB or ETV5 reversed the reduced colony-forming activity of HHEX-depleted ASXL1-MT-expressing leukemia cells. These findings indicate that the HHEX-MYB/ETV5 axis promotes myeloid transformation in ASXL1-mutated preleukemia cells.

Comprehensive database and evolutionary dynamics of U12-type introns.

During nuclear maturation of most eukaryotic pre-messenger RNAs and long non-coding RNAs, introns are removed through the process of RNA splicing. Different classes of introns are excised by the U2-type or the U12-type spliceosomes, large complexes of small nuclear ribonucleoprotein particles and associated proteins. We created intronIC, a program for assigning intron class to all introns in a given genome, and used it on 24 eukaryotic genomes to create the Intron Annotation and Orthology Database (IAOD). We then used the data in the IAOD to revisit several hypotheses concerning the evolution of the two classes of spliceosomal introns, finding support for the class conversion model explaining the low abundance of U12-type introns in modern genomes.

Host metabolome predicts the severity and onset of acute toxicities induced by CAR T-cell therapy.

Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy is a highly effective treatment option for patients with relapsed/refractory large B-cell lymphoma. However, widespread use is deterred by the development of clinically significant acute inflammatory toxicities, including cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS), that induce significant morbidity and require close monitoring. Identification of host biochemical signatures that predict the severity and time-to-onset of CRS and ICANS may assist patient stratification to enable timely mitigation strategies. Here, we report pretreatment host metabolites that are associated with CRS and ICANS induced by axicabtagene ciloleucel or tisagenlecleucel therapy. Both untargeted metabolomics analysis and validation using targeted assays revealed a significant association between the abundance of specific pretreatment biochemical entities and an increased risk and/or onset of clinically significant CRS (q < .1) and ICANS (q < .25). Higher pretreatment levels of plasma glucose and lower levels of cholesterol and glutamate were associated with a faster onset of CRS. In contrast, low baseline levels of the amino acids proline and glycine and the secondary bile acid isoursodeoxycholate were significantly correlated with clinically significant CRS. Lower concentration of the amino acid hydroxyproline was associated with higher grade and faster onset of ICANS, whereas low glutamine was negatively correlated with faster development of ICANS. Overall, our data indicate that the pretreatment host metabolome has biomarker potential in determining the risk of clinically significant CRS and ICANS, and may be useful in risk stratification of patients before anti-CD19 CAR T-cell therapy.

Molecular subtypes of epilepsy associated with post-surgical seizure recurrence.

Approximately 50% of individuals who undergo resective epilepsy surgery experience seizure recurrence. The heterogenous post-operative outcomes are not fully explained by clinical, imaging and electrophysiological variables. We hypothesized that molecular features may be useful in understanding surgical response, and that individuals with epilepsy can be classified into molecular subtypes that are associated with seizure freedom or recurrence after surgical resection. Pre-operative blood samples, brain tissue and post-operative seizure outcomes were collected from a cohort of 40 individuals with temporal lobe epilepsy, 23 of whom experienced post-operative seizure recurrence. Messenger RNA and microRNA extracted from the blood and tissue samples were sequenced. The messenger RNA and microRNA expression levels from the blood and brain were each subjected to a novel clustering approach combined with multiple logistic regression to separate individuals into genetic clusters that identify novel subtypes associated with post-operative seizure outcomes. We then compared the microRNAs and messenger RNAs from patient blood and brain tissue that were significantly associated with each subtype to identify signatures that are similarly over- or under-represented for an outcome and more likely to represent endophenotypes with common molecular aetiology. These target microRNAs and messenger RNAs were further characterized by pathway analysis to assess their functional role in epilepsy. Using blood-derived microRNA and messenger RNA expression levels, we identified two subtypes of epilepsy that were significantly associated with seizure recurrence (clusters A1 and B4) (adjusted P < 0.20). A total of 551 microRNAs and 2486 messenger RNAs were associated with clusters A1 and B4, respectively (adjusted P < 0.05). Clustering of brain-tissue messenger RNA expression levels revealed an additional subtype (C2) associated with seizure recurrence that had high overlap of dysregulated messenger RNA transcripts with cluster B4. Clusters A1, B4 and C2 also shared significant overlap of subjects, which altogether suggests a coordinated mechanism by which microRNA and messenger RNA transcripts may be related to seizure recurrence. Epileptic subtypes A1, B4 and C2 reveal both known and novel microRNA and messenger RNA targets in seizure recurrence. Furthermore, targets identified in A1 and B4 are quantifiable in pre-operative blood samples and could potentially serve as biomarkers for surgical resection outcomes.

Characterization of Salivary and Plasma Metabolites as Biomarkers for HCC: A Pilot Study.

(1) Background: The incidence of hepatocellular carcinoma (HCC) is rising, and current screening methods lack sensitivity. This study aimed to identify distinct and overlapping metabolites in saliva and plasma that are significantly associated with HCC. (2) Methods: Saliva samples were collected from 42 individuals (HCC = 16, cirrhosis = 12, healthy = 14), with plasma samples from 22 (HCC = 14, cirrhosis = 2, healthy = 6). We performed untargeted mass spectrometry on blood and plasma, tested metabolites for associations with HCC or cirrhosis using a logistic regression, and identified enriched pathways with Metaboanalyst. Pearson's correlation was employed to test for correlations between salivary and plasma metabolites. (3) Results: Six salivary metabolites (1-hexadecanol, isooctanol, malonic acid, N-acetyl-valine, octadecanol, and succinic acid) and ten plasma metabolites (glycine, 3-(4-hydroxyphenyl)propionic acid, aconitic acid, isocitric acid, tagatose, cellobiose, fucose, glyceric acid, isocitric acid, isothreonic acid, and phenylacetic acid) were associated with HCC. Malonic acid was correlated between the paired saliva and plasma samples. Pathway analysis highlighted deregulation of the 'The Citric Acid Cycle' in both biospecimens. (4) Conclusions: Our study suggests that salivary and plasma metabolites may serve as independent sources for HCC detection. Despite the lack of correlation between individual metabolites, they converge on 'The Citric Acid Cycle' pathway, implicated in HCC pathogenesis.

Genetic variations that influence paclitaxel pharmacokinetics and intracellular effects that may contribute to chemotherapy-induced neuropathy: A narrative review.

Taxanes, particularly paclitaxel and docetaxel, are chemotherapeutic agents commonly used to treat breast cancers. A frequent side effect is chemotherapy-induced peripheral neuropathy (CIPN) that occurs in up to 70% of all treated patients and impacts the quality of life during and after treatment. CIPN presents as glove and stocking sensory deficits and diminished motor and autonomic function. Nerves with longer axons are at higher risk of developing CIPN. The causes of CIPN are multifactorial and poorly understood, limiting treatment options. Pathophysiologic mechanisms can include: (i) disruptions of mitochondrial and intracellular microtubule functions, (ii) disruption of axon morphology, and (iii) activation of microglial and other immune cell responses, among others. Recent work has explored the contribution of genetic variation and selected epigenetic changes in response to taxanes for any insights into their relation to pathophysiologic mechanisms of CIPN20, with the hope of identifying predictive and targetable biomarkers. Although promising, many genetic studies of CIPN are inconsistent making it difficult to develop reliable biomarkers of CIPN. The aims of this narrative review are to benchmark available evidence and identify gaps in the understanding of the role genetic variation has in influencing paclitaxel's pharmacokinetics and cellular membrane transport potentially related to the development of CIPN.

A multimodal analysis of genomic and RNA splicing features in myeloid malignancies.

RNA splicing dysfunctions are more widespread than what is believed by only estimating the effects resulting by splicing factor mutations (SFMT) in myeloid neoplasia (MN). The genetic complexity of MN is amenable to machine learning (ML) strategies. We applied an integrative ML approach to identify co-varying features by combining genomic lesions (mutations, deletions, and copy number), exon-inclusion ratio as measure of RNA splicing (percent spliced in, PSI), and gene expression (GE) of 1,258 MN and 63 normal controls. We identified 15 clusters based on mutations, GE, and PSI. Different PSI levels were present at various extents regardless of SFMT suggesting that changes in RNA splicing were not strictly related to SFMT. Combination of PSI and GE further distinguished the features and identified PSI similarities and differences, common pathways, and expression signatures across clusters. Thus, multimodal features can resolve the complex architecture of MN and help identifying convergent molecular and transcriptomic pathways amenable to therapies.

TET2 mutations as a part of DNA dioxygenase deficiency in myelodysplastic syndromes.

Decrease in DNA dioxygenase activity generated by TET2 gene family is crucial in myelodysplastic syndromes (MDS). The general downregulation of 5-hydroxymethylcytosine (5-hmC) argues for a role of DNA demethylation in MDS beyond TET2 mutations, which albeit frequent, do not convey any prognostic significance. We investigated TETs expression to identify factors which can modulate the impact of mutations and thus 5-hmC levels on clinical phenotypes and prognosis of MDS patients. DNA/RNA-sequencing and 5-hmC data were collected from 1665 patients with MDS and 91 controls. Irrespective of mutations, a significant fraction of MDS patients exhibited lower TET2 expression, whereas 5-hmC levels were not uniformly decreased. In searching for factors explaining compensatory mechanisms, we discovered that TET3 was upregulated in MDS and inversely correlated with TET2 expression in wild-type cases. Although TET2 was reduced across all age groups, TET3 levels were increased in a likely feedback mechanism induced by TET2 dysfunction. This inverse relationship of TET2 and TET3 expression also corresponded to the expression of L-2-hydroxyglutarate dehydrogenase, involved in agonist/antagonist substrate metabolism. Importantly, elevated TET3 levels influenced the clinical phenotype of TET2 deficiency whereby the lack of compensation by TET3 (low TET3 expression) was associated with poor outcomes of TET2 mutant carriers.

Germline DDX41 mutations cause ineffective hematopoiesis and myelodysplasia.

DDX41 mutations are the most common germline alterations in adult myelodysplastic syndromes (MDSs). The majority of affected individuals harbor germline monoallelic frameshift DDX41 mutations and subsequently acquire somatic mutations in their other DDX41 allele, typically missense R525H. Hematopoietic progenitor cells (HPCs) with biallelic frameshift and R525H mutations undergo cell cycle arrest and apoptosis, causing bone marrow failure in mice. Mechanistically, DDX41 is essential for small nucleolar RNA (snoRNA) processing, ribosome assembly, and protein synthesis. Although monoallelic DDX41 mutations do not affect hematopoiesis in young mice, a subset of aged mice develops features of MDS. Biallelic mutations in DDX41 are observed at a low frequency in non-dominant hematopoietic stem cell clones in bone marrow (BM) from individuals with MDS. Mice chimeric for monoallelic DDX41 mutant BM cells and a minor population of biallelic mutant BM cells develop hematopoietic defects at a younger age, suggesting that biallelic DDX41 mutant cells are disease modifying in the context of monoallelic DDX41 mutant BM.

Salivary Metabolites are Promising Non-Invasive Biomarkers of Hepatocellular Carcinoma and Chronic Liver Disease.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading causes of cancer mortality worldwide. Improved tools are needed for detecting HCC so that treatment can begin as early as possible. Current diagnostic approaches and existing biomarkers, such as alpha-fetoprotein (AFP) lack sensitivity, resulting in too many false negative diagnoses. Machine-learning may be able to identify combinations of biomarkers that provide more robust predictions and improve sensitivity for detecting HCC. We sought to evaluate whether metabolites in patient saliva could distinguish those with HCC, cirrhosis, and those with no documented liver disease. METHODS AND RESULTS: We tested 125 salivary metabolites from 110 individuals (43 healthy, 37 HCC, 30 cirrhosis) and identified 4 metabolites that displayed significantly different abundance between groups (FDR P <.2). We also developed four tree-based, machine-learning models, optimized to include different numbers of metabolites, that were trained using cross-validation on 99 patients and validated on a withheld test set of 11 patients. A model using 12 metabolites -octadecanol, acetophenone, lauric acid, 1-monopalmitin, dodecanol, salicylaldehyde, glycyl-proline, 1-monostearin, creatinine, glutamine, serine and 4-hydroxybutyric acid- had a cross-validated sensitivity of 84.8%, specificity of 92.4% and correctly classified 90% of the HCC patients in the test cohort. This model outperformed previously reported sensitivities and specificities for AFP (20-100ng/ml) (61%, 86%) and AFP plus ultrasound (62%, 88%). CONCLUSIONS AND IMPACT: Metabolites detectable in saliva may represent products of disease pathology or a breakdown in liver function. Notably, combinations of salivary metabolites derived from machine-learning may serve as promising non-invasive biomarkers for the detection of HCC.

Functional analyses of human LUC7-like proteins involved in splicing regulation and myeloid neoplasms.

Vertebrates have evolved three paralogs, termed LUC7L, LUC7L2, and LUC7L3, of the essential yeast U1 small nuclear RNA (snRNA)-associated splicing factor Luc7p. We investigated the mechanistic and regulatory functions of these putative splicing factors, of which one (LUC7L2) is mutated or deleted in myeloid neoplasms. Protein interaction data show that all three proteins bind similar core but distinct regulatory splicing factors, probably mediated through their divergent arginine-serine-rich domains, which are not present in Luc7p. Knockdown of each factor reveals mostly unique sets of significantly dysregulated alternative splicing events dependent on their binding locations, which are largely non-overlapping. Notably, knockdown of LUC7L2 alone significantly upregulates the expression of multiple spliceosomal factors and downregulates glycolysis genes, possibly contributing to disease pathogenesis. RNA binding studies reveal that LUC7L2 and LUC7L3 crosslink to weak 5' splice sites and to the 5' end of U1 snRNA, establishing an evolutionarily conserved role in 5' splice site selection.

Complex landscape of alternative splicing in myeloid neoplasms.

Myeloid neoplasms are characterized by frequent mutations in at least seven components of the spliceosome that have distinct roles in the process of pre-mRNA splicing. Hotspot mutations in SF3B1, SRSF2, U2AF1 and loss of function mutations in ZRSR2 have revealed widely different aberrant splicing signatures with little overlap. However, previous studies lacked the power necessary to identify commonly mis-spliced transcripts in heterogeneous patient cohorts. By performing RNA-Seq on bone marrow samples from 1258 myeloid neoplasm patients and 63 healthy bone marrow donors, we identified transcripts frequently mis-spliced by mutated splicing factors (SF), rare SF mutations with common alternative splicing (AS) signatures, and SF-dependent neojunctions. We characterized 17,300 dysregulated AS events using a pipeline designed to predict the impact of mis-splicing on protein function. Meta-splicing analysis revealed a pattern of reduced levels of retained introns among disease samples that was exacerbated in patients with splicing factor mutations. These introns share characteristics with "detained introns," a class of introns that have been shown to promote differentiation by detaining pro-proliferative transcripts in the nucleus. In this study, we have functionally characterized 17,300 targets of mis-splicing by the SF mutations, identifying a common pathway by which AS may promote maintenance of a proliferative state.

Spliceosomal factor mutations and mis-splicing in MDS.

Somatic, heterozygous missense and nonsense mutations in at least seven proteins that function in the spliceosome are found at high frequency in MDS patients. These proteins act at various steps in the process of splicing by the spliceosome and lead to characteristic alterations in the alternative splicing of a subset of genes. Several studies have investigated the effects of these mutations and have attempted to identify a commonly affected gene or pathway. Here, we summarize what is known about the normal function of these proteins and how the mutations alter the splicing landscape of the genome. We also summarize the commonly mis-spliced gene targets and discuss the state of mechanistic unification that has been achieved. Finally, we discuss alternative mechanisms by which these mutations may lead to disease.