Evaluation of the genetic basis of familial-associated early-onset hematologic cancers in an ancestral/ethnically diverse population.

Genetic predisposition to hematologic malignancies has historically been addressed utilizing patients recruited from clinical trials and pedigrees constructed at major treatment centers. Such efforts leave unexplored the genetic basis of variations in risk by race/ethnic group shown in population-based surveillance data where cancer registration, compulsory by law, delivers universal enrollment. To address this, we performed exome sequencing on DNA isolated from newborn bloodspots derived from sibling pairs with early-onset cancers across California in which at least one of the siblings developed a hematologic cancer, using unbiased recruitment from the full state population. We identified pathogenic/likely pathogenic (P/LP) variants among 1172 selected cancer genes that were private or present at low allele frequencies in reference populations. Within 64 subjects from 32 families, we found 9 LP variants shared between siblings, and an additional 7 such variants in singleton children (not shared with their sibling). In eight of the shared cases, the ancestral origin of the local haplotype that carries P/LP variants matched the dominant global ancestry of study participant families. This was the case for Latino sibling pairs on FLG and CBLB, non-Latino White sibling pairs in TP53 and NOD2, and a shared GATA2 variant for a non-Latino Black sibling pair. A new inherited mutation in HABP2 was identified in a sibling pair, one with diffuse large B-cell lymphoma and the other with neuroblastoma. Overall, the profile of P/LP germline variants across ancestral/ethnic groups suggests that rare alleles contributing to hematologic diseases originate within their race/ethnic origin parental populations, demonstrating the value of this discovery process in diverse, population-based registries.

Single-cell characterization of infiltrating T cells identifies novel targets for gallbladder cancer immunotherapy.

Gallbladder cancer (GBC) is among the most common malignancies of biliary tract system due to its limited treatments. The immunotherapeutic targets for T cells are appealing, however, heterogeneity of T cells hinds its further development. We systematically construct T cell atlas by single-cell RNA sequencing; and utilized the identified gene signatures of high_CNV_T cells to predict molecular subtyping towards personalized therapeutic treatments for GBC. We identified 12 T cell subtypes, where exhausted CD8+ T cells, activated/exhausted CD8+ T cells, and regulatory T cells were predominant in tumors. There appeared to be an inverse relationship between Th17 and Treg populations with Th17 levels significantly reduced, whereas Tregs were concomitantly increased. Furthermore, we first established subtyping criterion to identify three subtypes of GBC based on their pro-tumorigenic microenvironments, e.g., the type 1 group shows more M2 macrophages infiltration, while the type 2 group is infiltrated by highly exhausted CD8+ T cells, B cells and Tregs with suppressive activities. Our study provides valuable insights into T cell heterogeneity and suggests that molecular subtyping based on T cells might provide a potential immunotherapeutic strategy to improve GBC treatment.

Mind- and Body-Based Interventions Improve Glycemic Control in Patients with Type 2 Diabetes: A Systematic Review and Meta-Analysis.

Aims/Hypothesis: Only 51% of patients with type 2 diabetes achieve the hemoglobin A1c (HbA1c) <7% target. Mind and body practices have been increasingly used to improve glycemic control among patients with type 2 diabetes, but studies show inconsistent efficacy. The authors conducted a systematic review and meta-analysis to assess the association between mind and body practices, and mean change in HbA1c and fasting blood glucose (FBG) in patients with type 2 diabetes. Methods: The authors conducted a literature search of Ovid MEDLINE, Embase, and ClinicalTrials.gov seeking through June 10, 2022, published articles on mind and body practices and type 2 diabetes. Two reviewers independently appraised full text of articles. Only intervention studies were included. Reviewers extracted data for meta-analysis. Restricted maximum likelihood random-effects modeling was used to calculate the mean differences and summary effect sizes. The authors assessed heterogeneity using Cochran's Q and I2 statistics. Funnel plots were generated for each outcome to gauge publication bias. Weighted linear models were used to conduct study-level meta-regression analyses of practice frequency. Results: The authors identified 587 articles with 28 meeting the inclusion criteria. A statistically significant and clinically relevant mean reduction in HbA1c of -0.84% (95% confidence interval [CI]: -1.10% to -0.58%; p < 0.0001) was estimated. Reduction was observed in all intervention subgroups: mindfulness-based stress reduction: -0.48% (95% CI: -0.72% to -0.23%; p = 0.03), qigong: -0.66% (95% CI: -1.18% to -0.14%; p = 0.01), and yoga: -1.00% (95% CI: -1.38% to -0.63%; p < 0.0001). Meta-regression revealed that for every additional day of yoga practice per week, the raw mean HbA1c differed by -0.22% (95% CI: -0.44% to -0.003%; p = 0.046) over the study period. FBG significantly improved following mind and body practices, with overall mean difference of -22.81 mg/dL (95% CI: -33.07 to -12.55 mg/dL; p < 0.0001). However, no significant association was found between the frequency of weekly yoga practice and change in FBG over the study period. Conclusions/Interpretation: Mind and body practices are strongly associated with improvement in glycemic control in patients with type 2 diabetes. The overall mean reduction in HbA1c and FBG was clinically significant, suggesting that mind and body practices may be an effective, complementary nonpharmacological intervention for type 2 diabetes. Additional analyses revealed that the mean decrease in HbA1c was greater in studies requiring larger number of yoga practice sessions each week.

Clonal hematopoiesis and risk of prostate cancer in large samples of European ancestry men.

Little is known regarding the potential relationship between clonal hematopoiesis (CH) of indeterminate potential (CHIP), which is the expansion of hematopoietic stem cells with somatic mutations, and risk of prostate cancer, the fifth leading cause of cancer death of men worldwide. We evaluated the association of age-related CHIP with overall and aggressive prostate cancer risk in two large whole-exome sequencing studies of 75 047 European ancestry men, including 7663 prostate cancer cases, 2770 of which had aggressive disease, and 3266 men carrying CHIP variants. We found that CHIP, defined by over 50 CHIP genes individually and in aggregate, was not significantly associated with overall (aggregate HR = 0.93, 95% CI = 0.76-1.13, P = 0.46) or aggressive (aggregate OR = 1.14, 95% CI = 0.92-1.41, P = 0.22) prostate cancer risk. CHIP was weakly associated with genetic risk of overall prostate cancer, measured using a polygenic risk score (OR = 1.05 per unit increase, 95% CI = 1.01-1.10, P = 0.01). CHIP was not significantly associated with carrying pathogenic/likely pathogenic/deleterious variants in DNA repair genes, which have previously been found to be associated with aggressive prostate cancer. While findings from this study suggest that CHIP is likely not a risk factor for prostate cancer, it will be important to investigate other types of CH in association with prostate cancer risk.

Variant to function mapping at single-cell resolution through network propagation.

Genome-wide association studies in combination with single-cell genomic atlases can provide insights into the mechanisms of disease-causal genetic variation. However, identification of disease-relevant or trait-relevant cell types, states and trajectories is often hampered by sparsity and noise, particularly in the analysis of single-cell epigenomic data. To overcome these challenges, we present SCAVENGE, a computational algorithm that uses network propagation to map causal variants to their relevant cellular context at single-cell resolution. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation, applying the method to blood traits at distinct stages of human hematopoiesis, to monocyte subsets that increase the risk for severe Coronavirus Disease 2019 (COVID-19) and to intermediate lymphocyte developmental states that predispose to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Accelerated epigenetic aging in newborns with Down syndrome.

Accelerated aging is a hallmark of Down syndrome (DS), with adults experiencing early-onset Alzheimer's disease and premature aging of the skin, hair, and immune and endocrine systems. Accelerated epigenetic aging has been found in the blood and brain tissue of adults with DS but when premature aging in DS begins remains unknown. We investigated whether accelerated aging in DS is already detectable in blood at birth. We assessed the association between age acceleration and DS using five epigenetic clocks in 346 newborns with DS and 567 newborns without DS using Illumina MethylationEPIC DNA methylation array data. We compared two epigenetic aging clocks (DNAmSkinBloodClock and pan-tissue DNAmAge) and three epigenetic gestational age clocks (Haftorn, Knight, and Bohlin) between DS and non-DS newborns using linear regression adjusting for observed age, sex, batch, deconvoluted blood cell proportions, and genetic ancestry. Targeted sequencing of GATA1 was performed in a subset of 184 newborns with DS to identify somatic mutations associated with transient abnormal myelopoiesis. DS was significantly associated with increased DNAmSkinBloodClock (effect estimate = 0.2442, p < 0.0001), with an epigenetic age acceleration of 244 days in newborns with DS after adjusting for potential confounding factors (95% confidence interval: 196-292 days). We also found evidence of epigenetic age acceleration associated with somatic GATA1 mutations among newborns with DS (p = 0.015). DS was not associated with epigenetic gestational age acceleration. We demonstrate that accelerated epigenetic aging in the blood of DS patients begins prenatally, with implications for the pathophysiology of immunosenescence and other aging-related traits in DS.

Investigating DNA methylation as a mediator of genetic risk in childhood acute lymphoblastic leukemia.

Genome-wide association studies have identified a growing number of single nucleotide polymorphisms (SNPs) associated with childhood acute lymphoblastic leukemia (ALL), yet the functional roles of most SNPs are unclear. Multiple lines of evidence suggest that epigenetic mechanisms may mediate the impact of heritable genetic variation on phenotypes. Here, we investigated whether DNA methylation mediates the effect of genetic risk loci for childhood ALL. We performed an epigenome-wide association study (EWAS) including 808 childhood ALL cases and 919 controls from California-based studies using neonatal blood DNA. For differentially methylated CpG positions (DMPs), we next conducted association analysis with 23 known ALL risk SNPs followed by causal mediation analyses addressing the significant SNP-DMP pairs. DNA methylation at CpG cg01139861, in the promoter region of IKZF1, mediated the effects of the intronic IKZF1 risk SNP rs78396808, with the average causal mediation effect (ACME) explaining ~30% of the total effect (ACME P = 0.0031). In analyses stratified by self-reported race/ethnicity, the mediation effect was only significant in Latinos, explaining ~41% of the total effect of rs78396808 on ALL risk (ACME P = 0.0037). Conditional analyses confirmed the presence of at least three independent genetic risk loci for childhood ALL at IKZF1, with rs78396808 unique to non-European populations. We also demonstrated that the most significant DMP in the EWAS, CpG cg13344587 at gene ARID5B (P = 8.61 × 10-10), was entirely confounded by the ARID5B ALL risk SNP rs7090445. Our findings provide new insights into the functional pathways of ALL risk SNPs and the DNA methylation differences associated with risk of childhood ALL.

Upregulated YB-1 protein promotes glioblastoma growth through a YB-1/CCT4/mLST8/mTOR pathway.

Y-box-binding protein 1 (YB-1) is a multifunctional RNA binding protein involved in virtually every step of RNA metabolism. However, the functions and mechanisms of YB-1 in one of the most aggressive cancers, glioblastoma, are not well understood. In this study, we found that YB-1 protein was markedly overexpressed in glioblastoma and acted as a critical activator of both mTORC1 and mTORC2 signaling. Mechanistically, YB-1 bound the 5'UTR of CCT4 mRNA to promote the translation of CCT4, a component of the CCT chaperone complex, that in turn activated the mTOR signaling pathway by promoting mLST8 folding. In addition, YB-1 autoregulated its own translation by binding to its 5'UTR, leading to sustained activation of mTOR signaling. In patients with glioblastoma, high protein expression of YB-1 correlated with increased expression of CCT4 and mLST8 and activated mTOR signaling. Importantly, the administration of RNA decoys specifically targeting YB-1 in a mouse xenograft model resulted in slower tumor growth and better survival. Taken together, these findings uncover a disrupted proteostasis pathway involving a YB-1/CCT4/mLST8/mTOR axis in promoting glioblastoma growth, suggesting that YB-1 is a potential therapeutic target for the treatment of glioblastoma.

Variant to function mapping at single-cell resolution through network propagation.

With burgeoning human disease genetic associations and single-cell genomic atlases covering a range of tissues, there are unprecedented opportunities to systematically gain insights into the mechanisms of disease-causal variation. However, sparsity and noise, particularly in the context of single-cell epigenomic data, hamper the identification of disease- or trait-relevant cell types, states, and trajectories. To overcome these challenges, we have developed the SCAVENGE method, which maps causal variants to their relevant cellular context at single-cell resolution by employing the strategy of network propagation. We demonstrate how SCAVENGE can help identify key biological mechanisms underlying human genetic variation including enrichment of blood traits at distinct stages of human hematopoiesis, defining monocyte subsets that increase the risk for severe coronavirus disease 2019 (COVID-19), and identifying intermediate lymphocyte developmental states that are critical for predisposition to acute leukemia. Our approach not only provides a framework for enabling variant-to-function insights at single-cell resolution, but also suggests a more general strategy for maximizing the inferences that can be made using single-cell genomic data.

Personalized, Electronic Health Record-Integrated Decision Aid for Stroke Prevention in Atrial Fibrillation: A Small Cluster Randomized Trial and Qualitative Analysis of Efficacy and Acceptability.

BACKGROUND: Shared decision-making in cardiology is increasingly recommended to improve patient-centeredness of care. Decision aids can improve patient knowledge and decisional quality but are infrequently used in real-world practice. This mixed-methods study tests the efficacy and acceptability of a decision aid integrated into the electronic health record (Integrated Decision Aid [IDeA]) and delivered by clinicians for patients with atrial fibrillation considering options to reduce stroke risk. We aimed to determine whether the IDeA improves patient knowledge, reduces decisional conflict, and is seen as acceptable by clinicians and patients. METHODS: A small cluster randomized trial included 6 cardiovascular clinicians and 66 patients randomized either to the IDeA (HealthDecision) or usual care (clinician discretion) during a clinical encounter when stroke prevention treatment options were discussed. The primary outcome was patient knowledge of personalized stroke risk. Exploratory outcomes included decisional conflict, values concordance, trust, the presence of a shared decision-making process, and patient knowledge related to time spent using the IDeA. Additionally, we conducted semistructured interviews with clinicians and patients who used the IDeA were conducted to assess acceptability and predictions of future use. RESULTS: The IDeA significantly increased patients' knowledge of their stroke risk (odds ratio, 3.88 [95% CI, 1.39-10.78]; P<0.01]). Patients had less uncertainty about their final decision (P=0.04). There were no significant differences in values concordance, trust in clinician or shared decision-making. Despite training, each clinician used the IDeA differently. Qualitative analysis revealed patients prefer using the IDeA earlier in their diagnosis. Clinicians were satisfied with the IDeA, yet varied in the contexts in which they planned to use it in the future. CONCLUSIONS: Using an Integrated Decision Aid, or IDeA, increases patient knowledge and lessens uncertainty for decision-making around stroke prevention in atrial fibrillation. Qualitative data provide insight into potential implementation strategies in real-world practice.

Epigenetic Biomarkers of Prenatal Tobacco Smoke Exposure Are Associated with Gene Deletions in Childhood Acute Lymphoblastic Leukemia.

BACKGROUND: Parental smoking is implicated in the etiology of acute lymphoblastic leukemia (ALL), the most common childhood cancer. We recently reported an association between an epigenetic biomarker of early-life tobacco smoke exposure at the AHRR gene and increased frequency of somatic gene deletions among ALL cases. METHODS: Here, we further assess this association using two epigenetic biomarkers for maternal smoking during pregnancy-DNA methylation at AHRR CpG cg05575921 and a recently established polyepigenetic smoking score-in an expanded set of 482 B-cell ALL (B-ALL) cases in the California Childhood Leukemia Study with available Illumina 450K or MethylationEPIC array data. Multivariable Poisson regression models were used to test the associations between the epigenetic biomarkers and gene deletion numbers. RESULTS: We found an association between DNA methylation at AHRR CpG cg05575921 and deletion number among 284 childhood B-ALL cases with MethylationEPIC array data, with a ratio of means (RM) of 1.31 [95% confidence interval (CI), 1.02-1.69] for each 0.1 ß value reduction in DNA methylation, an effect size similar to our previous report in an independent set of 198 B-ALL cases with 450K array data [meta-analysis summary RM (sRM) = 1.32; 95% CI, 1.10-1.57]. The polyepigenetic smoking score was positively associated with gene deletion frequency among all 482 B-ALL cases (sRM = 1.31 for each 4-unit increase in score; 95% CI, 1.09-1.57). CONCLUSIONS: We provide further evidence that prenatal tobacco-smoke exposure may influence the generation of somatic copy-number deletions in childhood B-ALL. IMPACT: Analyses of deletion breakpoint sequences are required to further understand the mutagenic effects of tobacco smoke in childhood ALL.

Dynamically remodeled hepatic extracellular matrix predicts prognosis of early-stage cirrhosis.

Liver cirrhosis remains major health problem. Despite the progress in diagnosis of asymptomatic early-stage cirrhosis, prognostic biomarkers are needed to identify cirrhotic patients at high risk developing advanced stage disease. Liver cirrhosis is the result of deregulated wound healing and is featured by aberrant extracellular matrix (ECM) remodeling. However, it is not comprehensively understood how ECM is dynamically remodeled in the progressive development of liver cirrhosis. It is yet unknown whether ECM signature is of predictive value in determining prognosis of early-stage liver cirrhosis. In this study, we systematically analyzed proteomics of decellularized hepatic matrix and identified four unique clusters of ECM proteins at tissue damage/inflammation, transitional ECM remodeling or fibrogenesis stage in carbon tetrachloride-induced liver fibrosis. In particular, basement membrane (BM) was heavily deposited at the fibrogenesis stage. BM component minor type IV collagen α5 chain expression was increased in activated hepatic stellate cells. Knockout of minor type IV collagen α5 chain ameliorated liver fibrosis by hampering hepatic stellate cell activation and promoting hepatocyte proliferation. ECM signatures were differentially enriched in the biopsies of good and poor prognosis early-stage liver cirrhosis patients. Clusters of ECM proteins responsible for homeostatic remodeling and tissue fibrogenesis, as well as basement membrane signature were significantly associated with disease progression and patient survival. In particular, a 14-gene signature consisting of basement membrane proteins is potent in predicting disease progression and patient survival. Thus, the ECM signatures are potential prognostic biomarkers to identify cirrhotic patients at high risk developing advanced stage disease.

Proteome-wide data analysis reveals tissue-specific network associated with SARS-CoV-2 infection.

For patients with COVID-19 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the damages to multiple organs have been clinically observed. Since most of current investigations for virus-host interaction are based on cell level, there is an urgent demand to probe tissue-specific features associated with SARS-CoV-2 infection. Based on collected proteomic datasets from human lung, colon, kidney, liver, and heart, we constructed a virus-receptor network, a virus-interaction network, and a virus-perturbation network. In the tissue-specific networks associated with virus-host crosstalk, both common and different key hubs are revealed in diverse tissues. Ubiquitous hubs in multiple tissues such as BRD4 and RIPK1 would be promising drug targets to rescue multi-organ injury and deal with inflammation. Certain tissue-unique hubs such as REEP5 might mediate specific olfactory dysfunction. The present analysis implies that SARS-CoV-2 could affect multi-targets in diverse host tissues, and the treatment of COVID-19 would be a complex task.

The Learning Curve for Shared Decision-making in Symptomatic Aortic Stenosis.

Importance: Shared decision-making (SDM) is widely advocated for patients with valvular heart disease yet is not integrated into the heart team model for patients with symptomatic aortic stenosis. Decision aids (DAs) have been shown to improve patient-centered outcomes and may facilitate SDM. Objective: To determine whether the repeated use of a DA by heart teams is associated with greater SDM, along with improved patient-centered outcomes and clinician attitudes about DAs. Design, Setting, and Participants: This mixed-methods study included a nonrandomized pre-post intervention and clinician interviews. It was conducted between April 30, 2015, and December 7, 2017, with quantitative analysis performed between January 12, 2017, and May 26, 2017, within 2 academic medical centers in northern New England among 35 patients with symptomatic aortic stenosis who were at high to prohibitive risk for surgery. The qualitative analysis was performed between August 6, 2018, and May 7, 2019. The Severe Aortic Stenosis Decision Aid was delivered by 6 clinicians, with patients choosing between transcatheter aortic valve replacement and medical management. Main Outcomes and Measures: Clinician SDM performance was measured using the Observer OPTION5 scale with dual-independent coding of audiotaped clinic visits. Previsit and postvisit surveys measured the patient's knowledge, satisfaction, and decisional conflict. Audiotaped clinician interviews were coded, and qualitative thematic analysis was performed. Results: Six male clinicians and 35 patients (19 of 34 women [55.9%; 1 survey was missing]; mean [SD] age, 85.8 [7.8] years) participated in the study. Shared decision-making increased stepwise with repeated use of the DA (mean [SD] Observer OPTION5 scores: usual care, 17.9 [7.6]; first use of a DA, 60.5 [30.9]; fifth use of a DA, 79.0 [8.4]; P < .001 for comparison between usual care and fifth use of DA). Multiple uses of the DA were associated with increased patient knowledge (mean difference, 18.0%; 95% CI, 1.2%-34.8%; P = .04) and satisfaction (mean difference, 6.7%; 95% CI, 2.5%-10.8%; P = .01) but not decisional conflict (mean [SD]: usual care, 96.0% [9.4%]; first use of DA, 93.8% [12.5%]; fifth use of DA, 95.0% [11.2%]; P = .60). Qualitative analysis of clinicians' interviews revealed that clinicians perceived that they used an SDM approach without DAs and that the DA was not well understood by elderly patients. There was infrequent values clarification or discussion of stroke risk. Conclusion and Relevance: In a mixed-methods pilot study, use of a DA for severe aortic stenosis by heart team clinicians was associated with improved SDM and patient-centered outcomes. However, in qualitative interviews, heart team clinicians did not perceive a significant benefit of the DA, and therefore sustained implementation is unlikely. This pilot study of SDM clarifies new research directions for heart teams.

Pragmatic Study of Clinician Use of a Personalized Patient Decision Aid Integrated into the Electronic Health Record: An 8-Year Experience.

Background: Patient decision aids (PDAs) facilitate shared decision-making (SDM) and are delivered in a variety of formats, including printed material or instructional videos, and, more recently, web-based tools. Barriers such as time constraints and disruption to clinical workflow are reported to impede usage in routine practice. Introduction: This pragmatic study examines use of PDAs integrated (iPDAs) into the electronic health record (EHR) over an 8-year period. Methods: A suite of iPDAs that personalize decision-making was integrated into an academic health system EHR. Clinician use was tracked using patient and clinician encrypted information, enabling identification of clinician types and unique uses for an 8-year period. Clinician feedback was obtained through survey. Results: Over 8 years, 1,209 identifiable clinicians used the iPDAs at least once ("aware"). Use increased over time, with 2,415 unique uses in 2010, and 23,456 in 2017. Clinicians who used an iPDA with at least 5 patients ("adopters"), increased by 82 clinicians each year (range 56-108); of clinicians who used the tool once, 54.3% became adopters. Of 261 primary care clinicians, 93.5% were aware, 86.2% were adopters, and 80.5% used the tools in the last 90 days. Clinicians perceived the iPDAs to be convenient, efficient, and encouraging of SDM. Discussion: We demonstrate that use of decision aids integrated into the EHR result in repeated use among clinicians over time and have the potential to overcome barriers to implementation. We noted a high degree of clinician satisfaction, without a sense of increase in visit time. Conclusion: Integration of PDAs into the EHR results in sustained use. Further research is needed to assess the impact of iPDAs on decisional quality.