Publications by authors named "Lusha W Liang"

Aims: Atrial fibrillation (AF) is the most common sustained arrhythmia among patients with hypertrophic cardiomyopathy (HCM), increasing symptom burden and stroke risk. We aimed to construct a plasma proteomics-based model to predict new-onset AF in patients with HCM and determine dysregulated signalling pathways.

Methods And Results: In this prospective, multi-centre cohort study, we conducted plasma proteomics profiling of 4986 proteins at enrolment.

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  • Treatment for hypertrophic cardiomyopathy (HCM) has traditionally relied on general therapies, but new cardiac myosin modulators like mavacamten and aficamten target specific issues by improving heart function.
  • Clinical trials show that mavacamten enhances exercise capacity, alleviates symptoms, and reduces obstruction in patients with obstructive HCM, potentially avoiding more invasive procedures.
  • Due to the complexity of HCM, individual patient responses may vary, emphasizing the importance of careful patient selection and collaborative decision-making in treatment.
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  • Telegenetics expanded access to genetic counseling and testing during the COVID-19 pandemic, allowing non-local patients to receive services outside the prior catchment area.
  • Both local and non-local patients reported similar experiences regarding the convenience and challenges of telegenetics, though both groups faced changes in daily life due to positive genetic test results.
  • Follow-up care varied significantly, with local patients having better access to appointments, highlighting the need for improved support for non-local patients to ensure continuity of care.
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Despite advances in our understanding of myocardial recovery among left ventricular assist device (LVAD) patients, with 10-30% of patients achieving substantial myocardial improvement, the rates of LVAD support cessation remain extremely low (1-2%). These numbers are in stark contrast to clinical trial data where successful LVAD cessation is reported in up to 47% of patients. The majority of LVAD programs lack structured recovery programs and targeted protocols, likely underscoring the heterogeneity that exists among LVAD patients with myocardial recovery.

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  • Hypertrophic cardiomyopathy (HCM) can lead to severe nonobstructive heart failure in about 5% to 7% of patients, despite being more commonly linked to obstructive symptoms and sudden cardiac death.
  • Diagnosing advanced heart failure in HCM involves imaging, hemodynamic assessments, and exercise testing to determine which patients might benefit from advanced treatments.
  • While some therapies focus on systolic dysfunction, heart transplantation is usually the preferred option for those with advanced heart failure in HCM, leading to high survival rates after the procedure.
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  • Hypertrophic cardiomyopathy (HCM) is the most common genetic heart condition, but the reasons behind major adverse cardiovascular events (MACEs) in these patients are still unclear.
  • A study involving 402 patients used plasma proteomics to identify proteins and signaling pathways associated with MACEs, comparing those with and without previous events.
  • The findings revealed dysregulation in both known pathways, like TGF-β, and new ones, like Ras-MAPK, providing insights into the molecular mechanisms involved in HCM progression.
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  • Heart failure (HF) is a major complication in hypertrophic cardiomyopathy (HCM), and existing clinical methods to predict its worsening are limited; this study aimed to create a plasma proteomics model for better prediction.
  • The researchers conducted a study with 389 HCM patients, using proteomics to analyze 4986 proteins and developed a predictive model which was validated across different patient groups.
  • The 11-protein model showed high accuracy (0.87) for predicting worsening HF, highlighting the dysregulation of the Ras-MAPK signaling pathway as a critical factor in this condition.
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  • Hypertrophic cardiomyopathy (HCM) is linked to gene mutations affecting heart muscle contractions, and this study aimed to identify specific miRNAs as potential biomarkers for HCM.
  • Researchers conducted a multicenter study with 555 participants, analyzing plasma miRNAs and developing a model to distinguish between HCM and hypertensive left ventricular hypertrophy.
  • Results showed strong predictive ability for the model with high accuracy, and identified dysregulation in the Ras-MAPK signaling pathway and inflammation-related pathways as significant in HCM's development.
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  • Hypertrophic cardiomyopathy can lead to severe cardiovascular issues, and the study aims to identify protein biomarkers that can predict major adverse cardiovascular events (MACE) in affected patients.
  • Researchers conducted a study involving plasma proteomics profiling on nearly 250 patients, developing a predictive model using data from one group and validating it with another.
  • Results showed the predictive model had a high accuracy rate (0.81) and identified significant pathways, including the MAPK and TGF-β pathways, which were linked to the development of MACE.
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  • The COVID-19 pandemic led to a significant increase in the use of telemedicine for cardiogenetics services, with remote visits rising from 6% in 2019 to 80% in 2020.
  • The proportion of family members attending genetic counseling appointments also increased from 18% to 34% during this period, indicating greater involvement and outreach.
  • Overall, telemedicine not only maintained the quality of genetic testing results but also expanded access to services beyond New York, reaching patients in multiple states and even Puerto Rico.
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  • Hypertrophic cardiomyopathy (HCM) is a complex heart disease with various subtypes that may have different biological features, and existing clinical models struggle to accurately predict serious cardiovascular issues.
  • In this study, researchers analyzed plasma protein data from 258 HCM patients over nearly 3 years using machine learning, leading to the identification of four distinct molecular subtypes of the disease.
  • The study found that patients classified as subtype D had a significantly higher risk of major adverse cardiovascular events compared to subtype A, and this subtype was linked to specific inflammatory and fibrosis-related pathways.
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Early right heart failure (RHF) occurs in up to 40% of patients following left ventricular assist device (LVAD) implantation and is associated with increased morbidity and mortality. The most recent report from the Mechanical Circulatory Support-Academic Research Consortium (MCS-ARC) working group subdivides early RHF into early acute RHF and early postimplant RHF. We sought to determine the effectiveness of right ventricular (RV) longitudinal strain (LS) in predicting RHF according to the new MCS-ARC definition.

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Background: Hypertrophic cardiomyopathy (HCM) is caused by mutations in the genes coding for proteins essential in normal myocardial contraction. However, it remains unclear through which molecular pathways gene mutations mediate the development of HCM. The objectives were to determine plasma protein biomarkers of HCM and to reveal molecular pathways differentially regulated in HCM.

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Endotyping is an emerging concept in which diseases are classified into distinct subtypes based on underlying molecular mechanisms. Heart failure (HF) is a complex clinical syndrome that encompasses multiple endotypes with differential risks of adverse events, and varying responses to treatment. Identifying these distinct endotypes requires molecular-level investigation involving multi-"omics" approaches, including genomics, transcriptomics, proteomics, and metabolomics.

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Background: Genetic testing can determine family screening strategies and has prognostic and diagnostic value in hypertrophic cardiomyopathy (HCM). However, it can also pose a significant psychosocial burden. Conventional scoring systems offer modest ability to predict genotype positivity.

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  • Hereditary transthyretin amyloid cardiomyopathy (hATTR-CM) due to the TTR V122I variant causes heart failure, particularly in older individuals of African ancestry, but its clinical impacts in other populations remain unclear.
  • The objective of the study was to explore the link between the TTR V122I variant and heart failure, while also examining how often carriers of the variant are diagnosed with hATTR-CM.
  • The study involved a large analysis of individuals enrolled in biobanks, revealing that 3.1% of those studied were TTR V122I carriers and that 30% had heart failure, highlighting a significant issue regarding diagnosis rates among these carriers.
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•Nonbacterial thrombotic endocarditis can occur in ovarian clear cell carcinoma.•We report on NBTE-associated embolic cerebrovascular infarcts in advanced OCCC.•Further NBTE-associated embolic events can be prevented with anticoagulant therapy.

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Objective: To determine clinical outcomes in patients with stage IA polyp-limited versus endometrium-limited high-grade (type II) endometrial carcinoma (EC).

Methods: We identified all cases of stage IA polyp-limited or endometrium-limited high-grade EC (FIGO grade 3 endometrioid, serous, clear cell, or mixed) who underwent simple hysterectomy, bilateral salpingo-oophorectomy, peritoneal washings, omental biopsy, and pelvic and para-aortic lymph node dissection and received adjuvant treatment at our institution from October 1995 to November 2012. Progression-free survival (PFS) and overall survival (OS) by histology, adjuvant therapy, and polyp-limited versus endometrium-limited disease status were determined using log-rank test.

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Genes that interact or function together are often clustered in bacterial genomes, and it has been proposed that this clustering may affect gene expression. In this study, we directly compared gene expression in nonclustered arrangements and in three common clustered arrangements (codirectional, divergent, and operon) using synthetic circuits in Escherichia coli. We found that gene clustering had minimal effects on gene expression.

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Gene translocations play an important role in the plasticity and evolution of bacterial genomes. In this study, we investigated the impact on gene regulation of three genome organizational features that can be altered by translocations: (i) chromosome position; (ii) gene orientation; and (iii) the distance between a target gene and its transcription factor gene ('target-TF distance'). Specifically, we quantified the effect of these features on constitutive expression, transcription factor binding and/or gene expression noise using a synthetic network in Escherichia coli composed of a transcription factor (LacI repressor) and its target gene (yfp).

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