Browsing by Author "Huang, Yong"

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    A distinct symptom pattern emerges for COVID-19 long-haul: a nationwide study
    (Springer Nature, 2022-09-23) Pinto, Melissa D.; Downs, Charles A.; Huang, Yong; El‑Azab, Sarah A.; Ramrakhiani, Nathan S.; Barisano, Anthony; Yu, Lu; Taylor, Kaitlyn; Esperanca, Alvaro; Abrahim, Heather L.; Hughes, Thomas; Giraldo Herrera, Maria; Rahamani, Amir M.; Dutt, Nikil; Chakraborty, Rana; Mendiola, Christian; Lambert, Natalie; Biostatistics, School of Public Health
    Long-haul COVID-19, also called post-acute sequelae of SARS-CoV-2 (PASC), is a new illness caused by SARS-CoV-2 infection and characterized by the persistence of symptoms. The purpose of this cross-sectional study was to identify a distinct and significant temporal pattern of PASC symptoms (symptom type and onset) among a nationwide sample of PASC survivors (n = 5652). The sample was randomly sorted into two independent samples for exploratory (EFA) and confirmatory factor analyses (CFA). Five factors emerged from the EFA: (1) cold and flu-like symptoms, (2) change in smell and/or taste, (3) dyspnea and chest pain, (4) cognitive and visual problems, and (5) cardiac symptoms. The CFA had excellent model fit (x2 = 513.721, df = 207, p < 0.01, TLI = 0.952, CFI = 0.964, RMSEA = 0.024). These findings demonstrate a novel symptom pattern for PASC. These findings can enable nurses in the identification of at-risk patients and facilitate early, systematic symptom management strategies for PASC.
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    A novel conceptual model of trauma-informed care for patients with post-acute sequelae of SARS-CoV-2 illness (PASC)
    (Wiley, 2022) Burton, Candace W.; Downs, Charles A.; Hughes, Thomas; Lambert, Natalie; Abrahim, Heather L.; Giraldo Herrera, Maria; Huang, Yong; Rahmani, Amir; Lee, Jung-Ah; Chakraborty, Rana; Pinto, Melissa D.; Biostatistics, School of Public Health
    Aim: This paper proposes a novel, trauma-informed, conceptual model of care for Post-Acute Sequelae of COVID-19 illness (PASC). Design: This paper describes essential elements, linkages and dimensions of the model that affect PASC patient experiences and the potential impact of trauma-informed care on outcomes. Data sources: PASC is a consequence of the global pandemic, and a new disease of which little is known. Our model was derived from the limited available studies, expert clinical experience specific to PASC survivors and publicly available social media narratives authored by PASC survivors. Implications for nursing: The model provides a critical and novel framework for the understanding and care of persons affected by PASC. This model is aimed at the provision of nursing care, with the intention of reducing the traumatic impacts of the uncertain course of this disease, a lack of defined treatment options and difficulties in seeking care. The use of a trauma-informed care approach to PASC patients can enhance nurses' ability to remediate and ameliorate both the traumatic burden of and the symptoms and experience of the illness. Conclusion: Applying a trauma-informed perspective to care of PASC patients can help to reduce the overall burden of this complex condition. Owing to the fundamentally holistic perspective of the nursing profession, nurses are best positioned to implement care that addresses multiple facets of the PASC experience. Impact: The proposed model specifically addresses the myriad ways in which PASC may affect physical as well as mental and psychosocial dimensions of health. The model particularly seeks to suggest means of supporting patients who have already experienced a life-threatening illness and are now coping with its long-term impact. Since the scope of this impact is not yet defined, trauma-informed care for PASC patients is likely to reduce the overall health and systems burdens of this complex condition.
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    COVID Symptoms, Symptom Clusters, and Predictors for Becoming a Long-Hauler: Looking for Clarity in the Haze of the Pandemic
    (Cold Spring Harbor Laboratory Press, 2021) Huang, Yong; Pinto, Melissa D.; Borelli, Jessica L.; Mehrabadi, Milad Asgari; Abrihim, Heather; Dutt, Nikil; Lambert, Natalie; Nurmi, Erika L.; Chakraborty, Rana; Rahmani, Amir M.; Downs, Charles A.; Biostatistics, School of Public Health
    Emerging data suggest that the effects of infection with SARS-CoV-2 are far reaching extending beyond those with severe acute disease. Specifically, the presence of persistent symptoms after apparent resolution from COVID-19 have frequently been reported throughout the pandemic by individuals labeled as “long-haulers”. The purpose of this study was to assess for symptoms at days 0-10 and 61+ among subjects with PCR-confirmed SARS-CoV-2 infection. The University of California COvid Research Data Set (UC CORDS) was used to identify 1407 records that met inclusion criteria. Symptoms attributable to COVID-19 were extracted from the electronic health record. Symptoms reported over the previous year prior to COVID-19 were excluded, using nonnegative matrix factorization (NMF) followed by graph lasso to assess relationships between symptoms. A model was developed predictive for becoming a long-hauler based on symptoms. 27% reported persistent symptoms after 60 days. Women were more likely to become long-haulers, and all age groups were represented with those aged 50 ± 20 years comprising 72% of cases. Presenting symptoms included palpitations, chronic rhinitis, dysgeusia, chills, insomnia, hyperhidrosis, anxiety, sore throat, and headache among others. We identified 5 symptom clusters at day 61+: chest pain-cough, dyspnea-cough, anxiety-tachycardia, abdominal pain-nausea, and low back pain-joint pain. Long-haulers represent a very significant public health concern, and there are no guidelines to address their diagnosis and management. Additional studies are urgently needed that focus on the physical, mental, and emotional impact of long-term COVID-19 survivors who become long-haulers.
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    Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure
    (Springer Nature, 2019-06-24) Cordero, Pablo; Parikh, Victoria N.; Chin, Elizabeth T.; Erbilgin, Ayca; Gloudemans, Michael J.; Shang, Ching; Huang, Yong; Chang, Alex C.; Smith, Kevin S.; Dewey, Frederick; Zaleta, Kathia; Morley, Michael; Brandimarto, Jeff; Glazer, Nicole; Waggott, Daryl; Pavlovic, Aleksandra; Zhao, Mingming; Moravec, Christine S.; Tang, W. H. Wilson; Skreen, Jamie; Malloy, Christine; Hannenhalli, Sridhar; Li, Hongzhe; Ritter, Scott; Li, Mingyao; Bernstein, Daniel; Connolly, Andrew; Hakonarson, Hakon; Lusis, Aldons J.; Margulies, Kenneth B.; Depaoli-Roach, Anna A.; Montgomery, Stephen B.; Wheeler, Matthew T.; Cappola, Thomas; Ashley, Euan A.; Biochemistry and Molecular Biology, School of Medicine
    Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure.