Coronavirus disease 2019 (COVID-19) is characterized by heterogeneity in susceptibility to the disease and severity of illness. Understanding inter-individual variation has important implications for not only allocation of resources but also targeting patients for escalation of care, inclusion in clinical trials, and individualized medical therapy including vaccination. In addition to geographic location and social vulnerability, there are clear biological differences such as age, sex, race, presence of comorbidities, underlying genetic variation, and differential immune response that contribute to variability in disease manifestation. These differences may have implications for precision medicine. Specific examples include the observation that androgens regulate the expression of the enzyme transmembrane protease, serine 2 which facilitates severe acute respiratory syndrome coronavirus 2 viral entry into the cell; therefore, androgen deprivation therapy is being explored as a treatment option in males infected with COVID-19. An immunophenotyping study of COVID-19 patients has shown that a subset develop T cytopenia which has prompted a clinical trial that is testing the efficacy of interleukin-7 in these patients. Predicting which COVID-19 patients will develop progressive disease that will require hospitalization has important implications for clinical trials that target outpatients. Enrollment of patients at low risk for progression of disease and hospitalization would likely not result in such therapy demonstrating efficacy. There are efforts to use artificial intelligence to integrate digital data from smartwatch applications or digital monitoring systems and biological data to enable identification of the high risk COVID-19 patient. The ultimate goal of precision medicine using such modern technology is to recognize individual differences to improve health for all.

In patients with univentricular hearts and Fontan palliation, obesity is associated with symptomatic heart failure and mortality.

One of 5 people will develop heart failure over his or her lifetime. Early diagnosis and better understanding of the pathophysiology of this disease are critical to optimal treatment. The “omics”—genomics, pharmacogenomics, epigenomics, proteomics, metabolomics, and microbiomics— of heart failure represent rapidly expanding fields of science that have, to date, not been integrated into a single body of work. The goals of this statement are to provide a comprehensive overview of the current state of these omics as they relate to the development and progression of heart failure and to consider the current and potential future applications of these data for precision medicine with respect to prevention, diagnosis, and therapy.

SUMMARY Sympathovagal imbalance contributes to progressive worsening of HF (HF) and is associated with untoward clinical outcomes. Based on compelling pre-clinical studies which supported the role of autonomic modulation in HF models, a series of clinical studies were initiated using spinal cord stimulation (SCS), vagus nerve stimulation (VNS) and baroreceptor activation therapy (BAT) in patients with HF with a reduced ejection fraction (HFrEF). While the phase II studies with BAT remain encouraging, the larger clinical studies with SCS and VNS have yielded disappointing results. Here we will focus on the pre-clinical studies that supported the role of neuromodulation in the failing heart, as well provide a critical review of the recent clinical trials that have sought to modulate autonomic tone in HF patients. This review will conclude with an analysis of some of the difficulties in translating device-based modulation of the autonomic nervous from pre-clinical models into successful clinical trials, as well as provide suggestions for how to move the field of neuromodulation forward

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