Publications

Under the U.S. Lung Allocation Score (LAS) system, older and sicker patients are prioritized for lung transplantation (LT). The impact of these changes on health-related quality of life (HRQL) after transplant has not been determined. In a single-center prospective cohort study from 2010 to 2016, we assessed HRQL before and repeatedly after LT for up to 3 years using the SF12-Physical and Mental Health, the respiratory-specific Airway Questionnaire 20-Revised, and the Euroqol 5D/Visual Analog Scale utility measures by multivariate linear mixed models jointly modeled with death. We also tested changes in LT-Valued Life Activities disability, BMI, allograft function, and 6-min walk test exercise capacity as predictors of HRQL change. Among 211 initial participants (92% of those eligible), LT improved HRQL by all 5 measures (p < 0.05) and all but SF12-Mental Health improved by threefold or greater than the minimally clinically important difference. Compared to younger participants, those aged ≥65 improved less in SF12-Physical and Mental Health (p < 0.01). Improvements in disability accounted for much of the HRQL improvement. In the LAS era, LT affords meaningful and durable HRQL improvements, mediated by amelioration of disability. Identifying factors limiting HRQL improvement in selected subgroups, especially those aged ≥65, are needed to maximize the net benefits of LT.

BACKGROUND

Genetic data are known to harbor information about human demographics, and genotyping data are commonly used for capturing ancestry information by leveraging genome-wide differences between populations. In contrast, it is not clear to what extent population structure is captured by whole-genome DNA methylation data.

RESULTS

We demonstrate, using three large-cohort 450K methylation array data sets, that ancestry information signal is mirrored in genome-wide DNA methylation data and that it can be further isolated more effectively by leveraging the correlation structure of CpGs with -located SNPs. Based on these insights, we propose a method, EPISTRUCTURE, for the inference of ancestry from methylation data, without the need for genotype data.

CONCLUSIONS

EPISTRUCTURE can be used to infer ancestry information of individuals based on their methylation data in the absence of corresponding genetic data. Although genetic data are often collected in epigenetic studies of large cohorts, these are typically not made publicly available, making the application of EPISTRUCTURE especially useful for anyone working on public data. Implementation of EPISTRUCTURE is available in GLINT, our recently released toolset for DNA methylation analysis at: http://glint-epigenetics.readthedocs.io.

Populations are often divided categorically into distinct racial/ethnic groups based on social rather than biological constructs. Genetic ancestry has been suggested as an alternative to this categorization. Herein, we typed over 450,000 CpG sites in whole blood of 573 individuals of diverse Hispanic origin who also had high-density genotype data. We found that both self-identified ethnicity and genetically determined ancestry were each significantly associated with methylation levels at 916 and 194 CpGs, respectively, and that shared genomic ancestry accounted for a median of 75.7% (IQR 45.8% to 92%) of the variance in methylation associated with ethnicity. There was a significant enrichment (p=4.2×10) of ethnicity-associated sites amongst loci previously associated environmental exposures, particularly maternal smoking during pregnancy. We conclude that differential methylation between ethnic groups is partially explained by the shared genetic ancestry but that environmental factors not captured by ancestry significantly contribute to variation in methylation.

CONTEXT

Despite increasing interest in advance care planning (ACP) and previous ACP descriptions, a consensus definition does not yet exist to guide clinical, research, and policy initiatives.

OBJECTIVE

The aim of this study was to develop a consensus definition of ACP for adults.

METHODS

We convened a Delphi panel of multidisciplinary, international ACP experts consisting of 52 clinicians, researchers, and policy leaders from four countries and a patient/surrogate advisory committee. We conducted 10 rounds using a modified Delphi method and qualitatively analyzed panelists' input. Panelists identified several themes lacking consensus and iteratively discussed and developed a final consensus definition.

RESULTS

Panelists identified several tensions concerning ACP concepts such as whether the definition should focus on conversations vs. written advance directives; patients' values vs. treatment preferences; current shared decision making vs. future medical decisions; and who should be included in the process. The panel achieved a final consensus one-sentence definition and accompanying goals statement: "Advance care planning is a process that supports adults at any age or stage of health in understanding and sharing their personal values, life goals, and preferences regarding future medical care. The goal of advance care planning is to help ensure that people receive medical care that is consistent with their values, goals and preferences during serious and chronic illness." The panel also described strategies to best support adults in ACP.

CONCLUSIONS

A multidisciplinary Delphi panel developed a consensus definition for ACP for adults that can be used to inform implementation and measurement of ACP clinical, research, and policy initiatives.

OBJECTIVE

Liver disease markers have been associated with mortality in HIV-infected individuals in the modern era of effective antiretroviral therapy. Our objective was to determine which markers are most predictive of mortality in HIV-monoinfected and HIV/hepatitis C virus (HCV)-coinfected persons.

RESEARCH DESIGN AND METHODS

We measured serum albumin, total protein, calculated globulin, aspartate transaminase (AST), and alanine transaminase in 193 HIV/HCV-coinfected and 720 HIV-monoinfected persons in the study of Fat Redistribution and Metabolic Change in HIV Infection. We evaluated associations of each marker with 5-year, all-cause mortality, adjusting for cardiovascular, HIV-related factors, inflammation, renal disease, muscle, and adiposity.

RESULTS

After 5 years of follow-up, overall mortality was 21% in HIV/HCV-coinfected and 12% in HIV-monoinfected participants. After multivariable adjustment, lower albumin and higher AST were independently associated with increased mortality. Lower albumin was associated with 49% increased odds of mortality overall [per 0.5 g/dl decrease, 95% confidence interval (CI): 1.2-1.9]; the association was stronger in HIV/HCV-coinfected [odds ratio (OR) = 2.1, 95% CI: 1.4-3.2] vs. HIV-monoinfected (OR = 1.3, 95% CI: 1.0-1.7; HCV-by-albumin interaction: P = 0.038). Higher AST was associated with 41% increased odds of mortality (per AST doubling; 95% CI: 1.1-1.8); associations were much stronger among HIV/HCV-coinfected (OR = 2.5, 95% CI: 1.5-4.1) than HIV-monoinfected (OR = 1.1, 95% CI: 0.8-1.5; HCV-by-AST interaction: P = 0.0042).

CONCLUSION

Lower serum albumin and higher AST appear to be important mortality risk factors in HIV/HCV-coinfection, but much less so in HIV-monoinfected individuals. The association of low albumin with mortality may reflect its role as a negative acute phase response protein. AST levels do not appear to be useful in predicting mortality in HIV-monoinfection and should be considered primarily in the context of HCV-coinfection.

The impact of real-time electronic monitoring on antiretroviral therapy adherence warrants further study. We conducted an analysis of cohort participants that initially involved standard electronic adherence monitoring (EAM), followed by real-time EAM and home visits for sustained at least 48-h adherence interruptions. Immediately after switching between the two types of EAM, mean adherence among 112 participants increased from 84% to 93% and remained elevated for 6 months (P < 0.001). Real-time EAM is a promising approach for improving adherence.