Quality of life drives patients' preferences for secondary findings from genomic sequencing.

There is growing impetus to include measures of personal utility, the nonmedical value of information, in addition to clinical utility in health technology assessment (HTA) of genomic tests such as genomic sequencing (GS). However, personal utility and clinical utility are challenging to define and measure. This study aimed to explore what drives patients' preferences for hypothetically learning medically actionable and non-medically actionable secondary findings (SF), capturing clinical and personal utility; this may inform development of measures to evaluate patient outcomes following return of SF. Semi-structured interviews were conducted with adults with a personal or family cancer history participating in a trial of a decision aid for selection of SF from genomic sequencing (GS) ( www.GenomicsADvISER.com ). Interviews were analyzed thematically using constant comparison. Preserving health-related and non-health-related quality of life was an overarching motivator for both learning and not learning SF. Some participants perceived that learning SF would help them "have a good quality of life" through informing actions to maintain physical health or leading to psychological benefits such as emotional preparation for disease. Other participants preferred not to learn SF because results "could ruin your quality of life," such as by causing negative psychological impacts. Measuring health-related and non-health-related quality of life may capture outcomes related to clinical and personal utility of GS and SF, which have previously been challenging to measure. Without appropriate measures, generating and synthesizing evidence to evaluate genomic technologies such as GS will continue to be a challenge, and will undervalue potential benefits of GS and SF.

Development of patient "profiles" to tailor counseling for incidental genomic sequencing results.

Guidelines recommend that providers engage patients in shared decision-making about receiving incidental results (IR) prior to genomic sequencing (GS), but this can be time-consuming, given the myriad of IR and variation in patients' preferences. We aimed to develop patient profiles to inform pre-test counseling for IR. We conducted semi-structured interviews with participants as a part of a randomized trial of the GenomicsADvISER.com, a decision aid for selecting IR. Interviews explored factors participants considered when deliberating over learning IR. Interviews were analyzed by thematic analysis and constant comparison. Participants were mostly female (28/31) and about half of them were over the age of 50 (16/31). We identified five patient profiles that reflect common contextual factors, attitudes, concerns, and perceived utility of IR. Information Enthusiasts self-identified as "planners" and valued learning most or all IR to enable planning and disease prevention because "knowledge is power". Concerned Individuals defined themselves as "anxious," and were reluctant to learn IR, anticipating negative psychological impacts from IR. Contemplators were discerning about the value and limitations of IR, weighing health benefits with the impacts of not being able to "un-know" information. Individuals of Advanced Life Stage did not consider IR relevant for themselves and primarily considered their implications for family members. Reassurance Seekers were reassured by previous negative genetic test results which shaped their expectations for receiving no IR: "hopefully [GS will] be negative, too. And then I can rest easy". These profiles could inform targeted counseling for IR by providing a framework to address common values, concerns. and misconceptions.

Untargeted plasma and tissue metabolomics in rats with chronic kidney disease given AST-120.

Chronic kidney disease (CKD) results in the accumulation of metabolic waste products that are normally cleared by the kidney, known as uremia. Many of these waste products are from bacteria metabolites in the gut. Accumulation of uremic toxins in plasma and tissue, as well as the gut-plasma-tissue metabolic axis are important for understanding pathophysiological mechanisms of comorbidities in CKD. In this study, an untargeted metabolomics approach was used to determine uremic toxin accumulation in plasma, liver, heart and kidney tissue in rats with adenine-induced CKD. Rats with CKD were also given AST-120, a spherical carbon adsorbent, to assess metabolic changes in plasma and tissues with the removal of gut-derived uremic toxins. AST-120 decreased >55% of metabolites that were increased in plasma, liver and heart tissue of rats with CKD. CKD was primarily defined by 8 gut-derived uremic toxins, which were significantly increased in plasma and all tissues. These metabolites were derived from aromatic amino acids and soy protein including: indoxyl sulfate, p-cresyl sulfate, hippuric acid, phenyl sulfate, pyrocatechol sulfate, 4-ethylphenyl sulfate, p-cresol glucuronide and equol 7-glucuronide. Our results highlight the importance of diet and gut-derived metabolites in the accumulation of uremic toxins and define the gut-plasma-tissue metabolic axis in CKD.