Striosomes Mediate Value-Based Learning Vulnerable in Age and a Huntington's Disease Model.

Learning valence-based responses to favorable and unfavorable options requires judgments of the relative value of the options, a process necessary for species survival. We found, using engineered mice, that circuit connectivity and function of the striosome compartment of the striatum are critical for this type of learning. Calcium imaging during valence-based learning exhibited a selective correlation between learning and striosomal but not matrix signals. This striosomal activity encoded discrimination learning and was correlated with task engagement, which, in turn, could be regulated by chemogenetic excitation and inhibition. Striosomal function during discrimination learning was disturbed with aging and severely so in a mouse model of Huntington's disease. Anatomical and functional connectivity of parvalbumin-positive, putative fast-spiking interneurons (FSIs) to striatal projection neurons was enhanced in striosomes compared with matrix in mice that learned. Computational modeling of these findings suggests that FSIs can modulate the striosomal signal-to-noise ratio, crucial for discrimination and learning.

The impact of clinical genome sequencing in a global population with suspected rare genetic disease.

There is mounting evidence of the value of clinical genome sequencing (cGS) in individuals with suspected rare genetic disease (RGD), but cGS performance and impact on clinical care in a diverse population drawn from both high-income countries (HICs) and low- and middle-income countries (LMICs) has not been investigated. The iHope program, a philanthropic cGS initiative, established a network of 24 clinical sites in eight countries through which it provided cGS to individuals with signs or symptoms of an RGD and constrained access to molecular testing. A total of 1,004 individuals (median age, 6.5 years; 53.5% male) with diverse ancestral backgrounds (51.8% non-majority European) were assessed from June 2016 to September 2021. The diagnostic yield of cGS was 41.4% (416/1,004), with individuals from LMIC sites 1.7 times more likely to receive a positive test result compared to HIC sites (LMIC 56.5% [195/345] vs. HIC 33.5% [221/659], OR 2.6, 95% CI 1.9-3.4, p < 0.0001). A change in diagnostic evaluation occurred in 76.9% (514/668) of individuals. Change of management, inclusive of specialty referrals, imaging and testing, therapeutic interventions, and palliative care, was reported in 41.4% (285/694) of individuals, which increased to 69.2% (480/694) when genetic counseling and avoidance of additional testing were also included. Individuals from LMIC sites were as likely as their HIC counterparts to experience a change in diagnostic evaluation (OR 6.1, 95% CI 1.1-∞, p = 0.05) and change of management (OR 0.9, 95% CI 0.5-1.3, p = 0.49). Increased access to genomic testing may support diagnostic equity and the reduction of global health care disparities.

Quantum network utility: A framework for benchmarking quantum networks.

The central aim of quantum networks is to facilitate user connectivity via quantum channels, but there is an open need for benchmarking metrics to compare diverse quantum networks. Here, we propose a general framework for quantifying the performance of a quantum network by estimating the value created by connecting users through quantum channels. In this framework, we define the quantum network utility metric [Formula: see text] to capture the social and economic value of quantum networks. The proposed framework accommodates a variety of applications from secure communications to distributed sensing. As a case study, we investigate the example of distributed quantum computing in detail. We determine the scaling laws of quantum network utility, which suggest that distributed edge quantum computing has more potential for success than its classical equivalent. We believe the proposed utility-based framework will serve as a foundation for guiding and assessing the development of quantum network technologies and designs.

A unified theoretical framework underlying the regulation of motivated behavior.

To orchestrate behaviors for survival, multiple psychological components have evolved. The current theories do not clearly distinguish the distinct components. In this article, we provide a unified theoretical framework. To optimize survival, there should be four components; (1) "need", an alarm based on a predicted deficiency. (2) "motivation", a direct behavior driver. (3) "pleasure", a teacher based on immediate outcomes. (4) "utility", a teacher based on final delayed outcomes. For behavior stability, need should be accumulated into motivation to drive behavior. Based on the immediate outcome of the behavior, the pleasure should teach whether to continue the current behavior. Based on the final delay outcome, the utility should teach whether to increase future behavior by reshaping the other three components. We provide several neural substrate candidates in the food context. The proposed theoretical framework, in combination with appropriate experiments, will unravel the neural components responsible for each theoretical component.

Slowing of Movements in Healthy Aging as a Rational Economic Response to an Elevated Effort Landscape.

Why do we move slower as we grow older? The reward circuits of the brain, which tend to invigorate movements, decline with aging, raising the possibility that reduced vigor is due to the diminishing value that our brain assigns to movements. However, as we grow older, it also becomes more effortful to make movements. Is age-related slowing principally a consequence of increased effort costs from the muscles, or reduced valuation of reward by the brain? Here, we first quantified the cost of reaching via metabolic energy expenditure in human participants (male and female), and found that older adults consumed more energy than the young at a given speed. Thus, movements are objectively more costly for older adults. Next, we observed that when reward increased, older adults, like the young, responded by initiating their movements earlier. Yet, unlike the young, they were unwilling to increase their movement speed. Was their reluctance to reach quicker for rewards due to the increased effort costs, or because they ascribed less value to the movement? Motivated by a mathematical model, we next made the young experience a component of aging by making their movements more effortful. Now the young responded to reward by reacting faster but chose not to increase their movement speed. This suggests that slower movements in older adults are partly driven by an adaptive response to an elevated effort landscape. Moving slower may be a rational economic response the brain is making to mitigate the elevated effort costs that accompany aging.

Risk-Taking Is Associated with Decreased Subjective Value Signals and Increased Prediction Error Signals in the Hot Columbia Card Task.

It remains a pressing concern to understand how neural computations relate to risky decisions. However, most observations of brain-behavior relationships in the risk-taking domain lack a rigorous computational basis or fail to emulate of the dynamic, sequential nature of real-life risky decision-making. Recent advances emphasize the role of neural prediction error (PE) signals. We modeled, according to prospect theory, the choices of n = 43 human participants (33 females, 10 males) performing an EEG version of the hot Columbia Card Task, featuring rounds of sequential decisions between stopping (safe option) and continuing with increasing odds of a high loss (risky option). Single-trial regression EEG analyses yielded a subjective value signal at centroparietal (300-700 ms) and frontocentral (>800 ms) electrodes and in the delta band, as well as PE signals tied to the feedback-related negativity, P3a, and P3b, and in the theta band. Higher risk preference (total number of risky choices) was linked to attenuated subjective value signals but increased PE signals. Higher P3-like activity associated with the most positive PE in each round predicted stopping in the present round but not risk-taking in the subsequent round. Our findings indicate that decreased representation of decision values and increased sensitivity to winning despite low odds (positive PE) facilitate risky choices at the subject level. Strong neural responses when gains are least expected (the most positive PE on each round) adaptively contribute to safer choices at the trial-by-trial level but do not affect risky choice at the round-by-round level.

Establishing the Medical Actionability of Genomic Variants.

Actionability is an important concept in medicine that does not have a well-accepted standard definition, nor is there a general consensus on how to establish it. Medical actionability is often conflated with clinical utility, a related but distinct concept. This lack of clarity contributes to practice variation and inconsistent coverage decisions in genomic medicine, leading to the potential for systematic bias in the use of evidence-based interventions. We clarify how medical actionability and clinical utility are distinct and then discuss the spectrum of actionability, including benefits for the person, the family, and society. We also describe applications across the life course, including prediction, diagnosis, and treatment. Current challenges in assessing the medical actionability of identified genomic variants include gaps in the evidence, limited contexts with practice guidelines, and subjective aspects of medical actionability. A standardized and authoritative assessment of medical actionability is critical to implementing genomic medicine in a fashion that improves population health outcomes and reduces health disparities.

A genome sequencing system for universal newborn screening, diagnosis, and precision medicine for severe genetic diseases.

Newborn screening (NBS) dramatically improves outcomes in severe childhood disorders by treatment before symptom onset. In many genetic diseases, however, outcomes remain poor because NBS has lagged behind drug development. Rapid whole-genome sequencing (rWGS) is attractive for comprehensive NBS because it concomitantly examines almost all genetic diseases and is gaining acceptance for genetic disease diagnosis in ill newborns. We describe prototypic methods for scalable, parentally consented, feedback-informed NBS and diagnosis of genetic diseases by rWGS and virtual, acute management guidance (NBS-rWGS). Using established criteria and the Delphi method, we reviewed 457 genetic diseases for NBS-rWGS, retaining 388 (85%) with effective treatments. Simulated NBS-rWGS in 454,707 UK Biobank subjects with 29,865 pathogenic or likely pathogenic variants associated with 388 disorders had a true negative rate (specificity) of 99.7% following root cause analysis. In 2,208 critically ill children with suspected genetic disorders and 2,168 of their parents, simulated NBS-rWGS for 388 disorders identified 104 (87%) of 119 diagnoses previously made by rWGS and 15 findings not previously reported (NBS-rWGS negative predictive value 99.6%, true positive rate [sensitivity] 88.8%). Retrospective NBS-rWGS diagnosed 15 children with disorders that had been undetected by conventional NBS. In 43 of the 104 children, had NBS-rWGS-based interventions been started on day of life 5, the Delphi consensus was that symptoms could have been avoided completely in seven critically ill children, mostly in 21, and partially in 13. We invite groups worldwide to refine these NBS-rWGS conditions and join us to prospectively examine clinical utility and cost effectiveness.

Worth the Work? Monkeys Discount Rewards by a Subjective Adapting Effort Cost.

All life must solve how to allocate limited energy resources to maximize benefits from scarce opportunities. Economic theory posits decision makers optimize choice by maximizing the subjective benefit (utility) of reward minus the subjective cost (disutility) of the required effort. While successful in many settings, this model does not fully account for how experience can alter reward-effort trade-offs. Here, we test how well the subtractive model of effort disutility explains the behavior of two male nonhuman primates (Macaca mulatta) in a binary choice task in which reward quantity and physical effort to obtain were varied. Applying random utility modeling to independently estimate reward utility and effort disutility, we show the subtractive effort model better explains out-of-sample choice behavior when compared with parabolic and exponential effort discounting. Furthermore, we demonstrate that effort disutility depends on previous experience of effort: in analogy to work from behavioral labor economics, we develop a model of reference-dependent effort disutility to explain the increased willingness to expend effort following previous experience of effortful options in a session. The result of this analysis suggests that monkeys discount reward by an effort cost that is measured relative to an expected effort learned from previous trials. When this subjective cost of effort, a function of context and experience, is accounted for, trial-by-trial choices can be explained by the subtractive cost model of effort. Therefore, in searching for net utility signals that may underpin effort-based decision-making in the brain, careful measurement of subjective effort costs is an essential first step.SIGNIFICANCE STATEMENT All decision-makers need to consider how much effort they need to expend when evaluating potential options. Economic theories suggest that the optimal way to choose is by cost-benefit analysis of reward against effort. To be able to do this efficiently over many decision contexts, this needs to be done flexibly, with appropriate adaptation to context and experience. Therefore, in aiming to understand how this might be achieved in the brain, it is important to first carefully measure the subjective cost of effort. Here, we show monkeys make reward-effort cost-benefit decisions, subtracting the subjective cost of effort from the subjective value of rewards. Moreover, the subjective cost of effort is dependent on the monkeys' experience of effort in previous trials.

Cost-utility analysis of Dexcom G6 real-time continuous glucose monitoring versus FreeStyle Libre 1 intermittently scanned continuous glucose monitoring in adults with type 1 diabetes in Belgium.

AIMS/HYPOTHESIS: The aim of this study was to assess the long-term cost-effectiveness of Dexcom G6 real-time continuous glucose monitoring (rtCGM) with alert functionality compared with FreeStyle Libre 1 intermittently scanned continuous glucose monitoring (isCGM) without alerts in adults with type 1 diabetes in Belgium. METHODS: The IQVIA CORE Diabetes Model was used to estimate cost-effectiveness. Input data for the simulated baseline cohort were sourced from the randomised ALERTT1 trial (ClinicalTrials.gov. REGISTRATION NO: NCT03772600). The age of the participants was 42.9 ± 14.1 years (mean ± SD), and the baseline HbA1c was 57.8 ± 9.5 mmol/mol (7.4 ± 0.9%). Participants using rtCGM showed a reduction in HbA1c of 3.6 mmol/mol (0.36 percentage points) based on the 6-month mean between-group difference. In the base case, both rtCGM and isCGM were priced at €3.92/day (excluding value-added tax [VAT]) according to the Belgian reimbursement system. The analysis was performed from a Belgian healthcare payer perspective over a lifetime time horizon. Health outcomes were expressed as quality-adjusted life years. Probabilistic and one-way sensitivity analyses were used to account for parameter uncertainty. RESULTS: In the base case, rtCGM dominated isCGM, resulting in lower diabetes-related complication costs and better health outcomes. The associated main drivers favouring rtCGM were lower HbA1c, fewer severe hypoglycaemic events and reduced fear of hypoglycaemia. The results were robust under a wide range of one-way sensitivity analyses. In models where the price of rtCGM is €5.11/day (a price increase of 30.4%) or €12.34/day (a price increase of 214.8%), rtCGM was cost-neutral or reached an incremental cost-effectiveness ratio of €40,000 per quality-adjusted life year, respectively. CONCLUSIONS/INTERPRETATION: When priced similarly, Dexcom G6 rtCGM with alert functionality has both economic and clinical benefits compared with FreeStyle Libre 1 isCGM without alerts in adults with type 1 diabetes in Belgium, and appears to be a cost-effective glucose monitoring modality. Trial registration ClinicalTrials.gov NCT03772600.

Fit-for-Purpose Ki-67 Immunohistochemistry Assays for Breast Cancer.

New therapies are being developed for breast cancer, and in this process, some "old" biomarkers are reutilized and given a new purpose. It is not always recognized that by changing a biomarker's intended use, a new biomarker assay is created. The Ki-67 biomarker is typically assessed by immunohistochemistry (IHC) to provide a proliferative index in breast cancer. Canadian laboratories assessed the analytical performance and diagnostic accuracy of their Ki-67 IHC laboratory-developed tests (LDTs) of relevance for the LDTs' clinical utility. Canadian clinical IHC laboratories enrolled in the Canadian Biomarker Quality Assurance Pilot Run for Ki-67 in breast cancer by invitation. The Dako Ki-67 IHC pharmDx assay was employed as a study reference assay. The Dako central laboratory was the reference laboratory. Participants received unstained slides of breast cancer tissue microarrays with 32 cases and performed their in-house Ki-67 assays. The results were assessed using QuPath, an open-source software application for bioimage analysis. Positive percent agreement (PPA, sensitivity) and negative percent agreement (NPA, specificity) were calculated against the Dako Ki-67 IHC pharmDx assay for 5%, 10%, 20%, and 30% cutoffs. Overall, PPA and NPA varied depending on the selected cutoff; participants were more successful with 5% and 10%, than with 20% and 30% cutoffs. Only 4 of 16 laboratories had robust IHC protocols with acceptable PPA for all cutoffs. The lowest PPA for the 5% cutoff was 85%, for 10% was 63%, for 20% was 14%, and for 30% was 13%. The lowest NPA for the 5% cutoff was 50%, for 10% was 33%, for 20% was 50%, and for 30% was 57%. Despite many years of international efforts to standardize IHC testing for Ki-67 in breast cancer, our results indicate that Canadian clinical LDTs have a wide analytical sensitivity range and poor agreement for 20% and 30% cutoffs. The poor agreement was not due to the readout but rather due to IHC protocol conditions. International Ki-67 in Breast Cancer Working Group (IKWG) recommendations related to Ki-67 IHC standardization cannot take full effect without reliable fit-for-purpose reference materials that are required for the initial assay calibration, assay performance monitoring, and proficiency testing.

Health utility values of breast cancer treatments and the impact of varying quality of life assumptions on cost-effectiveness.

In breast cancer research, utility assumptions are outdated and inconsistent which may affect the results of quality adjusted life year (QALY) calculations and thereby cost-effectiveness analyses (CEAs). Four hundred sixty four female patients with breast cancer treated at Erasmus MC, the Netherlands, completed EQ-5D-5L questionnaires from diagnosis throughout their treatment. Average utilities were calculated stratified by age and treatment. These utilities were applied in CEAs analysing 920 breast cancer screening policies differing in eligible ages and screening interval simulated by the MISCAN-Breast microsimulation model, using a willingness-to-pay threshold of €20,000. The CEAs included varying sets on normative, breast cancer treatment and screening and follow-up utilities. Efficiency frontiers were compared to assess the impact of the utility sets. The calculated average patient utilities were reduced at breast cancer diagnosis and 6 months after surgery and increased toward normative utilities 12 months after surgery. When using normative utility values of 1 in CEAs, QALYs were overestimated compared to using average gender and age-specific values. Only small differences in QALYs gained were seen when varying treatment utilities in CEAs. The CEAs varying screening and follow-up utilities showed only small changes in QALYs gained and the efficiency frontier. Throughout all variations in utility sets, the optimal strategy remained robust; biennial for ages 40-76 years and occasionally biennial 40-74 years. In sum, we recommend to use gender and age stratified normative utilities in CEAs, and patient-based breast cancer utilities stratified by age and treatment or disease stage. Furthermore, despite varying utilities, the optimal screening scenario seems very robust.

Utility and Diversity: Challenges for Genomic Medicine.

Genomic information is poised to play an increasing role in clinical care, extending beyond highly penetrant genetic conditions to less penetrant genotypes and common disorders. But with this shift, the question of clinical utility becomes a major challenge. A collaborative effort is necessary to determine the information needed to evaluate different uses of genomic information and then acquire that information. Another challenge must also be addressed if that process is to provide equitable benefits: the lack of diversity of genomic data. Current genomic knowledge comes primarily from populations of European descent, which poses the risk that most of the human population will be shortchanged when health benefits of genomics emerge. These two challenges have defined my career as a geneticist and have taught me that solutions must start with dialogue across disciplinary and social divides.

Developing and validating clinical prediction models in hepatology - An overview for clinicians.

Prediction models are everywhere in clinical medicine. We use them to assign a diagnosis or a prognosis, and there have been continuous efforts to develop better prediction models. It is important to understand the fundamentals of prediction modelling, thus, we herein describe nine steps to develop and validate a clinical prediction model with the intention of implementing it in clinical practice: Determine if there is a need for a new prediction model; define the purpose and intended use of the model; assess the quality and quantity of the data you wish to develop the model on; develop the model using sound statistical methods; generate risk predictions on the probability scale (0-100%); evaluate the performance of the model in terms of discrimination, calibration, and clinical utility; validate the model using bootstrapping to correct for the apparent optimism in performance; validate the model on external datasets to assess the generalisability and transportability of the model; and finally publish the model so that it can be implemented or validated by others.

Environmental effects and their impact on yield in adjacent experimental plots of high-stem and short-stem wheat varieties.

BACKGROUND: In regional wheat trials, when short-stem wheat varieties and high-stem wheat varieties are planted adjacent to each other in small plots, changes in their marginal plot environment can lead to bias in yield evaluation. Currently, there is no relevant research revealing the degree of their mutual influence. RESULTS: In a regional wheat experiment, when high-stem wheat varieties and short-stem wheat varieties were planted adjacent to one another, there was no significant change in soil temperature or humidity in the high-stem wheat variety experimental plot from November to May compared to the control plot, while the soil humidity in the short-stem wheat variety experimental plot was greater than that in the control plot. In May, the soil temperature of the short-stem wheat varieties in the experimental plot was lower than that in the control plot. Illumination of the wheat canopy in the high-stem wheat variety experimental plot had a significant positive effect in April and May, while illumination of the wheat canopy in the short-stem wheat variety experimental plot had a negative effect. The chlorophyll fluorescence parameters of flag leaves in the high-stem wheat variety experimental plots showed an overall increasing trend, while the chlorophyll fluorescence parameters of flag leaves in the experimental plots of short-stem wheat varieties showed a decreasing trend. The analysis of the economic yield, biological yield, and yield factors in each experimental plot revealed that the marginal effects of the economic yield and 1000-grain weight were particularly significant and manifested as positive effects in the high-stem wheat variety experimental plot and as negative effects in the short-stem wheat variety experimental plot. The economic yield of the high-stem wheat variety experimental plot was significantly greater than that of the control plot, the economic yield of the short-stem wheat variety experimental plot was significantly lower than that of the control plot, and the economic yield of the high-stem experimental plot was significantly greater than that of the short-stem experimental plot. When the yield of the control plot of the high-stem wheat varieties was compared to that of the control plot of the short-stem wheat varieties, the yield of the control plot of the short-stem wheat varieties was significantly greater than that of the control plot of the high-stem wheat varieties. CONCLUSIONS: Based on these findings, it is concluded that plots with high-stem and short-stem wheat varieties are adjacent in regional wheat trials, the plots of high-stem wheat varieties are subject to marginal positive effects, resulting in a significant increase in economic yield; the plots of short-stem wheat varieties are subject to marginal negative effects, resulting in a decrease in economic yield. This study reveals the mutual influence mechanism of environment and yield with adjacent planting of high-stem and short-stem wheat varieties in regional wheat trials, providing a useful reference and guidance for optimizing the layout of regional wheat trials.

An original study assessing biomarker success rate in breast cancer recurrence biomarker research.

BACKGROUND: Breast cancer is the second most common cause of cancer mortality worldwide. Biomarker discovery has led to advances in understanding molecular phenotyping and thus has a great potential for precision management of this diverse disease. Despite increased interest in the biomarker field, only a small number of breast cancer biomarkers are known to be clinically useful. Therefore, it is very important to characterise the success rate of biomarkers in this field and study potential reasons for the deficit. We therefore aim to achieve quantitative characterisation of the biomarker translation gap by tracking the progress of prognostic biomarkers associated with breast cancer recurrence. METHODS: An electronic systematic search was conducted in Medline and Embase databases using keywords and mesh headings associated with breast cancer recurrence biomarkers (1940-2023). Abstracts were screened, and primary clinical studies involving breast cancer recurrence biomarkers were selected. Upon identification of relevant literature, we extracted the biomarker name, date of publication and journal name. All analyses were performed using IBM SPSS Statistics and GraphPad prism (La Jolla, California, USA). RESULTS: A total of 19,195 articles were identified, from which 4597 articles reported breast cancer biomarkers associated with recurrence. Upon data extraction, 2437 individual biomarkers were identified. Out of these, 23 are currently recommended for clinical use, which corresponds to only 0.94% of all discovered biomarkers. CONCLUSIONS: This study characterised for the first time the translational gap in the field of recurrence-related breast cancer biomarkers, indicating that only 0.94% of identified biomarkers were recommended for clinical use. This denotes an evident barrier in the biomarker research field and emphasises the need for a clearer route from biomarker discovery through to implementation.

Measuring perceived utility of genomic sequencing: Development and validation of the GENEtic Utility (GENE-U) scale for adult screening.

PURPOSE: As population-based screening programs to identify genetic conditions in adults using genomic sequencing (GS) are increasingly available, validated patient-centered outcome measures are needed to understand participants' experience. We aimed to develop and validate an instrument to assess the perceived utility of GS in the context of adult screening. METHODS: Informed by a 5-domain conceptual model, we used a 5-step approach to instrument development and validation: (1) item writing, (2) cognitive testing, (3) pilot testing and item reduction, (4) psychometric testing, and (5) evaluation of construct validity. Adults undergoing risk-based or population-based GS who had received GS results as part of ongoing research studies participated in structured cognitive interviews and 2 rounds of surveys. After item pool refinement, we conducted an exploratory factor analysis and calculated Pearson correlations with related instruments. RESULTS: We derived the 18-item Adult Screening version of the GENEtic Utility scale (total sum score α = .87). Mirroring the Pediatric Diagnostic version, the instrument has a 2-factor structure, including an Informational Utility subscale (14 items, α = .89) and an Emotional Utility subscale (4 items, α = .75). The Informational Utility subscale was strongly associated with empowerment and personal utility of GS. Correlations of the Emotional Utility subscale with psychosocial impact and anxiety and depression were weak to moderate. CONCLUSION: Initial psychometric testing of the Adult Screening GENEtic Utility scale demonstrates its promise, and additional validation in translational genomics research is warranted.

Assessment of Mendelian and risk-factor genes in Alzheimer disease: A prospective nationwide clinical utility study and recommendations for genetic screening.

PURPOSE: To assess the likely pathogenic/pathogenic (LP/P) variants rates in Mendelian dementia genes and the moderate-to-strong risk factors rates in patients with Alzheimer disease (AD). METHODS: We included 700 patients in a prospective study and performed exome sequencing. A panel of 28 Mendelian and 6 risk-factor genes was interpreted and returned to patients. We built a framework for risk variant interpretation and risk gradation and assessed the detection rates among early-onset AD (EOAD, age of onset (AOO) ≤65 years, n = 608) depending on AOO and pedigree structure and late-onset AD (66 < AOO < 75, n = 92). RESULTS: Twenty-one patients carried a LP/P variant in a Mendelian gene (all with EOAD, 3.4%), 20 of 21 affected APP, PSEN1, or PSEN2. LP/P variant detection rates in EOAD ranged from 1.7% to 11.6% based on AOO and pedigree structure. Risk factors were found in 69.5% of the remaining 679 patients, including 83 (12.2%) being heterozygotes for rare risk variants, in decreasing order of frequency, in TREM2, ABCA7, ATP8B4, SORL1, and ABCA1, including 5 heterozygotes for multiple rare risk variants, suggesting non-monogenic inheritance, even in some autosomal-dominant-like pedigrees. CONCLUSION: We suggest that genetic screening should be proposed to all EOAD patients and should no longer be prioritized based on pedigree structure.

Determining priority indicators of utility for genomic testing in rare disease: A Delphi study.

PURPOSE: Determining the value of genomic tests in rare disease necessitates a broader conceptualization of genomic utility beyond diagnostic yield. Despite widespread discussion, consensus toward which aspects of value to consider is lacking. This study aimed to use expert opinion to identify and refine priority indicators of utility in rare disease genomic testing. METHODS: We used 2 survey rounds following Delphi methodology to obtain consensus on indicators of utility among experts involved in policy, clinical, research, and consumer advocacy leadership in Australia. We analyzed quantitative and qualitative data to identify, define, and determine priority indicators. RESULTS: Twenty-five experts completed round 1 and 18 completed both rounds. Twenty indicators reached consensus as a priority in value assessment, including those relating to prognostic information, timeliness of results, practical and health care outcomes, clinical accreditation, and diagnostic yield. Whereas indicators pertaining to discovery research, disutility, and factors secondary to primary reason for testing were considered less of a priority and were removed. CONCLUSION: This study obtained expert consensus on different utility indicators that are considered a priority in determining the value of genomic testing in rare disease in Australia. Indicators may inform a standardized approach to evidence generation and assessment to guide future research, decision making, and implementation efforts.

Measuring perceived utility of genomic sequencing: Development and validation of the GENEtic Utility (GENE-U) scale for pediatric diagnostic testing.

PURPOSE: Measuring the effects of genomic sequencing (GS) on patients and families is critical for translational research. We aimed to develop and validate an instrument to assess parents' perceived utility of pediatric diagnostic GS. METHODS: Informed by a 5-domain conceptual model, the study comprised 5 steps: (1) item writing, (2) cognitive testing, (3) pilot testing and item reduction, (4) psychometric testing, and (5) evaluation of construct validity. Parents of pediatric patients who had received results of clinically indicated GS participated in structured cognitive interviews and 2 rounds of surveys. After eliminating items based on theory and quantitative performance, we conducted an exploratory factor analysis and calculated Pearson correlations with related instruments. RESULTS: We derived the 21-item Pediatric Diagnostic version of the GENEtic Utility (GENE-U) scale, which has a 2-factor structure that includes an Informational Utility subscale (16 items, α = 0.91) and an Emotional Utility subscale (5 items, α = 0.71). Scores can be summed to calculate a Total scale score (α = 0.87). The Informational Utility subscale was strongly associated with empowerment and personal utility of GS, and the Emotional Utility subscale was moderately associated with psychosocial impact and depression and anxiety. CONCLUSION: The pediatric diagnostic GENE-U scale demonstrated good psychometric performance in this initial evaluation and could be a useful tool for translational genomics researchers, warranting additional validation.