Saturation mutagenesis-reinforced functional assays for disease-related genes.

Interpretation of disease-causing genetic variants remains a challenge in human genetics. Current costs and complexity of deep mutational scanning methods are obstacles for achieving genome-wide resolution of variants in disease-related genes. Our framework, saturation mutagenesis-reinforced functional assays (SMuRF), offers simple and cost-effective saturation mutagenesis paired with streamlined functional assays to enhance the interpretation of unresolved variants. Applying SMuRF to neuromuscular disease genes FKRP and LARGE1, we generated functional scores for all possible coding single-nucleotide variants, which aid in resolving clinically reported variants of uncertain significance. SMuRF also demonstrates utility in predicting disease severity, resolving critical structural regions, and providing training datasets for the development of computational predictors. Overall, our approach enables variant-to-function insights for disease genes in a cost-effective manner that can be broadly implemented by standard research laboratories.

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.

Chronic Stress Alters Striosome-Circuit Dynamics, Leading to Aberrant Decision-Making.

Effective evaluation of costs and benefits is a core survival capacity that in humans is considered as optimal, "rational" decision-making. This capacity is vulnerable in neuropsychiatric disorders and in the aftermath of chronic stress, in which aberrant choices and high-risk behaviors occur. We report that chronic stress exposure in rodents produces abnormal evaluation of costs and benefits resembling non-optimal decision-making in which choices of high-cost/high-reward options are sharply increased. Concomitantly, alterations in the task-related spike activity of medial prefrontal neurons correspond with increased activity of their striosome-predominant striatal projection neuron targets and with decreased and delayed striatal fast-firing interneuron activity. These effects of chronic stress on prefronto-striatal circuit dynamics could be blocked or be mimicked by selective optogenetic manipulation of these circuits. We suggest that altered excitation-inhibition dynamics of striosome-based circuit function could be an underlying mechanism by which chronic stress contributes to disorders characterized by aberrant decision-making under conflict. VIDEO ABSTRACT.

Navigating financial toxicity in patients with cancer: A multidisciplinary management approach.

Approximately one-half of individuals with cancer face personal economic burdens associated with the disease and its treatment, a problem known as financial toxicity (FT). FT more frequently affects socioeconomically vulnerable individuals and leads to subsequent adverse economic and health outcomes. Whereas multilevel systemic factors at the policy, payer, and provider levels drive FT, there are also accompanying intervenable patient-level factors that exacerbate FT in the setting of clinical care delivery. The primary strategy to intervene on FT at the patient level is financial navigation. Financial navigation uses comprehensive assessment of patients' risk factors for FT, guidance toward support resources, and referrals to assist patient financial needs during cancer care. Social workers or nurse navigators most frequently lead financial navigation. Oncologists and clinical provider teams are multidisciplinary partners who can support optimal FT management in the context of their clinical roles. Oncologists and clinical provider teams can proactively assess patient concerns about the financial hardship and employment effects of disease and treatment. They can respond by streamlining clinical treatment and care delivery planning and incorporating FT concerns into comprehensive goals of care discussions and coordinated symptom and psychosocial care. By understanding how age and life stage, socioeconomic, and cultural factors modify FT trajectory, oncologists and multidisciplinary health care teams can be engaged and informative in patient-centered, tailored FT management. The case presentations in this report provide a practical context to summarize authors' recommendations for patient-level FT management, supported by a review of key supporting evidence and a discussion of challenges to mitigating FT in oncology care. CA Cancer J Clin. 2022;72:437-453.

Meta-analysis and public policy: Reconciling the evidence on deworming.

The WHO recommends mass drug administration (MDA) for intestinal worm infections in areas with over 20% infection prevalence. Recent Cochrane meta-analyses endorse treatment of infected individuals but recommend against MDA. We conducted a theory-agnostic random-effects meta-analysis of the effect of multiple-dose MDA and a cost-effectiveness analysis. We estimate significant effects of MDA on child weight (0.15 kg, 95% CI: 0.07, 0.24; P < 0.001), mid-upper arm circumference (0.20 cm, 95% CI: 0.03, 0.37; P = 0.02), and height (0.09 cm, 95% CI: 0.01, 0.16; P = 0.02) when prevalence is over 20% but not on Hb (0.06 g/dL, 95% CI: -0.01, 0.14; P = 0.1). These results suggest that MDA is a cost-effective intervention, particularly in the settings where it is recommended by the WHO.

Higher total energy costs strain the elderly, especially low-income, across 31 developed countries.

Addressing the total energy cost burden of elderly people is essential for designing equitable and effective energy policies, especially in responding to energy crisis in an aging society. It is due to the double impact of energy price hikes on households-through direct impact on fuel bills and indirect impact on the prices of goods and services consumed. However, while examining the household energy cost burden of the elderly, their indirect energy consumption and associated cost burden remain poorly understood. This study quantifies and compares the direct and indirect energy footprints and associated total energy cost burdens for different age groups across 31 developed countries. It reveals that the elderly have larger per capita energy footprints, resulting from higher levels of both direct and indirect energy consumption compared with the younger age groups. More importantly, the elderly, especially the low-income elderly, have a higher total energy cost burden rate. As the share of elderly in the total population rapidly grows in these countries, the larger per capita energy footprint and associated cost burden rate of elderly people would make these aging countries more vulnerable in times of energy crises. It is therefore crucial to develop policies that aim to reduce energy consumption and costs, improve energy efficiency, and support low-income elderly populations. Such policies are necessary to reduce the vulnerability of these aging countries to the energy crisis.

Adopting electric school buses in the United States: Health and climate benefits.

Electric school buses have been proposed as an alternative to reduce the health and climate impacts of the current U.S. school bus fleet, of which a substantial share are highly polluting old diesel vehicles. However, the climate and health benefits of electric school buses are not well known. As they are substantially more costly than diesel buses, assessing their benefits is needed to inform policy decisions. We assess the health benefits of electric school buses in the United States from reduced adult mortality and childhood asthma onset risks due to exposure to ambient fine particulate matter (PM2.5). We also evaluate climate benefits from reduced greenhouse-gas emissions. We find that replacing the average diesel bus in the U.S. fleet in 2017 with an electric bus yields $84,200 in total benefits. Climate benefits amount to $40,400/bus, whereas health benefits amount to $43,800/bus due to 4.42*10-3 fewer PM2.5-attributable deaths ($40,000 of total) and 7.42*10-3 fewer PM2.5-attributable new childhood asthma cases ($3,700 of total). However, health benefits of electric buses vary substantially by driving location and model year (MY) of the diesel buses they replace. Replacing old, MY 2005 diesel buses in large cities yields $207,200/bus in health benefits and is likely cost-beneficial, although other policies that accelerate fleet turnover in these areas deserve consideration. Electric school buses driven in rural areas achieve small health benefits from reduced exposure to ambient PM2.5. Further research assessing benefits of reduced exposure to in-cabin air pollution among children riding buses would be valuable to inform policy decisions.

Policies, projections, and the social cost of carbon: Results from the DICE-2023 model.

The present study examines the assumptions, modeling structure, and results of DICE-2023, the revised Dynamic Integrated Model of Climate and the Economy (DICE), updated to 2023. The revision contains major changes in the treatment of risk, the carbon and climate modules, the treatment of nonindustrial greenhouse gases, discount rates, as well as updates on all the major components. Noteworthy changes are a significant reduction in the target for the optimal (cost-beneficial) temperature path, a lower cost of reaching the 2 °C target, an analysis of the impact of the Paris Accord, and a major increase in the estimated social cost of carbon.

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics.

Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy and are currently the mainstay, which possess higher target specificity and biological activity than small-molecule chemical drugs, making them efficient in regulating disease-related biological processes, and have significant potential in the development of personalized drugs. Currently, protein drugs are designed and developed for specific protein targets based on patient-specific protein data. However, due to the rapid development of two-dimensional gel electrophoresis and mass spectrometry, it is now widely recognized that a canonical protein actually includes multiple proteoforms, and the differences between these proteoforms will result in varying responses to drugs. The variation in the effects of different proteoforms can be significant and the impact can even alter the intended benefit of a drug, potentially making it harmful instead of lifesaving. As a result, we propose that protein drugs should shift from being targeted through the lens of protein (proteomics) to being targeted through the lens of proteoform (proteoformics). This will enable the development of personalized protein drugs that are better equipped to meet patients' specific needs and disease characteristics. With further development in the field of proteoformics, individualized drug therapy, especially personalized protein drugs aimed at proteoforms as a drug target, will improve the understanding of disease mechanisms, discovery of new drug targets and signaling pathways, provide a theoretical basis for the development of new drugs, aid doctors in conducting health risk assessments and making more cost-effective targeted prevention strategies conducted by artificial intelligence/machine learning, promote technological innovation, and provide more convenient treatment tailored to individualized patient profile, which will benefit the affected individuals and society at large.

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.

Cortical cell size regulates root metabolic cost.

It has been hypothesized that vacuolar occupancy in mature root cortical parenchyma cells regulates root metabolic cost and thereby plant fitness under conditions of drought, suboptimal nutrient availability, and increased soil mechanical impedance. However, the mechanistic role of vacuoles in reducing root metabolic cost was unproven. Here we provide evidence to support this hypothesis. We first show that root cortical cell size is determined by both cortical cell diameter and cell length. Significant genotypic variation for both cortical cell diameter (~1.1- to 1.5-fold) and cortical cell length (~ 1.3- to 7-fold) was observed in maize and wheat. GWAS and QTL analyses indicate cortical cell diameter and length are heritable and under independent genetic control. We identify candidate genes for both phenes. Empirical results from isophenic lines contrasting for cortical cell diameter and length show that increased cell size, due to either diameter or length, is associated with reduced root respiration, nitrogen content, and phosphorus content. RootSlice, a functional-structural model of root anatomy, predicts that an increased vacuolar: cytoplasmic ratio per unit cortical volume causes reduced root respiration and nutrient content. Ultrastructural imaging of cortical parenchyma cells with varying cortical diameter and cortical cell length confirms the in silico predictions and shows that an increase in cell size is correlated with increased vacuolar volume and reduced cytoplasmic volume. Vacuolar occupancy and its relationship with cell size merits further investigation as a phene for improving crop adaptation to edaphic stress.

Forecasting the Economic Burden of Cardiovascular Disease and Stroke in the United States Through 2050: A Presidential Advisory From the American Heart Association.

BACKGROUND: Quantifying the economic burden of cardiovascular disease and stroke over the coming decades may inform policy, health system, and community-level interventions for prevention and treatment. METHODS: We used nationally representative health, economic, and demographic data to project health care costs attributable to key cardiovascular risk factors (hypertension, diabetes, hypercholesterolemia) and conditions (coronary heart disease, stroke, heart failure, atrial fibrillation) through 2050. The human capital approach was used to estimate productivity losses from morbidity and premature mortality due to cardiovascular conditions. RESULTS: One in 3 US adults received care for a cardiovascular risk factor or condition in 2020. Annual inflation-adjusted (2022 US dollars) health care costs of cardiovascular risk factors are projected to triple between 2020 and 2050, from $400 billion to $1344 billion. For cardiovascular conditions, annual health care costs are projected to almost quadruple, from $393 billion to $1490 billion, and productivity losses are projected to increase by 54%, from $234 billion to $361 billion. Stroke is projected to account for the largest absolute increase in costs. Large relative increases among the Asian American population (497%) and Hispanic American population (489%) reflect the projected increases in the size of these populations. CONCLUSIONS: The economic burden of cardiovascular risk factors and overt cardiovascular disease in the United States is projected to increase substantially in the coming decades. Development and deployment of cost-effective programs and policies to promote cardiovascular health are urgently needed to rein in costs and to equitably enhance population health.

Brief Communication: The Predictable Network Topology of Evolutionary Genomic Constraint.

Large-scale comparative genomics studies offer valuable resources for understanding both functional and evolutionary rate constraints. It is suggested that constraint aligns with the topology of genomic networks, increasing toward the center, with intermediate nodes combining relaxed constraint with higher contributions to the phenotype due to pleiotropy. However, this pattern has yet to be demonstrated in vertebrates. This study shows that constraint intensifies toward the network's center in placental mammals. Genes with rate changes associated with emergence of hibernation cluster mostly toward intermediate positions, with higher constraint in faster-evolving genes, which is indicative of a "sweet spot" for adaptation. If this trend holds universally, network node metrics could predict high-constraint regions even in clades lacking empirical constraint data.

Functional Optimization in Distinct Tissues and Conditions Constrains the Rate of Protein Evolution.

Understanding the main determinants of protein evolution is a fundamental challenge in biology. Despite many decades of active research, the molecular and cellular mechanisms underlying the substantial variability of evolutionary rates across cellular proteins are not currently well understood. It also remains unclear how protein molecular function is optimized in the context of multicellular species and why many proteins, such as enzymes, are only moderately efficient on average. Our analysis of genomics and functional datasets reveals in multiple organisms a strong inverse relationship between the optimality of protein molecular function and the rate of protein evolution. Furthermore, we find that highly expressed proteins tend to be substantially more functionally optimized. These results suggest that cellular expression costs lead to more pronounced functional optimization of abundant proteins and that the purifying selection to maintain high levels of functional optimality significantly slows protein evolution. We observe that in multicellular species both the rate of protein evolution and the degree of protein functional efficiency are primarily affected by expression in several distinct cell types and tissues, specifically, in developed neurons with upregulated synaptic processes in animals and in young and fast-growing tissues in plants. Overall, our analysis reveals how various constraints from the molecular, cellular, and species' levels of biological organization jointly affect the rate of protein evolution and the level of protein functional adaptation.

Effectiveness and Cost-Effectiveness of Colorectal Cancer Screening With a Blood Test That Meets the Centers for Medicare & Medicaid Services Coverage Decision.

BACKGROUND & AIMS: A blood-based colorectal cancer (CRC) screening test may increase screening participation. However, blood tests may be less effective than current guideline-endorsed options. The Centers for Medicare & Medicaid Services (CMS) covers blood tests with sensitivity of at least 74% for detection of CRC and specificity of at least 90%. In this study, we investigate whether a blood test that meets these criteria is cost-effective. METHODS: Three microsimulation models for CRC (MISCAN-Colon, CRC-SPIN, and SimCRC) were used to estimate the effectiveness and cost-effectiveness of triennial blood-based screening (from ages 45 to 75 years) compared to no screening, annual fecal immunochemical testing (FIT), triennial stool DNA testing combined with an FIT assay, and colonoscopy screening every 10 years. The CMS coverage criteria were used as performance characteristics of the hypothetical blood test. We varied screening ages, test performance characteristics, and screening uptake in a sensitivity analysis. RESULTS: Without screening, the models predicted 77-88 CRC cases and 32-36 CRC deaths per 1000 individuals, costing $5.3-$5.8 million. Compared to no screening, blood-based screening was cost-effective, with an additional cost of $25,600-$43,700 per quality-adjusted life-year gained (QALYG). However, compared to FIT, triennial stool DNA testing combined with FIT, and colonoscopy, blood-based screening was not cost-effective, with both a decrease in QALYG and an increase in costs. FIT remained more effective (+5-24 QALYG) and less costly (-$3.2 to -$3.5 million) than blood-based screening even when uptake of blood-based screening was 20 percentage points higher than uptake of FIT. CONCLUSION: Even with higher screening uptake, triennial blood-based screening, with the CMS-specified minimum performance sensitivity of 74% and specificity of 90%, was not projected to be cost-effective compared with established strategies for colorectal cancer screening.

Comparative Effectiveness and Cost-Effectiveness of Colorectal Cancer Screening With Blood-Based Biomarkers (Liquid Biopsy) vs Fecal Tests or Colonoscopy.

BACKGROUND & AIMS: Colorectal cancer (CRC) screening is highly effective but underused. Blood-based biomarkers (liquid biopsy) could improve screening participation. METHODS: Using our established Markov model, screening every 3 years with a blood-based test that meets minimum Centers for Medicare & Medicaid Services' thresholds (CMSmin) (CRC sensitivity 74%, specificity 90%) was compared with established alternatives. Test attributes were varied in sensitivity analyses. RESULTS: CMSmin reduced CRC incidence by 40% and CRC mortality by 52% vs no screening. These reductions were less profound than the 68%-79% and 73%-81%, respectively, achieved with multi-target stool DNA (Cologuard; Exact Sciences) every 3 years, annual fecal immunochemical testing (FIT), or colonoscopy every 10 years. Assuming the same cost as multi-target stool DNA, CMSmin cost $28,500/quality-adjusted life-year gained vs no screening, but FIT, colonoscopy, and multi-target stool DNA were less costly and more effective. CMSmin would match FIT's clinical outcomes if it achieved 1.4- to 1.8-fold FIT's participation rate. Advanced precancerous lesion (APL) sensitivity was a key determinant of a test's effectiveness. A paradigm-changing blood-based test (sensitivity >90% for CRC and 80% for APL; 90% specificity; cost ≤$120-$140) would be cost-effective vs FIT at comparable participation. CONCLUSIONS: CMSmin could contribute to CRC control by achieving screening in those who will not use established methods. Substituting blood-based testing for established effective CRC screening methods will require higher CRC and APL sensitivities that deliver programmatic benefits matching those of FIT. High APL sensitivity, which can result in CRC prevention, should be a top priority for screening test developers. APL detection should not be penalized by a definition of test specificity that focuses on CRC only.

McAN: a novel computational algorithm and platform for constructing and visualizing haplotype networks.

Haplotype networks are graphs used to represent evolutionary relationships between a set of taxa and are characterized by intuitiveness in analyzing genealogical relationships of closely related genomes. We here propose a novel algorithm termed McAN that considers mutation spectrum history (mutations in ancestry haplotype should be contained in descendant haplotype), node size (corresponding to sample count for a given node) and sampling time when constructing haplotype network. We show that McAN is two orders of magnitude faster than state-of-the-art algorithms without losing accuracy, making it suitable for analysis of a large number of sequences. Based on our algorithm, we developed an online web server and offline tool for haplotype network construction, community lineage determination, and interactive network visualization. We demonstrate that McAN is highly suitable for analyzing and visualizing massive genomic data and is helpful to enhance the understanding of genome evolution. Availability: Source code is written in C/C++ and available at https://github.com/Theory-Lun/McAN and https://ngdc.cncb.ac.cn/biocode/tools/BT007301 under the MIT license. Web server is available at https://ngdc.cncb.ac.cn/bit/hapnet/. SARS-CoV-2 dataset are available at https://ngdc.cncb.ac.cn/ncov/. Contact: songshh@big.ac.cn (Song S), zhaowm@big.ac.cn (Zhao W), baoym@big.ac.cn (Bao Y), zhangzhang@big.ac.cn (Zhang Z), ybxue@big.ac.cn (Xue Y).

Development, validation and application of single molecule molecular inversion probe based novel integrated genetic screening method for 29 common lysosomal storage disorders in India.

BACKGROUND: Current clinical diagnosis pathway for lysosomal storage disorders (LSDs) involves sequential biochemical enzymatic tests followed by DNA sequencing, which is iterative, has low diagnostic yield and is costly due to overlapping clinical presentations. Here, we describe a novel low-cost and high-throughput sequencing assay using single-molecule molecular inversion probes (smMIPs) to screen for causative single nucleotide variants (SNVs) and copy number variants (CNVs) in genes associated with 29 common LSDs in India. RESULTS: 903 smMIPs were designed to target exon and exon-intron boundaries of targeted genes (n = 23; 53.7 kb of the human genome) and were equimolarly pooled to create a sequencing library. After extensive validation in a cohort of 50 patients, we screened 300 patients with either biochemical diagnosis (n = 187) or clinical suspicion (n = 113) of LSDs. A diagnostic yield of 83.4% was observed in patients with prior biochemical diagnosis of LSD. Furthermore, diagnostic yield of 73.9% (n = 54/73) was observed in patients with high clinical suspicion of LSD in contrast with 2.4% (n = 1/40) in patients with low clinical suspicion of LSD. In addition to detecting SNVs, the assay could detect single and multi-exon copy number variants with high confidence. Critically, Niemann-Pick disease type C and neuronal ceroid lipofuscinosis-6 diseases for which biochemical testing is unavailable, could be diagnosed using our assay. Lastly, we observed a non-inferior performance of the assay in DNA extracted from dried blood spots in comparison with whole blood. CONCLUSION: We developed a flexible and scalable assay to reliably detect genetic causes of 29 common LSDs in India. The assay consolidates the detection of multiple variant types in multiple sample types while having improved diagnostic yield at same or lower cost compared to current clinical paradigm.

The financial burden and distress of patients with cancer: Understanding and stepping-up action on the financial toxicity of cancer treatment.

"Financial toxicity" has now become a familiar term used in the discussion of cancer drugs, and it is gaining traction in the literature given the high price of newer classes of therapies. However, as a phenomenon in the contemporary treatment and care of people with cancer, financial toxicity is not fully understood, with the discussion on mitigation mainly geared toward interventions at the health system level. Although important, health policy prescriptions take time before their intended results manifest, if they are implemented at all. They require corresponding strategies at the individual patient level. In this review, the authors discuss the nature of financial toxicity, defined as the objective financial burden and subjective financial distress of patients with cancer, as a result of treatments using innovative drugs and concomitant health services. They discuss coping with financial toxicity by patients and how maladaptive coping leads to poor health and nonhealth outcomes. They cover management strategies for oncologists, including having the difficult and urgent conversation about the cost and value of cancer treatment, availability of and access to resources, and assessment of financial toxicity as part of supportive care in the provision of comprehensive cancer care. CA Cancer J Clin 2018;68:153-165. © 2018 American Cancer Society.

Resilience and Disaster: Flexible Adaptation in the Face of Uncertain Threat.

Disasters cause sweeping damage, hardship, and loss of life. In this article, we first consider the dominant psychological approach to disasters and its narrow focus on psychopathology (e.g., posttraumatic stress disorder). We then review research on a broader approach that has identified heterogeneous, highly replicable trajectories of outcome, the most common being stable mental health or resilience. We review trajectory research for different types of disasters, including the COVID-19 pandemic. Next, we consider correlates of the resilience trajectory and note their paradoxically limited ability to predict future resilient outcomes. Research using machine learning algorithms improved prediction but has not yet illuminated the mechanism behind resilient adaptation. To that end, we propose a more direct psychological explanation for resilience based on research on the motivational and mechanistic components of regulatory flexibility. Finally, we consider how future research might leverage new computational approaches to better capture regulatory flexibility in real time.