Snapshot: Trial Types in Precision Medicine.

Integrating precision diagnostics into personalized treatments requires understanding how biomarkers relate to clinical outcomes. Various clinical data collection methods exist, each with strengths and weaknesses. Interventional data are high quality but narrowly focused. Real-world data (RWD) provide broader information but with variable quality. Master protocols allow better efficiency in data collection. The master observational trial bridges the gap between interventional and retrospective RWD collection methods. To view this SnapShot, open or download the PDF.

Data Harmonization for a Molecularly Driven Health System.

Data commons have emerged as the best current method for enabling data aggregation across multiple projects and multiple data sources. Good data harmonization techniques are critical to maintain quality of data within a data commons, as well as to allow future meta-analysis across different data commons. We present some of the current best practices for data harmonization.

Cryo-EM in molecular and cellular biology.

This review summarizes the current state of methods and results achievable by cryo-electron microscopy (cryo-EM) imaging for molecular, cell, and structural biologists who wish to understand what is required and how it might help to address their research questions. It covers some of the main issues in sample preparation, microscopes and data collection, image processing, three-dimensional (3D) reconstruction, and validation and interpretation of the resulting EM density maps and atomic models.

Financial incentives for vaccination do not have negative unintended consequences.

Financial incentives to encourage healthy and prosocial behaviours often trigger initial behavioural change1-11, but a large academic literature warns against using them12-16. Critics warn that financial incentives can crowd out prosocial motivations and reduce perceived safety and trust, thereby reducing healthy behaviours when no payments are offered and eroding morals more generally17-24. Here we report findings from a large-scale, pre-registered study in Sweden that causally measures the unintended consequences of offering financial incentives for taking the first dose of a COVID-19 vaccine. We use a unique combination of random exposure to financial incentives, population-wide administrative vaccination records and rich survey data. We find no negative consequences of financial incentives; we can reject even small negative impacts of offering financial incentives on future vaccination uptake, morals, trust and perceived safety. In a complementary study, we find that informing US residents about the existence of state incentive programmes also has no negative consequences. Our findings inform not only the academic debate on financial incentives for behaviour change but also policy-makers who consider using financial incentives to change behaviour.

An open science study of ageing in companion dogs.

The Dog Aging Project is a long-term longitudinal study of ageing in tens of thousands of companion dogs. The domestic dog is among the most variable mammal species in terms of morphology, behaviour, risk of age-related disease and life expectancy. Given that dogs share the human environment and have a sophisticated healthcare system but are much shorter-lived than people, they offer a unique opportunity to identify the genetic, environmental and lifestyle factors associated with healthy lifespan. To take advantage of this opportunity, the Dog Aging Project will collect extensive survey data, environmental information, electronic veterinary medical records, genome-wide sequence information, clinicopathology and molecular phenotypes derived from blood cells, plasma and faecal samples. Here, we describe the specific goals and design of the Dog Aging Project and discuss the potential for this open-data, community science study to greatly enhance understanding of ageing in a genetically variable, socially relevant species living in a complex environment.

Trial of N-Acetyl-l-Leucine in Niemann-Pick Disease Type C.

BACKGROUND: Niemann-Pick disease type C is a rare lysosomal storage disorder. We evaluated the safety and efficacy of N-acetyl-l-leucine (NALL), an agent that potentially ameliorates lysosomal and metabolic dysfunction, for the treatment of Niemann-Pick disease type C. METHODS: In this double-blind, placebo-controlled, crossover trial, we randomly assigned patients 4 years of age or older with genetically confirmed Niemann-Pick disease type C in a 1:1 ratio to receive NALL for 12 weeks, followed by placebo for 12 weeks, or to receive placebo for 12 weeks, followed by NALL for 12 weeks. NALL or matching placebo was administered orally two to three times per day, with patients 4 to 12 years of age receiving weight-based doses (2 to 4 g per day) and those 13 years of age or older receiving a dose of 4 g per day. The primary end point was the total score on the Scale for the Assessment and Rating of Ataxia (SARA; range, 0 to 40, with lower scores indicating better neurologic status). Secondary end points included scores on the Clinical Global Impression of Improvement, the Spinocerebellar Ataxia Functional Index, and the Modified Disability Rating Scale. Crossover data from the two 12-week periods in each group were included in the comparisons of NALL with placebo. RESULTS: A total of 60 patients 5 to 67 years of age were enrolled. The mean baseline SARA total scores used in the primary analysis were 15.88 before receipt of the first dose of NALL (60 patients) and 15.68 before receipt of the first dose of placebo (59 patients; 1 patient never received placebo). The mean (±SD) change from baseline in the SARA total score was -1.97±2.43 points after 12 weeks of receiving NALL and -0.60±2.39 points after 12 weeks of receiving placebo (least-squares mean difference, -1.28 points; 95% confidence interval, -1.91 to -0.65; P<0.001). The results for the secondary end points were generally supportive of the findings in the primary analysis, but these were not adjusted for multiple comparisons. The incidence of adverse events was similar with NALL and placebo, and no treatment-related serious adverse events occurred. CONCLUSIONS: Among patients with Niemann-Pick disease type C, treatment with NALL for 12 weeks led to better neurologic status than placebo. A longer period is needed to determine the long-term effects of this agent in patients with Niemann-Pick disease type C. (Funded by IntraBio; ClinicalTrials.gov number, NCT05163288; EudraCT number, 2021-005356-10.).

Mapping carbon accumulation potential from global natural forest regrowth.

To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy.

Advancing interdisciplinary science for disrupting wildlife trafficking networks.

Wildlife trafficking, whether local or transnational in scope, undermines sustainable development efforts, degrades cultural resources, endangers species, erodes the local and global economy, and facilitates the spread of zoonotic diseases. Wildlife trafficking networks (WTNs) occupy a unique gray space in supply chains-straddling licit and illicit networks, supporting legitimate and criminal workforces, and often demonstrating high resilience in their sourcing flexibility and adaptability. Authorities in different sectors desire, but frequently lack knowledge about how to allocate resources to disrupt illicit wildlife supply networks and prevent negative collateral impacts. Novel conceptualizations and a deeper scientific understanding of WTN structures are needed to help unravel the dynamics of interaction between disruption and resilience while accommodating socioenvironmental context. We use the case of ploughshare tortoise trafficking to help illustrate the potential of key advancements in interdisciplinary thinking. Insights herein suggest a significant need and opportunity for scientists to generate new science-based recommendations for WTN-related data collection and analysis for supply chain visibility, shifts in illicit supply chain dominance, network resilience, or limits of the supplier base.

Discordance in chromosomal and self-reported sex in the UK Biobank: Implications for transgender- and intersex-inclusive data collection.

There is growing need to distinguish between sex and gender. While sex is assigned at birth, gender is socially constructed and may not correspond to one's assigned sex. However, in most research studies, sex or gender is assessed in isolation or the terms are used interchangeably, which has implications for research accuracy and inclusivity. We used data from the UK Biobank to quantify the prevalence of disagreement between chromosomal and self-reported sex and identify potential reasons for discordance. Among approximately 200 individuals with sex discordance, 71% of discordances were potentially explained by the presence of intersex traits or transgender identity. The findings indicate that when describing sex- and/or gender-specific differences in health, researchers may be limited in their ability to draw conclusions regarding specific sex and/or gender health information.

GWAS Central: an expanding resource for finding and visualising genotype and phenotype data from genome-wide association studies.

The GWAS Central resource gathers and curates extensive summary-level genome-wide association study (GWAS) data and puts a range of user-friendly but powerful website tools for the comparison and visualisation of GWAS data at the fingertips of researchers. Through our continued efforts to harmonise and import data received from GWAS authors and consortia, and data sets actively collected from public sources, the database now contains over 72.5 million P-values for over 5000 studies testing over 7.4 million unique genetic markers investigating over 1700 unique phenotypes. Here, we describe an update to integrate this extensive data collection with mouse disease model data to support insights into the functional impact of human genetic variation. GWAS Central has expanded to include mouse gene-phenotype associations observed during mouse gene knockout screens. To allow similar cross-species phenotypes to be compared, terms from mammalian and human phenotype ontologies have been mapped. New interactive interfaces to find, correlate and view human and mouse genotype-phenotype associations are included in the website toolkit. Additionally, the integrated browser for interrogating multiple association data sets has been updated and a GA4GH Beacon API endpoint has been added for discovering variants tested in GWAS. The GWAS Central resource is accessible at https://www.gwascentral.org/.

M6AREG: m6A-centered regulation of disease development and drug response.

As the most prevalent internal modification in eukaryotic RNAs, N6-methyladenosine (m6A) has been discovered to play an essential role in cellular proliferation, metabolic homeostasis, embryonic development, etc. With the rapid accumulation of research interest in m6A, its crucial roles in the regulations of disease development and drug response are gaining more and more attention. Thus, a database offering such valuable data on m6A-centered regulation is greatly needed; however, no such database is as yet available. Herein, a new database named 'M6AREG' is developed to (i) systematically cover, for the first time, data on the effects of m6A-centered regulation on both disease development and drug response, (ii) explicitly describe the molecular mechanism underlying each type of regulation and (iii) fully reference the collected data by cross-linking to existing databases. Since the accumulated data are valuable for researchers in diverse disciplines (such as pathology and pathophysiology, clinical laboratory diagnostics, medicinal biochemistry and drug design), M6AREG is expected to have many implications for the future conduct of m6A-based regulation studies. It is currently accessible by all users at: https://idrblab.org/m6areg/.

The impact of flooding on food security across Africa.

Recent record rainfall and flood events have prompted increased attention to flood impacts on human systems. Information regarding flood effects on food security is of particular importance for humanitarian organizations and is especially valuable across Africa's rural areas that contribute to regional food supplies. We quantitatively evaluate where and to what extent flooding impacts food security across Africa, using a Granger causality analysis and panel modeling approaches. Within our modeled areas, we find that ∼12% of the people that experienced food insecurity from 2009 to 2020 had their food security status affected by flooding. Furthermore, flooding and its associated meteorological conditions can simultaneously degrade food security locally while enhancing it at regional spatial scales, leading to large variations in overall food security outcomes. Dedicated data collection at the intersection of flood events and associated food security measures across different spatial and temporal scales are required to better characterize the extent of flood impact and inform preparedness, response, and recovery needs.

Balancing data privacy and usability in the federal statistical system.

The federal statistical system is experiencing competing pressures for change. On the one hand, for confidentiality reasons, much socially valuable data currently held by federal agencies is either not made available to researchers at all or only made available under onerous conditions. On the other hand, agencies which release public databases face new challenges in protecting the privacy of the subjects in those databases, which leads them to consider releasing fewer data or masking the data in ways that will reduce their accuracy. In this essay, we argue that the discussion has not given proper consideration to the reduced social benefits of data availability and their usability relative to the value of increased levels of privacy protection. A more balanced benefit-cost framework should be used to assess these trade-offs. We express concerns both with synthetic data methods for disclosure limitation, which will reduce the types of research that can be reliably conducted in unknown ways, and with differential privacy criteria that use what we argue is an inappropriate measure of disclosure risk. We recommend that the measure of disclosure risk used to assess all disclosure protection methods focus on what we believe is the risk that individuals should care about, that more study of the impact of differential privacy criteria and synthetic data methods on data usability for research be conducted before either is put into widespread use, and that more research be conducted on alternative methods of disclosure risk reduction that better balance benefits and costs.

Middle Eastern and North African Americans may not be perceived, nor perceive themselves, to be White.

People of Middle Eastern and North African (MENA) descent are categorized as non-White in many Western countries but counted as White on the US Census. Yet, it is not clear that MENA people see themselves or are seen by others as White. We examine both sides of this ethnoracial boundary in two experiments. First, we examined how non-MENA White and MENA individuals perceive the racial status of MENA traits (external categorization), and then, how MENA individuals identify themselves (self-identification). We found non-MENA Whites and MENAs consider MENA-related traits-including ancestry, names, and religion-to be MENA rather than White. Furthermore, when given the option, most MENA individuals self-identify as MENA or as MENA and White, particularly second-generation individuals and those who identify as Muslim. In addition, MENAs who perceive more anti-MENA discrimination are more likely to embrace a MENA identity, which suggests that perceived racial hostility may be activating a stronger group identity. Our findings provide evidence about the suitability of adding a separate MENA label to the race/ethnicity identification question in the US Census, and suggest MENAs' official designation as White may not correspond to their lived experiences nor to others' perceptions. As long as MENA Americans remain aggregated with Whites, potential inequalities they face will remain hidden.

Threatened Species Initiative: Empowering conservation action using genomic resources.

Globally, 15,521 animal species are listed as threatened by the International Union for the Conservation of Nature, and of these less than 3% have genomic resources that can inform conservation management. To combat this, global genome initiatives are developing genomic resources, yet production of a reference genome alone does not conserve a species. The reference genome allows us to develop a suite of tools to understand both genome-wide and functional diversity within and between species. Conservation practitioners can use these tools to inform their decision-making. But, at present there is an implementation gap between the release of genome information and the use of genomic data in applied conservation by conservation practitioners. In May 2020, we launched the Threatened Species Initiative and brought a consortium of genome biologists, population biologists, bioinformaticians, population geneticists, and ecologists together with conservation agencies across Australia, including government, zoos, and nongovernment organizations. Our objective is to create a foundation of genomic data to advance our understanding of key Australian threatened species, and ultimately empower conservation practitioners to access and apply genomic data to their decision-making processes through a web-based portal. Currently, we are developing genomic resources for 61 threatened species from a range of taxa, across Australia, with more than 130 collaborators from government, academia, and conservation organizations. Developed in direct consultation with government threatened-species managers and other conservation practitioners, herein we present our framework for meeting their needs and our systematic approach to integrating genomics into threatened species recovery.

Proceedings from the inaugural Artificial Intelligence in Primary Immune Deficiencies (AIPID) conference.

Here, we summarize the proceedings of the inaugural Artificial Intelligence in Primary Immune Deficiencies conference, during which experts and advocates gathered to advance research into the applications of artificial intelligence (AI), machine learning, and other computational tools in the diagnosis and management of inborn errors of immunity (IEIs). The conference focused on the key themes of expediting IEI diagnoses, challenges in data collection, roles of natural language processing and large language models in interpreting electronic health records, and ethical considerations in implementation. Innovative AI-based tools trained on electronic health records and claims databases have discovered new patterns of warning signs for IEIs, facilitating faster diagnoses and enhancing patient outcomes. Challenges in training AIs persist on account of data limitations, especially in cases of rare diseases, overlapping phenotypes, and biases inherent in current data sets. Furthermore, experts highlighted the significance of ethical considerations, data protection, and the necessity for open science principles. The conference delved into regulatory frameworks, equity in access, and the imperative for collaborative efforts to overcome these obstacles and harness the transformative potential of AI. Concerted efforts to successfully integrate AI into daily clinical immunology practice are still needed.