Fitting consistent knowledge into the planning process: An integrated database on adaptation and mitigation measures in Europe.

Climate action is far from meeting the internationally agreed adaptation and mitigation goals. Even though climate action planning has increased since the Paris Agreement in 2015, the implementation rate of those plans remains low. Climate planning literature claims that accounting for long-term planning and implementation times, accurately estimating costs, identifying synergies and trade-offs between measures, or considering justice and equity issues might increase the quality of climate plans and facilitate the further implementation of climate actions. Also, there is no uniform way of responding to the climate crisis. Existing climate action databases typically focus on a particular type of response, sector, hazard, or type. In parallel, national governments and international initiatives provide tools and guidelines to facilitate the development of climate action plans. However, the primary climate action recording and monitoring initiatives and projects do not share the same framework as those tools, resulting in a lost opportunity to improve climate actions' knowledge transferability. Thus, we reviewed nine existing databases of adaptation and five mitigation databases, comprising a total of 7.130 adaptation actions and 11.409 mitigation actions, and detected a lack of alignment with climate planning practices and claims. Furthermore, we revealed a lack of coherency regarding the level of abstraction of climate actions and their role in the implementation process. Not all climate actions are meant to operate similarly from a planning perspective: while some had a direct outcome on the target indicators, others are thought to facilitate their implementation. Ultimately, we created a new integrated database of adaptation and mitigation measures in Europe, focusing exclusively on climate planning and implementation practices. First, we identified specific and transferable mitigation and adaptation measures and instruments through an originally designed decision tree. Second, we harmonised the collection of climate actions in a unique framework based on one of the biggest climate planning initiatives: the Sustainable and Energy Climate Action Plans by the Covenant of Mayors. Our integrated database of adaptation and mitigation measures (1) classifies and relates the different types of climate actions; (2) provides data that may improve the quality of climate plans and facilitate implementation; (3) allows a better perspective of systematic problems by identifying potential synergies and trade-offs; and (4) defines and characterises measures using a framework that draws on actual practice. The database compiles a total of 191 adaptation measures, 188 mitigation measures, and 97 measures that account for each, and a total of 609 associated instruments. For monitoring their outcomes, 93 Sustainable Development Goals relevant indicators are included.

Genetic influence on within-person longitudinal change in anthropometric traits in the UK Biobank.

The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2-5% for height, sitting height, body mass index (BMI) and weight (P ≤ 2.4 × 10-3). We also analysed longitudinal trait change and show a loss of both average height and weight beyond about 70 years of age. A variant tracking the Alzheimer's risk APOE- E 4 allele (rs429358) was significantly associated with weight loss ( ß = -0.047 kg per yr, s.e. 0.007, P = 2.2 × 10-11), and using 2-sample Mendelian Randomisation we detected a relationship consistent with causality between decreased lumbar spine bone mineral density and height loss (bxy = 0.011, s.e. 0.003, P = 3.5 × 10-4). Finally, population-level variance quantitative trait loci (vQTL) were consistent with within-person variability for several traits, indicating an overlap between trait variability assessed at the population or individual level. Our findings help elucidate the genetic influence on trait-change within an individual and highlight disease risks associated with these changes.

Antigenic Characterization of Circulating and Emerging SARS-CoV-2 Variants in the U.S. throughout the Delta to Omicron Waves.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has evolved into numerous lineages with unique spike mutations and caused multiple epidemics domestically and globally. Although COVID-19 vaccines are available, new variants with the capacity for immune evasion continue to emerge. To understand and characterize the evolution of circulating SARS-CoV-2 variants in the U.S., the Centers for Disease Control and Prevention (CDC) initiated the National SARS-CoV-2 Strain Surveillance (NS3) program and has received thousands of SARS-CoV-2 clinical specimens from across the nation as part of a genotype to phenotype characterization process. Focus reduction neutralization with various antisera was used to antigenically characterize 143 SARS-CoV-2 Delta, Mu and Omicron subvariants from selected clinical specimens received between May 2021 and February 2023, representing a total of 59 unique spike protein sequences. BA.4/5 subvariants BU.1, BQ.1.1, CR.1.1, CQ.2 and BA.4/5 + D420N + K444T; BA.2.75 subvariants BM.4.1.1, BA.2.75.2, CV.1; and recombinant Omicron variants XBF, XBB.1, XBB.1.5 showed the greatest escape from neutralizing antibodies when analyzed against post third-dose original monovalent vaccinee sera. Post fourth-dose bivalent vaccinee sera provided better protection against those subvariants, but substantial reductions in neutralization titers were still observed, especially among BA.4/5 subvariants with both an N-terminal domain (NTD) deletion and receptor binding domain (RBD) substitutions K444M + N460K and recombinant Omicron variants. This analysis demonstrated a framework for long-term systematic genotype to antigenic characterization of circulating and emerging SARS-CoV-2 variants in the U.S., which is critical to assessing their potential impact on the effectiveness of current vaccines and antigen recommendations for future updates.

Loci on chromosome 20 interact with rs16969968 to influence cigarettes per day in European ancestry individuals.

BACKGROUND: The understanding of the molecular genetic contributions to smoking is largely limited to the additive effects of individual single nucleotide polymorphisms (SNPs), but the underlying genetic risk is likely to also include dominance, epistatic, and gene-environment interactions. METHODS: To begin to address this complexity, we attempted to identify genetic interactions between rs16969968, the most replicated SNP associated with smoking quantity, and all SNPs and genes across the genome. RESULTS: Using the UK Biobank European subsample, we found one SNP, rs1892967, and two genes, PCNA and TMEM230, that showed a significant genome-wide interaction with rs16969968 for log10 CPD and raw CPD, respectively, in a sample of 116 442 individuals who self-reported currently or previously smoking. We extended these analyses to individuals of South Asian descent and meta-analyzed the combined sample of 117 212 individuals of European and South Asian ancestry. We replicated the gene findings in a meta-analysis of five Finnish samples (N=40 140): FinHealth, FINRISK, Finnish Twin Cohort, GeneRISK, and Health-2000-2011. CONCLUSIONS: To our knowledge, this represents the first reliable epistatic association between single nucleotide polymorphisms for smoking behaviors and provides a novel direction for possible future functional studies related to this interaction. Furthermore, this work demonstrates the feasibility of these analyses by pooling multiple datasets across various ancestries, which may be applied to other top SNPs for smoking and/or other phenotypes.

In-field detection and characterization of B/Victoria lineage deletion variant viruses causing early influenza activity and an outbreak in Louisiana, 2019.

Background: In 2019, the Louisiana Department of Health reported an early influenza B/Victoria (B/VIC) virus outbreak. Method: As it was an atypically large outbreak, we deployed to Louisiana to investigate it using genomics and a triplex real-time RT-PCR assay to detect three antigenically distinct B/VIC lineage variant viruses. Results: The investigation indicated that B/VIC V1A.3 subclade, containing a three amino acid deletion in the hemagglutinin and known to be antigenically distinct to the B/Colorado/06/2017 vaccine virus, was the most prevalent circulating virus within the specimens evaluated (86/88 in real-time RT-PCR). Conclusion: This work underscores the value of portable platforms for rapid, onsite pathogen characterization.

Clostridioides difficile infection across the lifespan: Estimation using life tables.

Using a life tables approach with 2011-2017 claims data, we calculated lifetime risks of Clostridioides difficile infection (CDI) beginning at age 18 years. The lifetime CDI risk rates were 32% in female patients insured by Medicaid, 10% in commercially insured male patients, and almost 40% in females with end-stage renal disease.

Targeted amplification and genetic sequencing of the severe acute respiratory syndrome coronavirus 2 surface glycoprotein.

IMPORTANCE: The COVID-19 pandemic was accompanied by an unprecedented surveillance effort. The resulting data were and will continue to be critical for surveillance and control of SARS-CoV-2. However, some genomic surveillance methods experienced challenges as the virus evolved, resulting in incomplete and poor quality data. Complete and quality coverage, especially of the S-gene, is important for supporting the selection of vaccine candidates. As such, we developed a robust method to target the S-gene for amplification and sequencing. By focusing on the S-gene and imposing strict coverage and quality metrics, we hope to increase the quality of surveillance data for this continually evolving gene. Our technique is currently being deployed globally to partner laboratories, and public health representatives from 79 countries have received hands-on training and support. Expanding access to quality surveillance methods will undoubtedly lead to earlier detection of novel variants and better inform vaccine strain selection.

Characterization of the In Vivo Deuteration of Native Phospholipids by Mass Spectrometry Yields Guidelines for Their Regiospecific Customization.

Customization of deuterated biomolecules is vital for many advanced biological experiments including neutron scattering. However, because it is challenging to control the proportion and regiospecificity of deuterium incorporation in live systems, often only two or three synthetic lipids are mixed together to form simplistic model membranes. This limits the applicability and biological accuracy of the results generated with these synthetic membranes. Despite some limited prior examination of deuterating Escherichia coli lipids in vivo, this approach has not been widely implemented. Here, an extensive mass spectrometry-based profiling of E. coli phospholipid deuteration states with several different growth media was performed, and a computational method to describe deuterium distributions with a one-number summary is introduced. The deuteration states of 36 lipid species were quantitatively profiled in 15 different growth conditions, and tandem mass spectrometry was used to reveal deuterium localization. Regressions were employed to enable the prediction of lipid deuteration for untested conditions. Small-angle neutron scattering was performed on select deuterated lipid samples, which validated the deuteration states calculated from the mass spectral data. Based on these experiments, guidelines for the design of specifically deuterated phospholipids are described. This unlocks even greater capabilities from neutron-based techniques, enabling experiments that were formerly impossible.

Non-random Mating Patterns in Education, Mental, and Somatic Health: A Population Study on Within- and Cross-Trait Associations.

Partners resemble each other on many traits, such as health and education. The traits are usually studied one by one in data from established couples and with potential participation bias. We studied all Norwegian parents who had their first child between 2016 and 2020 (N=187,926) and the siblings of these parents. We analysed grade point averages (GPA), educational attainment (EA), and medical records with prospective diagnostic data on 10 mental and 10 somatic health conditions measured 10 to 5 years before childbirth. We found stronger partner similarity in mental (median r=0.14) than in somatic health conditions (median r=0.04), with ubiquitous cross-trait correlations for mental health conditions (median r=0.13). GPA correlated 0.43 and EA 0.47 between partners. High GPA or EA was associated with better mental (median r=-0.16) and somatic (median r=-0.08) health in partners. Elevated correlations for mental health (median r=0.25) in established couples indicated convergence. Analyses of data on siblings and in-laws revealed deviations from direct assortment, suggesting instead indirect assortment based on related traits. GPA and EA accounted for 30-40% of the partner correlations in health. This has implications for the distribution of risk factors among children and for studies of intergenerational transmission.

Recurrence of Metastatic Crohn's Disease after Surgical Resection.

A 36-year-old woman presented to the emergency department with a 1-day history of purulent perianal and vulvar discharge. She had a 25-year history of Crohn's disease (CD), and 13 years prior had received a total colectomy with end ileostomy. She had vulvar biopsies 5 years prior to presentation, demonstrating noncaseating granulomas consistent with metastatic Crohn's disease (MCD). Throughout the course of her disease, she had a failed treatment with adalimumab, certolizumab, methotrexate, and 6-mercaptopurine. She had received a radical vulvectomy 1 year prior to presenting to control recurrent vulvar abscesses and MCD while receiving monthly subcutaneous infliximab 10 mg/kg body weight. Dermatology was consulted at presentation, and the physical examination revealed tender, linear ulcerations with a granulated appearance and depigmentation on the natal cleft and vulva (Figures 1 and 2). Computerized tomography (CT) scan of the abdomen and pelvis indicated thickening of soft tissue without evidence of abscesses, fluid collection, or fistulae. Given the distribution and morphology of lesions with a history of biopsy-proven MCD, the patient was diagnosed with a flare of MCD.

The challenges of sociogenomics make it more, not less, worthy of careful and innovative investigation.

Influences on social traits involve a tangled interplay of genetic, social, and environmental factors. Moreover, there is increasing awareness that gene-environment correlations are real and potentially measurable. Such gene-environment correlations can mislead if they are uncontrolled and genetic associations are interpreted as being purely because of direct genetic effects. This complexity is cause for more and better investigation, not a reason to refrain from researching one of the potentially important factors (genetics) influencing trait variation.

Increased Incidence and Risk of Septicemia and Urinary Tract Infection After Clostridioides difficile Infection.

Background: Although increased occurrence of septicemia in persons with Clostridioides difficile infection (CDI) has been reported, incidence rates and risk of septicemia and urinary tract infection (UTI) after CDI are unclear. Methods: The first episode of CDI was identified using 2011-2017 MarketScan and CMS Medicare data and CDI cases categorized by standard surveillance definitions. Uninfected persons were frequency matched 4:1 to cases by the CDI case surveillance definition. Multivariable Cox proportional hazards models were used to identify risk factors for septicemia and UTI within 90 days of CDI onset, accounting for the competing risk of death in the Medicare population. Results: The incidence of septicemia was highest after hospital-onset CDI in the Medicare, younger commercial, and younger Medicaid populations (25.5%, 15.7%, and 19.5%, respectively) and lowest in those with community-associated CDI (3.8%, 4.3%, and 8.3%, respectively). In contrast, the incidence of UTI was highest in those with other healthcare facility onset CDI in all 3 populations (32.1%, 24.2%, and 18.1%, respectively). Hospital-onset CDI was associated with highest risk of septicemia compared with uninfected controls in all 3 populations. In the younger populations, risk of septicemia was more uniform across the CDI surveillance definitions. The risk of UTI was significantly higher in all CDI surveillance categories compared to uninfected controls, and among CDI cases it was lowest in those with community-associated CDI. Conclusions: The incidence of septicemia is high after CDI, particularly after hospital-onset infection. Additional preventive measures are needed to reduce infectious complications of CDI.

Evidence of correlations between human partners based on systematic reviews and meta-analyses of 22 traits and UK Biobank analysis of 133 traits.

Positive correlations between mates can increase trait variation and prevalence, as well as bias estimates from genetically informed study designs. While past studies of similarity between human mating partners have largely found evidence of positive correlations, to our knowledge, no formal meta-analysis has examined human partner correlations across multiple categories of traits. Thus, we conducted systematic reviews and random-effects meta-analyses of human male-female partner correlations across 22 traits commonly studied by psychologists, economists, sociologists, anthropologists, epidemiologists and geneticists. Using ScienceDirect, PubMed and Google Scholar, we incorporated 480 partner correlations from 199 peer-reviewed studies of co-parents, engaged pairs, married pairs and/or cohabitating pairs that were published on or before 16 August 2022. We also calculated 133 trait correlations using up to 79,074 male-female couples in the UK Biobank (UKB). Estimates of the 22 mean meta-analysed correlations ranged from rmeta = 0.08 (adjusted 95% CI = 0.03, 0.13) for extraversion to rmeta = 0.58 (adjusted 95% CI = 0.50, 0.64) for political values, with funnel plots showing little evidence of publication bias across traits. The 133 UKB correlations ranged from rUKB = -0.18 (adjusted 95% CI = -0.20, -0.16) for chronotype (being a 'morning' or 'evening' person) to rUKB = 0.87 (adjusted 95% CI = 0.86, 0.87) for birth year. Across analyses, political and religious attitudes, educational attainment and some substance use traits showed the highest correlations, while psychological (that is, psychiatric/personality) and anthropometric traits generally yielded lower but positive correlations. We observed high levels of between-sample heterogeneity for most meta-analysed traits, probably because of both systematic differences between samples and true differences in partner correlations across populations.

Healthcare Costs of Clostridioides difficile Infection in Commercially Insured Younger Adults.

In a US adult population aged <65 years, attributable costs due to Clostridioides difficile infection (CDI) were highest in persons with hospital onset and lowest in those with community-associated CDI treated outside a hospital. The economic burden of CDI in younger adults underscores the need for additional CDI-preventive strategies.

Genetic risk shared across 24 chronic pain conditions: identification and characterization with genomic structural equation modeling.

ABSTRACT: Chronic pain conditions frequently co-occur, suggesting common risks and paths to prevention and treatment. Previous studies have reported genetic correlations among specific groups of pain conditions and reported genetic risk for within-individual multisite pain counts (≤7). Here, we identified genetic risk for multiple distinct pain disorders across individuals using 24 chronic pain conditions and genomic structural equation modeling (Genomic SEM). First, we ran individual genome-wide association studies (GWASs) on all 24 conditions in the UK Biobank ( N ≤ 436,000) and estimated their pairwise genetic correlations. Then we used these correlations to model their genetic factor structure in Genomic SEM, using both hypothesis- and data-driven exploratory approaches. A complementary network analysis enabled us to visualize these genetic relationships in an unstructured manner. Genomic SEM analysis revealed a general factor explaining most of the shared genetic variance across all pain conditions and a second, more specific factor explaining genetic covariance across musculoskeletal pain conditions. Network analysis revealed a large cluster of conditions and identified arthropathic, back, and neck pain as potential hubs for cross-condition chronic pain. Additionally, we ran GWASs on both factors extracted in Genomic SEM and annotated them functionally. Annotation identified pathways associated with organogenesis, metabolism, transcription, and DNA repair, with overrepresentation of strongly associated genes exclusively in brain tissues. Cross-reference with previous GWASs showed genetic overlap with cognition, mood, and brain structure. These results identify common genetic risks and suggest neurobiological and psychosocial mechanisms that should be targeted to prevent and treat cross-condition chronic pain.

Declining autozygosity over time: An exploration in over 1 million individuals from three diverse cohorts.

Previous studies have hypothesized that autozygosity is decreasing over generational time. However, these studies were limited to relatively small samples (n < 11,000) lacking in diversity, which may limit the generalizability of their findings. We present data that partially support this hypothesis from three large cohorts of diverse ancestries, two from the US (All of Us, n = 82,474; the Million Veteran Program, n = 622,497) and one from the UK (UK Biobank, n = 380,899). Our results from a mixed-effect meta-analysis demonstrate an overall trend of decreasing autozygosity over generational time (meta-analyzed slope = -0.029, SE = 0.009, p = 6.03e-4). On the basis of our estimates, we would predict FROH to decline 0.29% for every 20-year increase in birth year. We determined that a model including an ancestry-by-country interaction term fit the data best, indicating that ancestry differences in this trend differ by country. We found further evidence to suggest a difference between the US and UK cohorts by meta-analyzing within country, observing a significant negative estimate in the US cohorts (meta-analyzed slope = -0.058, SE = 0.015, p = 1.50e-4) but a non-significant estimate in the UK (meta-analyzed slope = -0.001, SE = 0.008, p = 0.945). The association between autozygosity and birth year was substantially attenuated when accounting for educational attainment and income (meta-analyzed slope = -0.011, SE = 0.008, p = 0.167), suggesting they may partially account for decreasing autozygosity over time. Overall, we demonstrate decreasing autozygosity over time in a large, modern sample and speculate that this trend can be attributed to increases in urbanization and panmixia and differences in sociodemographic processes lead to country-specific differences in the rate of decline.

Manipulating Fermentation Pathways in the Hyperthermophilic Archaeon Pyrococcus furiosus for Ethanol Production up to 95°C Driven by Carbon Monoxide Oxidation.

Genetic engineering of hyperthermophilic organisms for the production of fuels and other useful chemicals is an emerging biotechnological opportunity. In particular, for volatile organic compounds such as ethanol, fermentation at high temperatures could allow for straightforward separation by direct distillation. Currently, the upper growth temperature limit for native ethanol producers is 72°C in the bacterium Thermoanaerobacter ethanolicus JW200, and the highest temperature for heterologously-engineered bioethanol production was recently demonstrated at 85°C in the archaeon Pyrococcus furiosus. Here, we describe an engineered strain of P. furiosus that synthesizes ethanol at 95°C, utilizing a homologously-expressed native alcohol dehydrogenase, termed AdhF. Ethanol biosynthesis was compared at 75°C and 95°C with various engineered strains. At lower temperatures, the acetaldehyde substrate for AdhF is most likely produced from acetate by aldehyde ferredoxin oxidoreductase (AOR). At higher temperatures, the effect of AOR on ethanol production is negligible, suggesting that acetaldehyde is produced by pyruvate ferredoxin oxidoreductase (POR) via oxidative decarboxylation of pyruvate, a reaction known to occur only at higher temperatures. Heterologous expression of a carbon monoxide dehydrogenase complex in the AdhF overexpression strain enabled it to use CO as a source of energy, leading to increased ethanol production. A genome reconstruction model for P. furiosus was developed to guide metabolic engineering strategies and understand outcomes. This work opens the door to the potential for 'bioreactive distillation' since fermentation can be performed well above the normal boiling point of ethanol. IMPORTANCE Previously, the highest temperature for biological ethanol production was 85°C. Here, we have engineered ethanol production at 95°C by the hyperthermophilic archaeon Pyrococcus furiosus. Using mutant strains, we showed that ethanol production occurs by different pathways at 75°C and 95°C. In addition, by heterologous expression of a carbon monoxide dehydrogenase complex, ethanol production by this organism was driven by the oxidation of carbon monoxide. A genome reconstruction model for P. furiosus was developed to guide metabolic engineering strategies and understand outcomes.