Predicted leukocyte telomere length and risk of myeloid neoplasms.

Maintenance of telomere length has long been established to play a role in the biology of cancer and several studies suggest that it may be especially important in myeloid malignancies. To overcome potential bias in confounding and reverse causation of observational studies, we use both a polygenic risk score (PRS) and inverse-variance weighted (IVW) Mendelian randomization (MR) analyses to estimate the relationship between genetically predicted leukocyte telomere length (LTL) and acute myeloid leukemia (AML) risk in 498 cases and 2099 controls and myelodysplastic syndrome (MDS) risk in 610 cases and 1759 controls. Genetic instruments derived from four recent studies explaining 1.23-4.57% of telomere variability were considered. We used multivariable logistic regression to estimate odds ratios (OR, 95% confidence intervals [CI]) as the measure of association between individual single-nucleotide polymorphisms and myeloid malignancies. We observed a significant association between a PRS of longer predicted LTL and AML using three genetic instruments (OR = 4.03 per ~1200 base pair [bp] increase in LTL, 95% CI: 1.65, 9.85 using Codd et al. [Codd, V., Nelson, C.P., Albrecht, E., Mangino, M., Deelen, J., Buxton, J.L., Hottenga, J.J., Fischer, K., Esko, T., Surakka, I. et al. (2013) Identification of seven loci affecting mean telomere length and their association with disease. Nat. Genet., 45, 422-427 427e421-422.], OR = 3.48 per one-standard deviation increase in LTL, 95% CI: 1.74, 6.97 using Li et al. [Li, C., Stoma, S., Lotta, L.A., Warner, S., Albrecht, E., Allione, A., Arp, P.P., Broer, L., Buxton, J.L., Alves, A.D.S.C. et al. (2020) Genome-wide association analysis in humans links nucleotide metabolism to leukocyte telomere length. Am. J. Hum. Genet., 106, 389-404.] and OR = 2.59 per 1000 bp increase in LTL, 95% CI: 1.03, 6.52 using Taub et al. [Taub, M.A., Conomos, M.P., Keener, R., Iyer, K.R., Weinstock, J.S., Yanek, L.R., Lane, J., Miller-Fleming, T.W., Brody, J.A., Raffield, L.M. et al. (2022) Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed. Cell Genom., 2.] genetic instruments). MR analyses further indicated an association between LTL and AML risk (PIVW ≤ 0.049) but not MDS (all PIVW ≥ 0.076). Findings suggest variation in genes relevant to telomere function and maintenance may be important in the etiology of AML but not MDS.

Predicted leukocyte telomere length and risk of germ cell tumours.

BACKGROUND: Genetically predicted leukocyte telomere length (LTL) has been evaluated in several studies of childhood and adult cancer. We test whether genetically predicted longer LTL is associated with germ cell tumours (GCT) in children and adults. METHODS: Paediatric GCT samples were obtained from a Children's Oncology Group study and state biobank programs in California and Michigan (N = 1413 cases, 1220 biological parents and 1022 unrelated controls). Replication analysis included 396 adult testicular GCTs (TGCT) and 1589 matched controls from the UK Biobank. Mendelian randomisation was used to look at the association between genetically predicted LTL and GCTs and TERT variants were evaluated within GCT subgroups. RESULTS: We identified significant associations between TERT variants reported in previous adult TGCT GWAS in paediatric GCT: TERT/rs2736100-C (OR = 0.82; P = 0.0003), TERT/rs2853677-G (OR = 0.80; P = 0.001), and TERT/rs7705526-A (OR = 0.81; P = 0.003). We also extended these findings to females and tumours outside the testes. In contrast, we did not observe strong evidence for an association between genetically predicted LTL by other variants and GCT risk in children or adults. CONCLUSION: While TERT is a known susceptibility locus for GCT, our results suggest that LTL predicted by other variants is not strongly associated with risk in either children or adults.

Rare and common variants associated with alcohol consumption identify a conserved molecular network.

BACKGROUND: Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology. METHODS: To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure. RESULTS: Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions. CONCLUSIONS: Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.

Rare and Common Variants Associated with Alcohol Consumption Identify a Conserved Molecular Network.

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, rare variants have only begun to be studied for their role in alcohol consumption. No studies have examined whether common and rare variants implicate the same genes and molecular networks. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N=666,978) and whole exome sequencing data (Genebass, N=393,099) to identify a set of common and rare variants for alcohol consumption. Gene-based analysis of each dataset have implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified only by rare variant analysis, but have been associated with related psychiatric traits. We then used a network colocalization procedure to propagate the common and rare gene sets onto a shared molecular network, revealing significant overlap. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. 74 of the genes in the network were previously implicated in comorbid psychiatric or substance use disorders, but had not previously been identified for alcohol-related behaviors, including EXOC2, EPM2A, CACNB3, and CACNG4. Differential gene expression analysis showed enrichment in the liver and several brain regions supporting the role of network genes in alcohol consumption. Thus, genes implicated by common and rare variants identify shared functions relevant to alcohol consumption, which also underlie psychiatric traits and substance use disorders that are comorbid with alcohol use.

Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals.

Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.

Genome-wide association studies of coffee intake in UK/US participants of European ancestry uncover cohort-specific genetic associations.

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N = 130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across hundreds of biomarkers, health, and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from the UK Biobank (UKB; N = 334,659). We observed consistent positive genetic correlations with substance use and obesity in both cohorts. Other genetic correlations were discrepant, including positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in the UKB, and genetic correlations with cognition that were negative in 23andMe but positive in the UKB. Phenome-wide association study using polygenic scores of coffee intake derived from 23andMe or UKB summary statistics also revealed consistent associations with increased odds of obesity- and red blood cell-related traits, but all other associations were cohort-specific. Our study shows that the genetics of coffee intake associate with substance use and obesity across cohorts, but also that GWAS performed in different populations could capture cultural differences in the relationship between behavior and genetics.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

Aligning Semantic Interoperability Frameworks with the FOXS Stack for FAIR Health Data.

BACKGROUND: FAIR Guiding Principles present a synergy with the use cases for digital health records, in that clinical data need to be found, accessible within a range of environments, and data must interoperate between systems and subsequently reused. The use of HL7 FHIR, openEHR, IHE XDS, and SNOMED CT (FOXS) together represents a specification to create an open digital health platform for modern health care applications. OBJECTIVES: To describe where logical FOXS components align to the European Open Science Cloud Interoperability Framework (EOSC-IF) reference architecture for semantic interoperability. This should provide a means of defining if FOXS aligns to FAIR principles and to establish the data models and structures that support longitudinal care records as being fit to underpin scientific research. METHODS: The EOSC-IF Semantic View is a representation of semantic interoperability where meaning is preserved between systems and users. This was analyzed and cross-referenced with FOXS architectural components, mapping concepts, and objects that describe content such as catalogues and semantic artifacts. RESULTS: Majority of conceptual Semantic View components were featured within the FOXS architecture. Semantic Business Objects are composed of a range of elements such as openEHR archetypes and templates, FHIR resources and profiles, SNOMED CT concepts, and XDS document identifiers. Semantic Functional Content comprises catalogues of metadata that were also supported by openEHR and FHIR tools. CONCLUSIONS: Despite some elements of EOSC-IF being vague (e.g., FAIR Digital Object), there was a broad conformance to the framework concepts and the components of a FOXS platform. This work supports a health-domain-specific view of semantic interoperability and how this may be achieved to support FAIR data for health research via a standardized framework.

Genome-Wide Association Studies of Coffee Intake in UK/US Participants of European Ancestry Uncover Gene-Cohort Influences.

Coffee is one of the most widely consumed beverages. We performed a genome-wide association study (GWAS) of coffee intake in US-based 23andMe participants (N=130,153) and identified 7 significant loci, with many replicating in three multi-ancestral cohorts. We examined genetic correlations and performed a phenome-wide association study across thousands of biomarkers and health and lifestyle traits, then compared our results to the largest available GWAS of coffee intake from UK Biobank (UKB; N=334,659). The results of these two GWAS were highly discrepant. We observed positive genetic correlations between coffee intake and psychiatric illnesses, pain, and gastrointestinal traits in 23andMe that were absent or negative in UKB. Genetic correlations with cognition were negative in 23andMe but positive in UKB. The only consistent observations were positive genetic correlations with substance use and obesity. Our study shows that GWAS in different cohorts could capture cultural differences in the relationship between behavior and genetics.

Multi-ancestry meta-analysis of tobacco use disorder prioritizes novel candidate risk genes and reveals associations with numerous health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviors, and although strides have been made using genome-wide association studies (GWAS) to identify risk variants, the majority of variants identified have been for nicotine consumption, rather than TUD. We leveraged five biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records, EHR) in 898,680 individuals (739,895 European, 114,420 African American, 44,365 Latin American). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviors in children, and hundreds of medical outcomes, including HIV infection, heart disease, and pain. This work furthers our biological understanding of TUD and establishes EHR as a source of phenotypic information for studying the genetics of TUD.

Utilising the FOXS Stack for FAIR Architected Data Access.

A FOXS stack assembles HL7 FHIR, openEHR, IHE XDS and SNOMED CT as an operational clinical data platform to build digital systems. This paper analyses its applicability for FAIR-enabled medical research based on a summary of key principles. It highlights the benefit of the blended approach to operational technology stacks for health systems, and a need for industry standard technologies to enable greater semantic coherence for primary/secondary data use.

openEHR Based Contextual Problem List.

The problem list is a key facet of the digital patient record that has historically been difficult to curate. This paper presents an implementation of a contextual problem list using openEHR. It describes the modelling approach, key model elements, and how these are assembled to underpin a Problem Oriented Medical Record. Finally, it discusses issues associated with how problem lists may be used.

Defining the Contextual Problem List.

The Problem Oriented Medical Record (POMR) is considered a key charting method to support clinical care. Although not uniformly represented amongst digital health systems, this paper presents a clinical model to represent multiple clinical perspectives from a single problem list. The contextual problem list model is defined according to primary diagnosis, comorbidities and problems arising from the primary condition. It is represented within the patient record as a single composition according to the prescribed context. The model pattern could help alleviate the traditional criticisms of paper and digitally based problem records.

Electronic patient record evaluation in community mental health.

BACKGROUND: Deployment of electronic patient records (EPRs) is one of the primary goals of national NHS information technology (IT) initiatives. However, many systems come into disrepute through poor planning or design flaws, and media scrutiny focuses on these problems rather than the potential gains. OBJECTIVE: To evaluate the deployment of an EPR in a community mental health setting. METHOD: A validated user questionnaire was issued to all clinically qualified staff working in community mental health teams followed by interview and validation phases. The study encompassed both quantitative and qualitative mechanisms to establish the efficacy and usability of the system. RESULTS: The questionnaire had a response rate of 49.3%. Overall, the response was positive, with almost no extreme negative responses. Of respondents, 88.5% were satisfied with system accuracy, while 91.7% of responses indicated that data was made available in a timely manner. Of those surveyed, 88.7% agreed the system was 'worth the time and effort required to use it'. Additionally, electronic notes are used more frequently than paper-based equivalents. CONCLUSION: The research concludes that the implemented system appears to offer a robust EPR that gives its users a high degree of satisfaction and provides tangible benefits to clinical staff.

Discovery of the 3-Imino-1,2,4-thiadiazinane 1,1-Dioxide Derivative Verubecestat (MK-8931)-A ß-Site Amyloid Precursor Protein Cleaving Enzyme 1 Inhibitor for the Treatment of Alzheimer's Disease.

Verubecestat 3 (MK-8931), a diaryl amide-substituted 3-imino-1,2,4-thiadiazinane 1,1-dioxide derivative, is a high-affinity ß-site amyloid precursor protein cleaving enzyme 1 (BACE1) inhibitor currently undergoing Phase 3 clinical evaluation for the treatment of mild to moderate and prodromal Alzheimer's disease. Although not selective over the closely related aspartyl protease BACE2, verubecestat has high selectivity for BACE1 over other key aspartyl proteases, notably cathepsin D, and profoundly lowers CSF and brain Aß levels in rats and nonhuman primates and CSF Aß levels in humans. In this annotation, we describe the discovery of 3, including design, validation, and selected SAR around the novel iminothiadiazinane dioxide core as well as aspects of its preclinical and Phase 1 clinical characterization.

Dietary exposure to genistein increases vasopressin but does not alter beta-endorphin in the rat hypothalamus.

Genistein is a plant-derived estrogenic isoflavone commonly found in soy-based products such as soymilk and soy-based dietary supplements for treating menopausal symptoms, for example. Vasopressin is a neurosecretory nonapeptide synthesized primarily in neurons of the hypothalamus and secreted into the bloodstream from the posterior lobe of the pituitary. The endogenous opiate peptide beta-endorphin is synthesized both in neurons of the hypothalamus and in pituitary cells, primarily of the neurointermediate lobe. It has been reported that exposure to 17beta-estradiol or diethylstilbesterol increased the vasopressin content of the hypothalamus, and that estradiol valerate selectively damages hypothalamic beta-endorphin-containing neurons. Since little was known of the potential effects of estrogenic endocrine-disruptor compounds on hypothalamic neuropeptides, we fed Sprague-Dawley fetuses from day 7 in utero until sacrifice at postnatal day 77, with either a control diet (<1 ppm) or an experimental diet containing 25, 250, or 1250 ppm of genistein. We then conducted ELISA assays for hypothalamic content of both beta-endorphin and vasopressin immunoreactivity. Whereas there were no statistically reliable effects of dietary genistein on hypothalamic beta-endorphin content, vasopressin levels were significantly elevated in the 1250-ppm genistein group (p < 0.05). Elevated vasopressin levels may be associated with fluid balance, altered blood pressure, and cardiovascular effects. These data are consistent with the known actions of estradiol and may serve to explain our finding in a previous study that estrogenic endocrine-disruptors such as genistein increased sodium preference in rats exposed through their diet.

Quantitative three-dimensional reconstruction: feasibility for studies of sexually dimorphic hypothalamic development in rats.

The adult rat brain develops through an interplay of neuronal proliferation with programmed cell death. Sensory stimulation, as well as growth factors and steroids, may alter the balance between these competing processes. "Endocrine disrupters" (EDs) may do the same by mimicry or modulation of endogenous hormones. The sexually dimorphic nucleus (SDN) of the medial preoptic hypothalamus contains a high concentration of estrogen receptors (ERs). The SDN develops to a final adult volume, which may be used as an indication of the hormonal conditions during perinatal development. Although male rats have been repeatedly observed to have a greater adult SDN volume than female rats, variability between the actual measurements reported (both within and between laboratories) have been rather large. Exposure of female rats to testosterone (or excessive estradiol, beyond the binding capacity of alpha-fetoprotein) has been shown to masculinize them through a P450 aromatase that converts testosterone to estrogen in the SDN. Exposure of males to estradiol may feminize them at low doses through interference with the synthesis of their endogenous testosterone, which normally acts on SDN ERs following aromatization. We have employed computer-assisted reconstruction methods in order to render the SDN within the surrounding hypothalamus in 3-D for computation of its volume. Ongoing studies are investigating whether exposure through the diet to estrogenic endocrine disruptors such as genistein, nonylphenol, and ethinyl estradiol might produce effects similar to those of estradiol itself on the adult SDN.

Peat bog wildfire smoke exposure in rural North Carolina is associated with cardiopulmonary emergency department visits assessed through syndromic surveillance.

BACKGROUND: In June 2008, burning peat deposits produced haze and air pollution far in excess of National Ambient Air Quality Standards, encroaching on rural communities of eastern North Carolina. Although the association of mortality and morbidity with exposure to urban air pollution is well established, the health effects associated with exposure to wildfire emissions are less well understood. OBJECTIVE: We investigated the effects of exposure on cardiorespiratory outcomes in the population affected by the fire. METHODS: We performed a population-based study using emergency department (ED) visits reported through the syndromic surveillance program NC DETECT (North Carolina Disease Event Tracking and Epidemiologic Collection Tool). We used aerosol optical depth measured by a satellite to determine a high-exposure window and distinguish counties most impacted by the dense smoke plume from surrounding referent counties. Poisson log-linear regression with a 5-day distributed lag was used to estimate changes in the cumulative relative risk (RR). RESULTS: In the exposed counties, significant increases in cumulative RR for asthma [1.65 (95% confidence interval, 1.25-2.1)], chronic obstructive pulmonary disease [1.73 (1.06-2.83)], and pneumonia and acute bronchitis [1.59 (1.07-2.34)] were observed. ED visits associated with cardiopulmonary symptoms [1.23 (1.06-1.43)] and heart failure [1.37 (1.01-1.85)] were also significantly increased. CONCLUSIONS: Satellite data and syndromic surveillance were combined to assess the health impacts of wildfire smoke in rural counties with sparse air-quality monitoring. This is the first study to demonstrate both respiratory and cardiac effects after brief exposure to peat wildfire smoke.

Comparison of methods for analysis of functional observation battery (FOB) data.

INTRODUCTION: Different methods for the analysis of behavioral observation data were compared to evaluate how the interpretation of a data set may depend on the analysis method employed. METHODS: Three methods of analysis were used to evaluate the same four sets of rodent behavioral FOB data: (1) evaluation by a trained behavioral toxicologist (ToxRev); (2) Kruskal-Wallis statistical analysis of variance for nonparametric data followed by Wilcoxon pairwise tests (KW) and (3) Cochran-Mantel-Haenszel statistical analysis of variance for nonparametric data followed by Wilcoxon pairwise tests (CMH). The FOB consisted of 9 behavioral, 10 neurologic and 7 autonomic parameters that were evaluated following administration of either vehicle or diazepam (1 or 4 mg/kg; 1, 2 or 5 mg/kg) to male and female rats. The chosen data sets were labeled A, B, C and D. The outcomes of the three analysis methods were compared to identify similarities and differences. RESULTS: ToxRev, KW and CMH analyses were in agreement in determining the no-effect level (NEL) for each data set. All methods were also in agreement calling the fewest FOB parameters in data set C, and correctly identifying the most effects in the behavior functional domain in each data set. The 3 methods were also in agreement in correctly not calling parameters such as convulsion. No single analysis method stood out as remarkably more permissive in identifying effects of diazepam on FOB parameters, although CMH appeared to be the most conservative method, identifying the fewest effects across all data sets. DISCUSSION: Factors contributing to these patterns of outcome are discussed, including variability within and between dose groups. ToxRev, KW and CMH are all viable methods for evaluating FOB-type data, however minor differences in a study's outcome using these analyses may be dependent upon the method selected.

Mathematical modeling to define optimum operating room staffing for pediatric patients in trauma centers.

BACKGROUND: Adult trauma centers (TCs) in the United States may be verified with an on-call operating room team if the performance improvement program shows no adverse outcome. Using queuing and simulation methodology, this study attempts to add a volume guideline for injured children. METHODS: Data from 63 verified TCs identified demographic factors including specific information regarding the first pediatric trauma-related operation done between 11 pm and 7 am each month for 1 year. RESULTS: The annual pediatric admits correlated with the number of operations (383) done from 11 pm to 7 am (P < .001). The probability of operation within 30 minutes of arrival varies with the number of admits and the percent of penetrating vs blunt injuries. This likely number of operations from 11 pm to 7 am beginning within 30 minutes of patient arrival would be 3.45, 4.21, and 4.95 for TCs admitting 150, 250, and 350 injured children per year, respectively. The probability that 2 rooms would be occupied simultaneously is 0.074 and 0.109 for centers with 160 and 260 pediatric trauma admissions, respectively. CONCLUSION: Trauma centers performing less than 6 pediatric trauma operations per year from 11 pm to 7 am could conserve resources by using an on-call operating room team.