Case-control Sample Research Articles

Plasma Metabolomic Profiling of Patients Recovered From Coronavirus Disease 2019 (COVID-19) With Pulmonary Sequelae 3 Months After Discharge.

BackgroundElucidation of the molecular mechanisms involved in the pathogenesis of coronavirus disease 2019 (COVID-19) may help to discover therapeutic targets.MethodsTo determine the metabolomic profile of circulating plasma from COVID-19 survivors with pulmonary sequelae 3 months after discharge, a random, outcome-stratified case-control sample was analyzed. We enrolled 103 recovered COVID-19 patients as well as 27 healthy donors, and performed pulmonary function tests, computerized tomography (CT) scans, laboratory examinations, and liquid chromatography-mass spectrometry.ResultsPlasma metabolite profiles of COVID-19 survivors with abnormal pulmonary function were different from those of healthy donors or subjects with normal pulmonary function. These alterations were associated with disease severity and mainly involved amino acid and glycerophospholipid metabolic pathways. Furthermore, increased levels of triacylglycerols, phosphatidylcholines, prostaglandin E2, arginine, and decreased levels of betain and adenosine were associated with pulmonary CO diffusing capacity and total lung capacity. The global plasma metabolomic profile differed between subjects with abnormal and normal pulmonary function.ConclusionsFurther metabolite-based analysis may help to identify the mechanisms underlying pulmonary dysfunction in COVID-19 survivors, and provide potential therapeutic targets in the future.

Comparative validation of the BOADICEA and Tyrer-Cuzick breast cancer risk models incorporating classical risk factors and polygenic risk in a population-based prospective cohort of women of European ancestry

BackgroundThe Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) and the Tyrer-Cuzick breast cancer risk prediction models are commonly used in clinical practice and have recently been extended to include polygenic risk scores (PRS). In addition, BOADICEA has also been extended to include reproductive and lifestyle factors, which were already part of Tyrer-Cuzick model. We conducted a comparative prospective validation of these models after incorporating the recently developed 313-variant PRS.MethodsCalibration and discrimination of 5-year absolute risk was assessed in a nested case-control sample of 1337 women of European ancestry (619 incident breast cancer cases) aged 23–75 years from the Generations Study.ResultsThe extended BOADICEA model with reproductive/lifestyle factors and PRS was well calibrated across risk deciles; expected-to-observed ratio (E/O) at the highest risk decile :0.97 (95 % CI 0.51 − 1.86) for women younger than 50 years and 1.09 (0.66 − 1.80) for women 50 years or older. Adding reproductive/lifestyle factors and PRS to the BOADICEA model improved discrimination modestly in younger women (area under the curve (AUC) 69.7 % vs. 69.1%) and substantially in older women (AUC 64.6 % vs. 56.8%). The Tyrer-Cuzick model with PRS showed evidence of overestimation at the highest risk decile: E/O = 1.54(0.81 − 2.92) for younger and 1.73 (1.03 − 2.90) for older women.ConclusionThe extended BOADICEA model identified women in a European-ancestry population at elevated breast cancer risk more accurately than the Tyrer-Cuzick model with PRS. With the increasing availability of PRS, these analyses can inform choice of risk models incorporating PRS for risk stratified breast cancer prevention among women of European ancestry.

COVID-19 Inmate Risk Appraisal (CIRA): development and validation of a screening tool to assess COVID-19 vulnerability in prisons.

To develop and validate a screening tool designed to identify detained people at increased risk for COVID-19 mortality, the COVID-19 Inmate Risk Appraisal (CIRA). Cross-sectional study with a representative sample (development) and a case-control sample (validation). The two largest Swiss prisons. (1) Development sample: all male persons detained in Pöschwies, Zurich (n = 365); (2) Validation sample: case-control sample of male persons detained in Champ-Dollon, Geneva (n = 192, matching 1:3 for participants at risk for severe course of COVID-19 and participants without risk factors). The CIRA combined seven risk factors identified by the World Health Organization and the Swiss Federal Office of Public Health as predictive of severe COVID-19 to derive an absolute risk increase in mortality rate: Age ≥60 years, cardiovascular disease, diabetes, hypertension, chronic respiratory disease, immunodeficiency and cancer. Based on the development sample, we proposed a three-level classification: average (<3.7), elevated (3.7-5.7) and high (>5.7) risk. In the validation sample, the CIRA identified all individuals identified as vulnerable by national recommendations (having at least one risk factor). The category “elevated risk” maximised sensitivity (1) and specificity (0.97). The CIRA had even higher capacity in discriminating individuals vulnerable according to clinical evaluation (a four-level risk categorisation based on a consensus of medical staff). The category “elevated risk” maximised sensitivity and specificity (both 1). When considering the individuals classified as extremely high risk by medical staff, the category “high risk” had a high discriminatory capacity (sensitivity =0.89, specificity =0.97). The CIRA scores have a high discriminative ability and will be important in custodial settings to support decisions and prioritise actions using a standardised valid assessment method. However, as knowledge on risk factors for COVID-19 mortality is still limited, the CIRA may be considered preliminary. Underlying data will be updated regularly on the website (http://www.prison-research.com), where the CIRA algorithm is freely available.

COVID-19 Inmate Risk Appraisal (CIRA): development and validation of a screening tool to assess COVID-19 vulnerability in prisons.

To develop and validate a screening tool designed to identify detained people at increased risk for COVID-19 mortality, the COVID-19 Inmate Risk Appraisal (CIRA). Cross-sectional study with a representative sample (development) and a case-control sample (validation). The two largest Swiss prisons. (1) Development sample: all male persons detained in Pöschwies, Zurich (n = 365); (2) Validation sample: case-control sample of male persons detained in Champ-Dollon, Geneva (n = 192, matching 1:3 for participants at risk for severe course of COVID-19 and participants without risk factors). The CIRA combined seven risk factors identified by the World Health Organization and the Swiss Federal Office of Public Health as predictive of severe COVID-19 to derive an absolute risk increase in mortality rate: Age ≥60 years, cardiovascular disease, diabetes, hypertension, chronic respiratory disease, immunodeficiency and cancer. Based on the development sample, we proposed a three-level classification: average (<3.7), elevated (3.7-5.7) and high (>5.7) risk. In the validation sample, the CIRA identified all individuals identified as vulnerable by national recommendations (having at least one risk factor). The category “elevated risk” maximised sensitivity (1) and specificity (0.97). The CIRA had even higher capacity in discriminating individuals vulnerable according to clinical evaluation (a four-level risk categorisation based on a consensus of medical staff). The category “elevated risk” maximised sensitivity and specificity (both 1). When considering the individuals classified as extremely high risk by medical staff, the category “high risk” had a high discriminatory capacity (sensitivity =0.89, specificity =0.97). The CIRA scores have a high discriminative ability and will be important in custodial settings to support decisions and prioritise actions using a standardised valid assessment method. However, as knowledge on risk factors for COVID-19 mortality is still limited, the CIRA may be considered preliminary. Underlying data will be updated regularly on the website (http://www.prison-research.com), where the CIRA algorithm is freely available.

Early signature in the blood lipidome associated with subsequent cognitive decline in the elderly: A case-control analysis nested within the Three-City cohort study.

BackgroundBrain lipid metabolism appears critical for cognitive aging, but whether alterations in the lipidome relate to cognitive decline remains unclear at the system level.MethodsWe studied participants from the Three-City study, a multicentric cohort of older persons, free of dementia at time of blood sampling, and who provided repeated measures of cognition over 12 subsequent years. We measured 189 serum lipids from 13 lipid classes using shotgun lipidomics in a case-control sample on cognitive decline (matched on age, sex and level of education) nested within the Bordeaux study center (discovery, n = 418). Associations with cognitive decline were investigated using bootstrapped penalized regression, and tested for validation in the Dijon study center (validation, n = 314).FindingsAmong 17 lipids identified in the discovery stage, lower levels of the triglyceride TAG50:5, and of four membrane lipids (sphingomyelin SM40:2,2, phosphatidylethanolamine PE38:5(18:1/20:4), ether-phosphatidylethanolamine PEO34:3(16:1/18:2), and ether-phosphatidylcholine PCO34:1(16:1/18:0)), and higher levels of PCO32:0(16:0/16:0), were associated with greater odds of cognitive decline, and replicated in our validation sample.InterpretationThese findings indicate that in the blood lipidome of non-demented older persons, a specific profile of lipids involved in membrane fluidity, myelination, and lipid rafts, is associated with subsequent cognitive decline.FundingThe complete list of funders is available at the end of the manuscript, in the Acknowledgement section.

Polygenic Scores for ADHD: A Meta-Analysis.

Attention-deficit/hyperactivity disorder (ADHD) is a highly heritable neurodevelopmental disorder that is known to have a polygenic (i.e., many genes of individually small effects) architecture. Polygenic scores (PGS), which characterize this polygenicity as a single score for a given individual, are considered the state-of-the-art in psychiatric genetics research. Despite the proliferation of ADHD studies adopting this approach and its clinical implications, remarkably little is known about the predictive utility of PGS in ADHD research to date, given that there have not yet been any systematic or meta-analytic reviews of this rapidly developing literature. We meta-analyzed 12 unique effect sizes from ADHD PGS studies, yielding an N = 40,088. These studies, which included a mixture of large population-based cohorts and case-control samples of predominantly European ancestry, yielded a pooled ADHD PGS effect size of rrandom = 0.201 (95% CI = [0.144, 0.288]) and an rfixed = 0.190 (95% CI = [0.180, 0.199]) in predicting ADHD. In other words, ADHD PGS reliably account for between 3.6% (in the fixed effects model) to 4.0% (in the random effects model) of the variance in broadly defined phenotypic ADHD. Findings provide important insights into the genetics of psychiatric outcomes and raise several key questions about the impact of PGS on psychiatric research moving forward. Our review concludes by providing recommendations for future research directions in the use of PGS, including new methods to account for comorbidities, integrating bioinformatics to elucidate biological pathways, and leveraging PGS to test mechanistic models of ADHD.

CAMAMED: a pipeline for composition-aware mapping-based analysis of metagenomic data.

Metagenomics is the study of genomic DNA recovered from a microbial community. Both assembly-based and mapping-based methods have been used to analyze metagenomic data. When appropriate gene catalogs are available, mapping-based methods are preferred over assembly based approaches, especially for analyzing the data at the functional level. In this study, we introduce CAMAMED as a composition-aware mapping-based metagenomic data analysis pipeline. This pipeline can analyze metagenomic samples at both taxonomic and functional profiling levels. Using this pipeline, metagenome sequences can be mapped to non-redundant gene catalogs and the gene frequency in the samples are obtained. Due to the highly compositional nature of metagenomic data, the cumulative sum-scaling method is used at both taxa and gene levels for compositional data analysis in our pipeline. Additionally, by mapping the genes to the KEGG database, annotations related to each gene can be extracted at different functional levels such as KEGG ortholog groups, enzyme commission numbers and reactions. Furthermore, the pipeline enables the user to identify potential biomarkers in case-control metagenomic samples by investigating functional differences. The source code for this software is available from https://github.com/mhnb/camamed. Also, the ready to use Docker images are available at https://hub.docker.com.

Surprise sampling: Improving and extending the local case-control sampling

Fithian and Hastie (2014) proposed a new sampling scheme called local case-control (LCC) sampling that achieves stability and efficiency by utilizing a clever adjustment pertained to the logistic model. It is particularly useful for classification with large and imbalanced data. This paper proposes a more general sampling scheme based on a working principle that data points deserve higher sampling probability if they contain more information or appear "surprising" in the sense of, for example, a large error of pilot prediction or a large absolute score. Compared with the relevant existing sampling schemes, as reported in Fithian and Hastie (2014) and Ai, et al. (2018), the proposed one has several advantages. It adaptively gives out the optimal forms to a variety of objectives, including the LCC and Ai et al. (2018)'s sampling as special cases. Under same model specifications, the proposed estimator also performs no worse than those in the literature. The estimation procedure is valid even if the model is misspecified and/or the pilot estimator is inconsistent or dependent on full data. We present theoretical justifications of the claimed advantages and optimality of the estimation and the sampling design. Different from Ai, et al. (2018), our large sample theory are population-wise rather than data-wise. Moreover, the proposed approach can be applied to unsupervised learning studies, since it essentially only requires a specific loss function and no response-covariate structure of data is needed. Numerical studies are carried out and the evidence in support of the theory is shown.

Socio-Economic Position as Risk Factor of Childhood Tuberculosis

Childhood tuberculosis cases in the year 2020 increased compared to cases in 2013. Meanwhile, childhood tuberculosis has received less attention in the current tuberculosis epidemic. Researches show that tuberculosis closely related to socio-economic position, but only few researches studied in childhood tuberculosis. This research aims to study socio-economic positions as risk factor of childhood tuberculosis. This research is a case control study carried out in six primary health centres which have the highest cases of childhood tuberculosis in Bandar Lampung, Indonesia. Samples of this research consisted of case sample and control sample. The case samples were all children with tuberculosis in the research study, which were 73 children and the control samples were 73 children who did not suffer from tuberculosis. Data collection was carried out by interview based on questionnaires, which then analysed using chi square. The results show that low socio-economic positions increase the risk of childhood tuberculosis in children. Furthermore, the mechanism included the presence of household contacts as well as low knowledge of tuberculosis transmission and prevention. In conclusion, childhood tuberculosis control program should be elaborated with socio-economic position intervention.

Polymorphisms in mitochondrial ribosomal protein S5 (MRPS5) are associated with leprosy risk in Chinese.

Leprosy is an infectious disease caused by Mycobacterium leprae (M. leprae), with about 210,000 new cases per year worldwide. Although numerous risk loci have been uncovered by genome-wide association studies, the effects of common genetic variants are relatively modest. To identify possible new genetic locus involved in susceptibility to leprosy, whole exome sequencing was performed for 28 subjects including 14 patients and 12 unaffected members from 8 leprosy-affected families as well as another case and an unrelated control, and then the follow-up SNP genotyping of the candidate variants was studied in case-control sample sets. A rare missense variant in mitochondrial ribosomal protein S5 (MRPS5), rs200730619 (c. 95108402T>C [p. Tyr137Cys]) was identified and validated in 369 cases and 270 controls of Chinese descent (Padjusted = 0.006, odds ratio [OR] = 2.74) as a contributing factor to leprosy risk. Moreover, the mRNA level of MRPS5 was downregulated in M. leprae sonicate-stimulated peripheral blood mononuclear cells. Our results indicated that MRPS5 may be involved in leprosy pathogenesis. Further studies are needed to determine if defective MRPS5 could lead to impairment of energy metabolism of host immune cells, which could further cause defect in clearing M. leprae and increase susceptibility to infection.

Weight calibration to improve efficiency for estimating pure risks from the additive hazards model with the nested case-control design.

We study the efficiency of covariate-specific estimates of pure risk (one minus the survival function) when some covariates are only available for case-control samples nested in a cohort. We focus on the semiparametric additive hazards model in which the hazard function equals a baseline hazard plus a linear combination of covariates with either time-varying or time-invariant coefficients. A published approach uses the design-based inclusion probabilities to reweight the nested case-control data. We obtain more efficient estimates of pure risks by calibrating the design weights to data available in the entire cohort, for both time-varying and time-invariant covariate coefficients. We develop explicit variance formulas for the weight-calibrated estimates based on influence functions. Simulations show the improvement in precision by using weight calibration and confirm the consistency of variance estimators and the validity of inference based on asymptotic normality. Examples are provided using data from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial Study (PLCO).

Proton pump inhibitor use is associated with a variety of infections in patients with liver cirrhosis.

There is evidence that intake of proton pump inhibitors (PPI) increases the risk for spontaneous bacterial peritonitis (SBP) in patients with liver cirrhosis. However, data regarding the impact of PPI intake on occurrence of infections other than SBP are still lacking.We hypothesized that PPI use is associated with a higher rate of infections other than SBP in patients with liver cirrhosis.The current case-control study sample included patients with liver cirrhosis from the Disease Analyzer database (IQVIA), which compiles data such as risk factors, drug prescriptions and diagnoses obtained from general practitioners and specialists in Germany. In total, 2,823 patients with infections were matched with 2,823 patients without infections by propensity scores. For quantification of PPI use the prescribed quantity of PPI during the past 12 months before index date was analyzed.Frequency of PPI users was significantly higher in patients with infections than in patients without infections (47.9% vs 37.9%). In regression analysis, PPI use was significantly associated with the occurrence of infections overall (OR 1.55, 95% CI 1.39–1.72, P < .001), and associated with the occurrence of lower respiratory tract infections, urinary tract infections and infectious gastroenteritis. There was no association between PPI use and skin infections. Pantoprazole and omeprazole were the most frequently prescribed PPIs and were both independently associated with the occurrence of infections.PPI use may be associated with infections other than SBP in patients with liver cirrhosis. Prescription of PPI should be limited to patients with a clear indication.

Abstract PO-173: Racial/ethnic differences and underlying behavioral mechanisms in the association between metabolic syndrome and cancer

Abstract Introduction: Recent epidemiological studies have suggested a trend of increasing prevalence of metabolic syndrome (MetS) and certain types of cancer among adults under the age of 50. How is MetS associated with cancer in adults under the age of 50? How does the association vary by racial/ethnic groups? What are the potential lifestyle behavioral mechanisms? This study attempts to gain insights into these questions. Methods: We used data from the 2011–2016 National Health and Nutrition Examination Survey (NHANES) to define a case-control sample to examine the racial/ethnic disparities in the association of MetS and cancer of any type. We used chi-square test and binary logistic regression to examine the MetS and cancer association. All analyses were conducted in Stata 14. Results: From a total sample of 17,969 cases, we identified 15,463 no-cancer cases, and 1,584 cancer cases. We found that MetS was significantly associated with cancer risk in the total sample (odds ratio = 1.50, p = .005). This association was only found in the Asian subsample with marginal significance (odds ratio = 3.68, p = .06). Smoking was a significant mediator to the MetS-cancer association in the total sample; sleep duration was a marginally significant mediator in the African American subsample. Conclusion: To summarize, we found that the association between MetS and cancer vary by race/ethnicity for adults under the age of 50. The etiological and epidemiological mechanisms of such racial/ethnic disparities warrant future research. Our findings of racial/ethnic disparities between MetS and cancer contribute to the growing body of the literature and provide implications for future research and public health interventions. The next steps of our research are to: (1) conduct analysis in larger samples such as the Surveillance, Epidemiology, and End Results (SEER)-Medicare linked database; (2) explore the etiological and epidemiological mechanisms of MetS-cancer association with sufficient power within each racial/ethnic group; and 3) design and implement integrative behavioral interventions among high-risk groups to reduce cardiometabolic and cancer risks. Citation Format: Lin Zhu, Grace X. Ma. Racial/ethnic differences and underlying behavioral mechanisms in the association between metabolic syndrome and cancer [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-173.

Abstract PO-160: Association between variants in acinar-to-ductal metaplasia genes and pancreatic cancer incidence in racially diverse populations

Abstract Background: Pancreatic cancer is one of the deadliest cancers with increasing incidence and mortality. Racial/ethnic disparities in incidence have been observed in the United States with African Americans exhibited the highest incidence. In the Multiethnic Cohort Study (MEC), we found elevated risk among African Americans, Japanese Americans and Native Hawaiians. Acinar-to-ductal metaplasia (ADM) is considered the main origin of pancreatic pre-neoplastic lesions that eventually develop into pancreatic ductal adenocarcinoma (PDAC). In our preliminary in-vitro study, we found differences in the rate of ADM across racial/ethnic groups with Blacks undergoing ADM greater than whites followed by Hispanics. We hypothesize that genetic variants in genes involved in the ADM process are associated with PDAC risk. Methods: We examined the associations of single nucleotide polymorphisms (SNP) in KRT19, PTF1A and SOX9 with risk of PDAC in two prospective cohorts: the MEC and the Southern Community Cohort Study (SCCS). Nested case-control samples with 691 incident PDAC cases and 13,778 controls from African-American, Japanese- American, Latino, Native Hawaiian, and white participants were included in this analysis. SNP and PDAC associations were examined using logistic regression, adjusting for age, sex, study, body mass index, diabetes, and population stratification using principal components. Results: In racial/ethnic groups combined, no association was observed between SNPs in KRT19, PTF1A and SOX9 and PDAC risk. However, in ethnic-stratified analyses, we found significant associations between PTF1A and PDAC in whites; rs1886763 (G/A) OR=1.72 (95% CI: 1.22, 2.42). We also found significant associations between 7 SNPs in KRT19 and PDAC among Japanese Americans. All these 7 SNPs were in high linkage disequilibrium, with the strongest of these associations was observed for rs56051972 (G/C) OR=1.77 (95% CI 1.17, 2.66). Conclusions: In this racially diverse populations, we found associations between key ADM genes and PDAC risk in certain racial/ethnic groups. Our findings suggest potential role of ADM in influencing PDAC risk. Citation Format: David Bogumil, Thomas Schmittgen, Corey Perkins, Eun-Sook Lee, Mariana Stern, John Carpten, Veronica Wendy Setiawan. Association between variants in acinar-to-ductal metaplasia genes and pancreatic cancer incidence in racially diverse populations [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-160.

Skin pigmentation polymorphisms associated with increased risk of melanoma in a case-control sample from southern Brazil

BackgroundMelanoma is the most aggressive type of skin cancer and is associated with environmental and genetic risk factors. It originates in melanocytes, the pigment-producing cells. Single nucleotide polymorphisms (SNPs) in pigmentation genes have been described in melanoma risk modulation, but knowledge in the field is still limited.MethodsIn a case-control approach (107 cases and 119 controls), we investigated the effect of four pigmentation gene SNPs (TYR rs1126809, HERC2 rs1129038, SLC24A5 rs1426654, and SLC45A2 rs16891982) on melanoma risk in individuals from southern Brazil using a multivariate logistic regression model and multifactor dimensionality reduction (MDR) analysis.ResultsTwo SNPs were associated with an increased risk of melanoma in a dominant model: rs1129038AA and rs1426654AA [OR = 2.094 (95% CI: 1.106–3.966), P = 2.3 10− 2 and OR = 7.126 (95% CI: 1.873–27.110), P = 4.0 10− 3, respectively]. SNP rs16891982CC was associated with a lower risk to melanoma development in a log-additive model when the allele C was inherited [OR = 0.081 (95% CI: 0.008–0.782), P = 3 10− 2]. In addition, MDR analysis showed that the combination of the rs1426654AA and rs16891982GG genotypes was associated with a higher risk for melanoma (P = 3 10− 3), with a redundant effect.ConclusionsThese results contribute to the current knowledge and indicate that epistatic interaction of these SNPs, with an additive or correlational effect, may be involved in modulating the risk of melanoma in individuals from a geographic region with a high incidence of the disease.

BIOM-50. GENETIC PREDISPOSITION TO LONGER TELOMERE LENGTH AND RISK OF CHILDHOOD, ADOLESCENT AND ADULT-ONSET EPENDYMOMA

Abstract INTRODUCTION Ependymoma is the third most common brain tumor in children, with well-described molecular characterization but poorly understood underlying germline risk factors. Telomerase reactivation in somatic cells has been linked to ependymoma progression, recurrence, and survival, and has been implicated as an important prognostic marker and potential therapeutic target. METHODS To investigate whether inherited predisposition to longer telomere length influences ependymoma risk, we utilized case-control data from three studies: 1) a population-based pediatric and adolescent ependymoma case-control sample from California (153 cases, 696 controls), 2) a hospital-based pediatric posterior fossa type A ependymoma (EPN-PF-A) case-control study from Toronto’s Hospital for Sick Children and the Children’s Hospital of Philadelphia (83 cases, 332 controls), and 3) a multicenter adult-onset ependymoma case-control dataset nested within the Glioma International Case-Control Consortium (GICC) (103 cases, 3287 controls). We investigated the individual effect of telomere-length associated SNPs on ependymoma risk, as well as the combined effect of these SNPs through polygenic score and Mendelian randomization analyses. RESULTS We observed an association between genetic predisposition to longer LTL and increased risk of adolescent-onset (P= 3.97x10-3) and adult-onset (P =0.042) ependymoma, but not ependymoma diagnosed in children &amp;lt; 12 years old (P=0.21), or among the pediatric EPN-PF-A sample (P=0.59). Comparing ependymoma patients ages 12–19 to those under 12 years of age demonstrated that age significantly modified the association between longer telomere length and ependymoma risk (P=0.021). CONCLUSIONS These findings complement emerging literature suggesting that dysregulated telomere maintenance is important for ependymoma pathogenesis and that longer telomere length is a risk factor for various neoplasms of the peripheral and central nervous system.

Maturation of the gut microbiome during the first year of life contributes to the protective farm effect on childhood asthma.

Growing up on a farm is associated with an asthma-protective effect, but the mechanisms underlying this effect are largely unknown. In the Protection against Allergy: Study in Rural Environments (PASTURE) birth cohort, we modeled maturation using 16S rRNA sequence data of the human gut microbiome in infants from 2 to 12 months of age. The estimated microbiome age (EMA) in 12-month-old infants was associated with previous farm exposure (β = 0.27 (0.12-0.43), P = 0.001, n = 618) and reduced risk of asthma at school age (odds ratio (OR) = 0.72 (0.56-0.93), P = 0.011). EMA mediated the protective farm effect by 19%. In a nested case-control sample (n = 138), we found inverse associations of asthma with the measured level of fecal butyrate (OR = 0.28 (0.09-0.91), P = 0.034), bacterial taxa that predict butyrate production (OR = 0.38 (0.17-0.84), P = 0.017) and the relative abundance of the gene encoding butyryl-coenzyme A (CoA):acetate-CoA-transferase, a major enzyme in butyrate metabolism (OR = 0.43 (0.19-0.97), P = 0.042). The gut microbiome may contribute to asthma protection through metabolites, supporting the concept of a gut-lung axis in humans.

Interactions of Soil and Vegetation Determine Habitat for Southeastern Pocket Gopher (Geomys pinetis)

Pocket gophers (Geomyidae) require soils amenable to burrowing and vegetation communities that provide adequate foods. We examined the interplay of soil texture and vegetation structure in determining site occupancy of the southeastern pocket gopher (Geomys pinetis), a species of conservation concern throughout its range. Using a case-control sampling design, we compared vegetation structure and soil texture between occupied and unoccupied sites in southeastern Alabama. All occupied sites had soil clay content ≤8.05% at 0–20 cm depth. In logistic regression modeling, clay content had overwhelming support as the most important single habitat variable distinguishing occupied from unoccupied sites. Based on soil results, we focused our examination of vegetation structure on the subset of our sites with <10% clay at 0–20 cm depth. Relative odds of occupancy were highest at intermediate levels of canopy cover; however, canopy cover at occupied sites ranged widely. Compared to unoccupied sites, occupied sites contained less midstory cover and greater ground cover of graminoids and shrubs. Our results demonstrate that although vegetation structure is important in determining site suitability, soil texture may be an overriding constraint limiting potential habitat for this species. Conservation actions for southeastern pocket gophers such as habitat restoration and population translocations should ensure that target sites have suitable low-clay soils.

Genetic predisposition to longer telomere length and risk of childhood, adolescent and adult-onset ependymoma

Ependymoma is the third most common brain tumor in children, with well-described molecular characterization but poorly understood underlying germline risk factors. To investigate whether genetic predisposition to longer telomere length influences ependymoma risk, we utilized case–control data from three studies: a population-based pediatric and adolescent ependymoma case–control sample from California (153 cases, 696 controls), a hospital-based pediatric posterior fossa type A (EPN-PF-A) ependymoma case–control study from Toronto’s Hospital for Sick Children and the Children’s Hospital of Philadelphia (83 cases, 332 controls), and a multicenter adult-onset ependymoma case–control dataset nested within the Glioma International Case-Control Consortium (GICC) (103 cases, 3287 controls). In the California case–control sample, a polygenic score for longer telomere length was significantly associated with increased risk of ependymoma diagnosed at ages 12–19 (P = 4.0 × 10−3), but not with ependymoma in children under 12 years of age (P = 0.94). Mendelian randomization supported this observation, identifying a significant association between genetic predisposition to longer telomere length and increased risk of adolescent-onset ependymoma (ORPRS = 1.67; 95% CI 1.18–2.37; P = 3.97 × 10−3) and adult-onset ependymoma (PMR-Egger = 0.042), but not with risk of ependymoma diagnosed before age 12 (OR = 1.12; 95% CI 0.94–1.34; P = 0.21), nor with EPN-PF-A (PMR-Egger = 0.59). These findings complement emerging literature suggesting that augmented telomere maintenance is important in ependymoma pathogenesis and progression, and that longer telomere length is a risk factor for diverse nervous system malignancies.

Interactions of Soil and Vegetation Determine Habitat for Southeastern Pocket Gopher (Geomys pinetis)

Pocket gophers (Geomyidae) require soils amenable to burrowing and vegetation communities that provide adequate foods. We examined the interplay of soil texture and vegetation structure in determining site occupancy of the southeastern pocket gopher (Geomys pinetis), a species of conservation concern throughout its range. Using a case-control sampling design, we compared vegetation structure and soil texture between occupied and unoccupied sites in southeastern Alabama. All occupied sites had soil clay content ≤8.05% at 0–20 cm depth. In logistic regression modeling, clay content had overwhelming support as the most important single habitat variable distinguishing occupied from unoccupied sites. Based on soil results, we focused our examination of vegetation structure on the subset of our sites with <10% clay at 0–20 cm depth. Relative odds of occupancy were highest at intermediate levels of canopy cover; however, canopy cover at occupied sites ranged widely. Compared to unoccupied sites, occupied sites contained less midstory cover and greater ground cover of graminoids and shrubs. Our results demonstrate that although vegetation structure is important in determining site suitability, soil texture may be an overriding constraint limiting potential habitat for this species. Conservation actions for southeastern pocket gophers such as habitat restoration and population translocations should ensure that target sites have suitable low-clay soils.