Search

The 24th annual Bioinformatics Open Source Conference ( BOSC 2023) was part of the 2023i conference on Intelligent Systems for Molecular Biology and the European Conference on Computational Biology (ISMB/ECCB 2023). Launched in 2000 and held yearly since, BOSC is the premier meeting covering open-source bioinformatics and open science. Like ISMB 2022, the 2023 meeting was a hybrid conference, with the in-person component hosted in Lyon, France. ISMB/ECCB attracted a near-record number of attendees, with over 2100 in person and about 900 more online. Approximately 200 people participated in BOSC sessions. In addition to 43 talks and 49 posters, BOSC featured two keynotes: Sara El-Gebali, who spoke about A New Odyssey: Pioneering the Future of Scientific Progress Through Open Collaboration, and Joseph Yracheta, who spoke about The Dissonance between Scientific Altruism & Capitalist Extraction: The Zero Trust and Federated Data Sovereignty Solution. Once again, a joint session brought together BOSC and the Bio-Ontologies COSI. The conference ended with a panel on Open and Ethical Data Sharing. As in prior years, BOSC was preceded by a CollaborationFest, a collaborative work event that brought together about 40 participants interested in synergistically combining ideas, shaping project plans, developing software, and more.

Greenspace may benefit sleep by enhancing physical activity, reducing stress or air pollution exposure. Studies on greenspace and childrens sleep are limited, and most use satellite-derived measures that do not capture ground-level exposures that may be important for sleep. We examined associations of street view imagery (SVI)-based greenspace with sleep in Project Viva, a Massachusetts pre-birth cohort. We used deep learning algorithms to derive novel metrics of greenspace (e.g., %trees, %grass) from SVI within 250m of participant residential addresses during 2007-2010 (mid-childhood, mean age 7.9 years) and 2012-2016 (early adolescence, 13.2y) (N = 533). In early adolescence, participants completed >5 days of wrist actigraphy. Sleep duration, efficiency, and time awake after sleep onset (WASO) were derived from actigraph data. We used linear regression to examine cross-sectional and prospective associations of mid-childhood and early adolescence greenspace exposure with early adolescence sleep, adjusting for confounders. We compared associations with satellite-based greenspace (Normalized Difference Vegetation Index, NDVI). In unadjusted models, mid-childhood SVI-based total greenspace and %trees (per interquartile range) were associated with longer sleep duration at early adolescence (9.4 min/day; 95%CI:3.2,15.7; 8.1; 95%CI:1.7,14.6 respectively). However, in fully adjusted models, only the association between %grass at mid-childhood and WASO was observed (4.1; 95%CI:0.2,7.9). No associations were observed between greenspace and sleep efficiency, nor in cross-sectional early adolescence models. The association between greenspace and sleep differed by racial and socioeconomic subgroups. For example, among Black participants, higher NDVI was associated with better sleep, in neighborhoods with low socio-economic status (SES), higher %grass was associated with worse sleep, and in neighborhoods with high SES, higher total greenspace and %grass were associated with better sleep time. SVI metrics may have the potential to identify specific features of greenspace that affect sleep.

BackgroundSeveral epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM2.5) have been reported. However, EWAS of PM2.5 elements (PEs), reflecting different emission sources, are very limited.ObjectivesWe performed EWAS of short- and intermediate-term exposure to PM2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM2.5 mass and its elements.MethodsWe repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways.ResultsWe included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM2.5 total mass and PEs. For example, PM2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling").ConclusionsPM2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.

BackgroundAir pollution exposure is ubiquitous with demonstrated effects on morbidity and mortality. A growing literature suggests that prenatal air pollution exposure impacts neurodevelopment. We posit that the Environmental influences on Child Health Outcomes (ECHO) program will provide unique opportunities to fill critical knowledge gaps given the wide spatial and temporal variability of ECHO participants.ObjectivesWe briefly describe current methods for air pollution exposure assessment, summarize existing studies of air pollution and neurodevelopment, and synthesize this information as a basis for recommendations, or a blueprint, for evaluating air pollution effects on neurodevelopmental outcomes in ECHO.MethodsWe review peer-reviewed literature on prenatal air pollution exposure and neurodevelopmental outcomes, including autism spectrum disorder, attention deficit hyperactivity disorder, intelligence, general cognition, mood, and imaging measures. ECHO meta-data were compiled and evaluated to assess frequency of neurodevelopmental assessments and prenatal and infancy residential address locations. Cohort recruitment locations and enrollment years were summarized to examine potential spatial and temporal variation present in ECHO.DiscussionWhile the literature provides compelling evidence that prenatal air pollution affects neurodevelopment, limitations in spatial and temporal exposure variation exist for current published studies. As >90% of the ECHO cohorts have collected a prenatal or infancy address, application of advanced geographic information systems-based models for common air pollutant exposures may be ideal to address limitations of published research.ConclusionsIn ECHO we have the opportunity to pioneer unifying exposure assessment and evaluate effects across multiple periods of development and neurodevelopmental outcomes, setting the standard for evaluation of prenatal air pollution exposures with the goal of improving children's health.

BackgroundLead is a ubiquitous toxicant following three compartment kinetics with the longest half-life found in bones. Patella and tibia lead levels-validated measures of cumulative exposure-require specialized X-ray-fluorescence-spectroscopy available only in a few centers worldwide. We developed minimally invasive biomarkers reflecting individual cumulative lead exposure using blood DNA methylation profiles-obtainable via Illumina 450K or IlluminaEPIC bead-chip assays.MethodsWe developed and tested two methylation-based biomarkers from 348 Normative Aging Study (NAS) elderly men. We selected methylation sites with strong associations with bone lead levels via robust regressions analysis and constructed the biomarkers using elastic nets. Results were validated in a NAS subset, reporting specificity, and sensitivity.FindingsParticipants were 73 years old on average (standard deviation, SD = 6), with moderate lead levels of (mean ± SD patella: 27 ± 18 µg/g; tibia:21 ± 13 µg/g). Methylation-based biomarkers for lead in patella and tibia included 59 and 138 DNA methylation sites, respectively. Estimated lead levels were significantly correlated with actual measured values, (r = 0.62 patella, r = 0.59 tibia) and had low mean square error (MSE) (MSE = 0.68 patella, MSE = 0.53 tibia). Means and distributions of the estimated and actual lead levels were not significantly different across patella and tibia bones (p > 0.05). Methylation-based biomarkers discriminated participants highly exposed (>median) to lead with a specificity of 74 and 73% for patella and tibia lead levels, respectively, with 70% sensitivity.InterpretationDNA methylation-based lead biomarkers are novel tools that can be used to reconstruct decades' worth of individual cumulative lead exposure using only blood DNA methylation profiles and may help identify the consequences of cumulative exposure.

BackgroundDNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts.MethodsNine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts.ResultsAmong 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate

Birthweight is associated with health outcomes across the life course, DNA methylation may be an underlying mechanism. In this meta-analysis of epigenome-wide association studies of 8,825 neonates from 24 birth cohorts in the Pregnancy And Childhood Epigenetics Consortium, we find that DNA methylation in neonatal blood is associated with birthweight at 914 sites, with a difference in birthweight ranging from -183 to 178 grams per 10% increase in methylation (PBonferroni

Genome-wide association studies have identified hundreds of genetic variants associated with blood pressure (BP), but sequence variation accounts for a small fraction of the phenotypic variance. Epigenetic changes may alter the expression of genes involved in BP regulation and explain part of the missing heritability. We therefore conducted a two-stage meta-analysis of the cross-sectional associations of systolic and diastolic BP with blood-derived genome-wide DNA methylation measured on the Infinium HumanMethylation450 BeadChip in 17,010 individuals of European, African American, and Hispanic ancestry. Of 31 discovery-stage cytosine-phosphate-guanine (CpG) dinucleotides, 13 replicated after Bonferroni correction (discovery: N = 9,828, p < 1.0 × 10-7; replication: N = 7,182, p  30%) and independent of known BP genetic variants, explaining an additional 1.4% and 2.0% of the interindividual variation in systolic and diastolic BP, respectively. Bidirectional Mendelian randomization among up to 4,513 individuals of European ancestry from 4 cohorts suggested that methylation at cg08035323 (TAF1B-YWHAQ) influences BP, while BP influences methylation at cg00533891 (ZMIZ1), cg00574958 (CPT1A), and cg02711608 (SLC1A5). Gene expression analyses further identified six genes (TSPAN2, SLC7A11, UNC93B1, CPT1A, PTMS, and LPCAT3) with evidence of triangular associations between methylation, gene expression, and BP. Additional integrative Mendelian randomization analyses of gene expression and DNA methylation suggested that the expression of TSPAN2 is a putative mediator of association between DNA methylation at cg23999170 and BP. These findings suggest that heritable DNA methylation plays a role in regulating BP independently of previously known genetic variants.

BackgroundEarly-life exposure to lead is associated with deficits in neurodevelopment and with hematopoietic system toxicity. DNA methylation may be one of the underlying mechanisms for the adverse effects of prenatal lead on the offspring, but epigenome-wide methylation data for low levels of prenatal lead exposure are lacking.ObjectivesWe investigated the association between prenatal maternal lead exposure and epigenome-wide DNA methylation in umbilical cord blood nucleated cells in Project Viva, a prospective U.S.-based prebirth cohort with relatively low levels of lead exposure.MethodsAmong 268 mother-infant pairs, we measured lead concentrations in red blood cells (RBC) from prenatal maternal blood samples, and using HumanMethylation450 Bead Chips, we measured genome-wide methylation levels at 482,397 CpG loci in umbilical cord blood and retained 394,460 loci after quality control. After adjustment for batch effects, cell types, and covariates, we used robust linear regression models to examine associations of prenatal lead exposure with DNA methylation in cord blood at epigenome-wide significance level [false discovery rate (FDR)

BACKGROUND: We have an incomplete understanding of the differences between cancer stem cells (CSCs) in human papillomavirus-positive (HPV-positive) and -negative (HPV-negative) head and neck squamous cell cancer (HNSCC). The PI3K pathway has the most frequent activating genetic events in HNSCC (especially HPV-positive driven), but the differential signaling between CSCs and non-CSCs is also unknown. METHODS: We addressed these unresolved questions using CSCs identified from 10 HNSCC patient-derived xenografts (PDXs). Sored populations were serially passaged in nude mice to evaluate tumorigenicity and tumor recapitulation. The transcription profile of HNSCC CSCs was characterized by mRNA sequencing, and the susceptibility of CSCs to therapy was investigated using an in vivo model. SOX2 transcriptional activity was used to follow the asymmetric division of PDX-derived CSCs. All statistical tests were two-sided. RESULTS: CSCs were enriched by high aldehyde dehydrogenase (ALDH) activity and CD44 expression and were similar between HPV-positive and HPV-negative cases (percent tumor formation injecting ≤ 1x10(3) cells: ALDH(+)CD44(high) = 65.8%, ALDH(-)CD44(high) = 33.1%, ALDH(+)CD44(high) = 20.0%; and injecting 1x10(5) cells: ALDH(-)CD44(low) = 4.4%). CSCs were resistant to conventional therapy and had PI3K/mTOR pathway overexpression (GSEA pathway enrichment, P < .001), and PI3K inhibition in vivo decreased their tumorigenicity (40.0%-100.0% across cases). PI3K/mTOR directly regulated SOX2 protein levels, and SOX2 in turn activated ALDH1A1 (P < .001 013C and 067C) expression and ALDH activity (ALDH(+) [%] empty-control vs SOX2, 0.4% ± 0.4% vs 14.5% ± 9.8%, P = .03 for 013C and 1.7% ± 1.3% vs 3.6% ± 3.4%, P = .04 for 067C) in 013C and 067 cells. SOX2 enhanced sphere and tumor growth (spheres/well, 013C P < .001 and 067C P = .04) and therapy resistance. SOX2 expression prompted mesenchymal-to-epithelial transition (MET) by inducing CDH1 (013C P = .002, 067C P = .01), followed by asymmetric division and proliferation, which contributed to tumor formation. CONCLUSIONS: The molecular link between PI3K activation and CSC properties found in this study provides insights into therapeutic strategies for HNSCC. Constitutive expression of SOX2 in HNSCC cells generates a CSC-like population that enables CSC studies.

PurposeCis-acting regulatory SNPs resulting in differential allelic expression (DAE) may, in part, explain the underlying phenotypic variation associated with many complex diseases. To investigate whether common variants associated with DAE were involved in breast cancer susceptibility among BRCA1 and BRCA2 mutation carriers, a list of 175 genes was developed based of their involvement in cancer-related pathways.MethodsUsing data from a genome-wide map of SNPs associated with allelic expression, we assessed the association of ~320 SNPs located in the vicinity of these genes with breast and ovarian cancer risks in 15,252 BRCA1 and 8211 BRCA2 mutation carriers ascertained from 54 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2.ResultsWe identified a region on 11q22.3 that is significantly associated with breast cancer risk in BRCA1 mutation carriers (most significant SNP rs228595 p = 7 × 10-6). This association was absent in BRCA2 carriers (p = 0.57). The 11q22.3 region notably encompasses genes such as ACAT1, NPAT, and ATM. Expression quantitative trait loci associations were observed in both normal breast and tumors across this region, namely for ACAT1, ATM, and other genes. In silico analysis revealed some overlap between top risk-associated SNPs and relevant biological features in mammary cell data, which suggests potential functional significance.ConclusionWe identified 11q22.3 as a new modifier locus in BRCA1 carriers. Replication in larger studies using estrogen receptor (ER)-negative or triple-negative (i.e., ER-, progesterone receptor-, and HER2-negative) cases could therefore be helpful to confirm the association of this locus with breast cancer risk.

BackgroundGestational age is often used as a proxy for developmental maturity by clinicians and researchers alike. DNA methylation has previously been shown to be associated with age and has been used to accurately estimate chronological age in children and adults. In the current study, we examine whether DNA methylation in cord blood can be used to estimate gestational age at birth.ResultsWe find that gestational age can be accurately estimated from DNA methylation of neonatal cord blood and blood spot samples. We calculate a DNA methylation gestational age using 148 CpG sites selected through elastic net regression in six training datasets. We evaluate predictive accuracy in nine testing datasets and find that the accuracy of the DNA methylation gestational age is consistent with that of gestational age estimates based on established methods, such as ultrasound. We also find that an increased DNA methylation gestational age relative to clinical gestational age is associated with birthweight independent of gestational age, sex, and ancestry.ConclusionsDNA methylation can be used to accurately estimate gestational age at or near birth and may provide additional information relevant to developmental stage. Further studies of this predictor are warranted to determine its utility in clinical settings and for research purposes. When clinical estimates are available this measure may increase accuracy in the testing of hypotheses related to developmental age and other early life circumstances.

Estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2x10-9), independent of chronological age, even after adjusting for additional risk factors (p

Epigenetic modifications, including DNA methylation, represent a potential mechanism for environmental impacts on human disease. Maternal smoking in pregnancy remains an important public health problem that impacts child health in a myriad of ways and has potential lifelong consequences. The mechanisms are largely unknown, but epigenetics most likely plays a role. We formed the Pregnancy And Childhood Epigenetics (PACE) consortium and meta-analyzed, across 13 cohorts (n = 6,685), the association between maternal smoking in pregnancy and newborn blood DNA methylation at over 450,000 CpG sites (CpGs) by using the Illumina 450K BeadChip. Over 6,000 CpGs were differentially methylated in relation to maternal smoking at genome-wide statistical significance (false discovery rate, 5%), including 2,965 CpGs corresponding to 2,017 genes not previously related to smoking and methylation in either newborns or adults. Several genes are relevant to diseases that can be caused by maternal smoking (e.g., orofacial clefts and asthma) or adult smoking (e.g., certain cancers). A number of differentially methylated CpGs were associated with gene expression. We observed enrichment in pathways and processes critical to development. In older children (5 cohorts, n = 3,187), 100% of CpGs gave at least nominal levels of significance, far more than expected by chance (p value < 2.2 × 10(-16)). Results were robust to different normalization methods used across studies and cell type adjustment. In this large scale meta-analysis of methylation data, we identified numerous loci involved in response to maternal smoking in pregnancy with persistence into later childhood and provide insights into mechanisms underlying effects of this important exposure.

The limitations of cancer cell lines have led to the development of direct patient-derived xenograft models. However, the interplay between the implanted human cancer cells and recruited mouse stromal and immune cells alters the tumor microenvironment and limits the value of these models. To overcome these constraints, we have developed a technique to expand human hematopoietic stem and progenitor cells (HSPCs) and use them to reconstitute the radiation-depleted bone marrow of a NOD/SCID/IL2rg(-/-) (NSG) mouse on which a patients tumor is then transplanted (XactMice). The human HSPCs produce immune cells that home into the tumor and help replicate its natural microenvironment. Despite previous passage on nude mice, the expression of epithelial, stromal and immune genes in XactMice tumors aligns more closely to that of the patient tumor than to those grown in non-humanized mice-an effect partially facilitated by human cytokines expressed by both the HSPC progeny and the tumor cells. The human immune and stromal cells produced in the XactMice can help recapitulate the microenvironment of an implanted xenograft, reverse the initial genetic drift seen after passage on non-humanized mice and provide a more accurate tumor model to guide patient treatment.

BackgroundDNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age.ResultsHere we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43.ConclusionsDNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

Differences in the ability of opioid drugs to promote regulated endocytosis of μ-opioid receptors are related to their tendency to produce drug tolerance and dependence. Here we show that drug-specific differences in receptor internalization are determined by a conserved, 10-residue sequence in the receptor's carboxyl-terminal cytoplasmic tail. Diverse opioids induce receptor phosphorylation at serine (S)375, present in the middle of this sequence, but opioids differ markedly in their ability to drive higher-order phosphorylation on flanking residues [threonine (T)370, T376, and T379]. Multi-phosphorylation is required for the endocytosis-promoting activity of this sequence and occurs both sequentially and hierarchically, with S375 representing the initiating site. Higher-order phosphorylation involving T370, T376, and T379 specifically requires GRK2/3 isoforms, and the same sequence controls opioid receptor internalization in neurons. These results reveal a biochemical mechanism differentiating the endocytic activity of opioid drugs.

Background: Little is known about the exact process of how patients search for medical information on the internet and what they retrieve. There is especially a paucity of literature on browsing for information on minor ailments, a term used for harmless diseases that are very common in the general population and thus have a significant impact on health care.Objective: This vignette-based experimental study aimed to explore what kind of Web-based search strategies are applied and how search strategies, demographic characteristics, and the quality of the visited websites relate to finding the right diagnosis. Additional goals were to describe how searching on the Web influences one's perception of the severity of the potential diagnosis and whether or not the participants would discuss the information they found on the internet with their doctors.Methods: Out of 1372 survey participants, 355 were randomly sampled, and 155 of them were recruited and assigned to one of four clinical scenarios. Each search term they used was classified as one of three search strategies: (1) hypothesis testing, (2) narrowing within the general hypothesis area, and (3) symptom exploration. The quality of the websites used was determined by using the DISCERN instrument. To compare the diagnostic accuracy of the participants before and after the internet search, a McNemar test was used. Chi-square tests were used to describe which factors are related to the chosen search strategy. A multivariate binary logistic regression model was constructed to predict which factors are related to finding a sound diagnosis after searching the internet for health information.Results: Most participants (65.8%, 102/155) used the symptom exploration strategy. However, this depends on the assigned scenario (P<.001) and the self-estimated severity score of the symptoms before the internet search (P=.001). A significant relation was found between choosing an accurate diagnosis and age (odds ratio [OR] 0.94, 95% CI 0.90 to 0.98) and the clinical scenario, as well as the use of high-quality websites (OR 7.49, 95% CI 1.85 to 30.26). Browsing the internet did not lead to a statistically significant change in participants' beliefs about the severity of the condition (McNemar test, P=.85). Most participants (65%) shared their retrieved information with their physician and most of them (75%) received a positive response.Conclusions: Our findings suggest that most patients use a symptom-based approach; however, if patients expect the potential diagnosis to be severe, they tend to use a hypothesis verification strategy more often and are therefore prone to certain forms of bias. In addition, self-diagnosing accuracy is related to younger age, the symptom scenario, and the use of high-quality websites. We should find ways to guide patients toward search strategies and websites that may more likely lead to accurate decision making. [ABSTRACT FROM AUTHOR]