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bioRxiv2017

Association Between Genetically Elevated Levels Of Inflammatory Biomarkers And Risk Of Schizophrenia: A Two-Sample Mendelian Randomisation Study

BackgroundPositive associations between inflammatory biomarkers and risk of psychiatric disorders, including schizophrenia, have been reported in observational studies. However, conventional observational studies are prone to bias such as reverse causation and residual confounding.\n\nMethodsIn this study, we used summary data to evaluate the association of genetically elevated C reactive protein (CRP), interleukin-1 receptor antagonist (IL-1Ra) and soluble interleukin-6 receptor (IL-6R) levels with schizophrenia in a two-sample Mendelian randomisation design.\n\nResultsThe pooled odds ratio estimate using 18 CRP genetic instruments was 0.90 (95% CI: 0.84; 0.97) per two-fold increment in CRP levels; consistent results were obtained using different Mendelian randomisation methods and a more conservative set of instruments. The odds ratio for soluble IL-6R was 1.06 (95% CI: 1.01; 1.12) per two-fold increment. Estimates for IL-1Ra were inconsistent among instruments and pooled estimates were imprecise and centred on the null.\n\nConclusionUnder Mendelian randomisation assumptions, our findings suggest a protective causal effect of CRP and a risk-increasing causal effect of soluble IL-6R (potentially mediated at least in part by CRP) on schizophrenia risk.

epidemiology↗

bioRxiv2017

Testing the principles of Mendelian randomization: Opportunities and complications on a genomewide scale

BackgroundMendelian randomization (MR) uses genetic variants as instrumental variables to assess whether observational associations between exposures and disease reflect causal relationships. MR requires genetic variants to be independent of factors that confound observational associations.\n\nMethodsUsing data from the Avon Longitudinal Study of Parents and Children, associations within and between 121 phenotypes and 13,720 genetic variants (from the NHGRI-EBI GWAS catalog) were examined to assess the validity of MR assumptions.\n\nResultsAmongst 7,260 pairwise comparisons between the 121 phenotypes, 2,188 (30%) provided evidence of association, where 363 were expected at the 5% level (observed:expected ratio=6.03; 95% CI: 5.42, 6.70; {chi}2=9682.29; d.f. =1, P[≤]1x10-50). Amongst 1,660,120 pairwise associations between phenotypes and genotypes, 86,748 (5.2%) gave evidence of association at the same threshold, where 83,006 were expected (observed:expected ratio=1.05; 95% CI: 1.04, 1.05; {chi}2=117.57; d.f. =1, P=2.15x10-27). Amongst 1,171,764 pairwise associations between the phenotypes and LD pruned independent genetic variants, 60,136 (5.1%) gave evidence of association, where 58,588 were expected (observed:expected ratio=1.03; 95% CI: 1.03, 1.08; {chi}2= 43.05; d.f. = 1, P=5.33x10-11).\n\nConclusionThese results confirm previously observed patterns of phenotypic correlation. They also provide evidence of a substantially lower level of association between genetic variants and phenotypes, with residual inflation the likely product of indistinguishable real genetic association, multiple variables measuring the same biological phenomena, or pleiotropy. These results reflect the favorable properties of genetic instruments for estimating causal relationships, but confirm the need for functional information or analytical methods to account for pleiotropic events.

epidemiology↗

bioRxiv2017

Disease as collider: a new case-only method to discover environmental factors in complex diseases with genetic risk estimation

BackgroundCase-only design for gene-environment interaction (CODGEI) relies on the rare disease assumption. A negative association due to collider bias appears between gene and environment when this assumption is not respected. Genetic risk estimation can quantify part of the predisposition of an individual to a disease.\n\nMethodsWe introduce Disease As Collider (DAC), a new case-only methodology to discover environmental factors using genetic risk estimation: a negative correlation between genetic risk and environment in cases provides a signature of a genuine environmental risk marker. Simulation of disease occurrence in a source population allows to estimate the statistical power of DAC and the influence of collider bias in CODGEI. We illustrate DAC in 831 type 1 diabetes (T1D) patients. Results: The power of DAC increases with sample size, prevalence and accuracy of genetic risk estimation. For a prevalence of 1% and a realistic genetic risk estimation, power of 80% is reached for a sample size under 3000. Collider bias offers an alternative interpretation to the results of CODGEI in a published study on breast cancer.\n\nConclusionDAC could provide a new line of evidence for discovering which environmental factors play a role in complex diseases or confirming results obtained in case-control studies. We discuss the circumstances needed for DAC to participate in the dissection of environmental determinants of disease. We provide guidance on the use of CODGEI regarding the rare disease assumption.\n\nO_LSTKey messagesC_LSTO_LIA complex disease is a collider between genetic determinants and environmental factors; it is a consequence of both.\nC_LIO_LICollider bias can affect the results of the case-only design for gene-environment interactions when the disease is common.\nC_LIO_LIUsing genetic risk estimation, collider bias can be used to discover or confirm the association between a disease and an environmental factor in a case-only setting.\nC_LIO_LIStatistical power of this approach is small when the disease is rare. Power increases with sample size, prevalence and genetic risk prediction accuracy.\nC_LI

epidemiology↗

bioRxiv2017

Increasing Antibiotic Susceptibility In Staphylococcus aureus In Boston, Massachusetts, 2000-2014: An Observational Study

BackgroundMethicillin resistant S. aureus (MRSA) has been declining over the past decade, but changes in S. aureus overall and the implications for trends in antibiotic resistance remain unclear.\n\nObjectiveTo determine whether the decline in rates of infection by MRSA has been accompanied by changes in rates of infection by methicillin susceptible, penicillin resistant S. aureus (MSSA) and penicillin susceptible S. aureus (PSSA). We test if these dynamics are associated with specific genetic lineages and evaluate gains and losses of resistance at the strain level.\n\nMethodsWe conducted a 15 year retrospective observational study at two tertiary care institutions in Boston, MA of 31,589 adult inpatients with S. aureus infections. Surveillance swabs and duplicate specimens were excluded. We also sequenced a sample of contemporary isolates (n = 180) obtained between January 2016 and July 2016. We determined changes in the annual rates of infection per 1,000 inpatient admissions by S. aureus subtype and in the annual mean antibiotic resistance by subtype. We performed phylogenetic analysis to generate a population structure and infer gain and loss of the genetic determinants of resistance.\n\nResultsOf the 43,954 S. aureus infections over the study period, 21,779 were MRSA, 17,565 MSSA and 4,610 PSSA. After multivariate adjustment, annual rates of infection by S. aureus declined from 2003 to 2014 by 2.9% (95% CI, 1.6%-4.3%), attributable to an annual decline in MRSA of 9.1% (95% CI, 6.3%-11.9%) and in MSSA by 2.2% (95% CI, 0.4%-4.0%). PSSA increased over this time period by 4.6% (95% CI, 3.0%-6.3%) annually. Resistance in S. aureus decreased from 2000 to 2014 by 0.86 antibiotics (95% CI, 0.81-0.91). By phylogenetic inference, 5/35 MSSA and 2/20 PSSA isolates in the common MRSA lineages ST5/USA100 and ST8/USA300 arose from the loss of genes conferring resistance.\n\nConclusions and relevanceAt two large tertiary care centers in Boston, MA, S. aureus infections have decreased in rate and have become more susceptible to antibiotics, with a rise in PSSA making penicillin an increasingly viable and important treatment option.

epidemiology↗

bioRxiv2017

Maternal BMI at the start of pregnancy and offspring epigenome-wide DNA methylation: Findings from the Pregnancy and Childhood Epigenetics (PACE) consortium.

Pre-pregnancy maternal obesity is associated with adverse offspring outcomes at birth and later in life. Epigenetic modifications such as DNA methylation could contribute, but data are scarce.\n\nWithin the Pregnancy and Childhood Epigenetics (PACE) Consortium, we meta-analysed the association between pre-pregnancy maternal BMI and methylation at over 450,000 sites in newborn blood DNA, across 19 cohorts (9,340 mother-newborn pairs). We attempted to infer causality by comparing effects of maternal versus paternal BMI and incorporating genetic variation. In four additional cohorts (1,817-mother-child pairs), we meta-analysed the association between maternal BMI at the start of pregnancy and blood methylation in adolescents.\n\nIn newborns, maternal BMI was associated with modest (<0.2% per BMI unit (1kg/m2), P<1.06*10-7) methylation variation at 9,044 sites throughout the genome. Adjustment for estimated cell proportions attenuated the number of significant CpGs to 104, including 86 sites common to the unadjusted model. These 86 sites map to several genes reported to be associated with adiposity-related and/or neuropsychiatric traits. At 72/86 sites, the direction of association was the same in newborns and adolescents, suggesting persistence of signals. However, we found evidence for a causal intrauterine effect of maternal BMI on newborn methylation at just 8/86 sites.\n\nIn conclusion, maternal adiposity is associated with modest variations in newborn blood DNA methylation, but the potential biological consequences of these variations are currently unclear.

epidemiology↗

bioRxiv2017

Modeling the consequences of regional heterogeneity in human papillomavirus (HPV) vaccination uptake on transmission in Switzerland

BackgroundCompleted human papillomavirus (HPV) vaccination by age 16 years among women in Switzerland ranges from 17 to 75% across 26 cantons. The consequences of regional heterogeneity in vaccination coverage on transmission and prevalence of HPV-16 are unclear.\n\nMethodsWe developed a deterministic, population-based model that describes HPV-16 transmission among young adults within and between the 26 cantons of Switzerland. We parameterized the model using sexual behavior data from Switzerland and data from the Swiss National Vaccination Coverage Survey. First, we investigated the general consequences of heterogeneity in vaccination uptake between two sub-populations. We then compared the predicted prevalence of HPV-16 after the introduction of heterogeneous HPV vaccination uptake in all of Switzerland with homogeneous vaccination at an uptake that is identical to the national average (52%).\n\nResultsHPV-16 prevalence in women is 3.34% when vaccination is introduced and begins to diverge across cantons, ranging from 0.14 to 1.09% after 15 years of vaccination. After the same time period, overall prevalence of HPV-16 in Switzerland is only marginally higher (0.55 %) with heterogeneous vaccination uptake than with homogeneous uptake (0.49%). Assuming inter-cantonal sexual mixing, cantons with low vaccination uptake benefit from a reduction in prevalence at the expense of cantons with high vaccination uptake.\n\nConclusionsRegional variations in uptake diminish the overall effect of vaccination on HPV-16 prevalence in Switzerland, although the effect size is small. Cantonal efforts towards HPV-prevalence reduction by increasing vaccination uptake are impaired by cantons with low vaccination uptake. Harmonization of cantonal vaccination programs would reduce inter-cantonal differences in HPV-16 prevalence.

epidemiology↗

bioRxiv2017

pomp-Astic Inference For Epidemic Models: Simple Vs. Complex

Infectious disease surveillance data often provides only partial information about the progression of the disease in the individual while disease transmission is often modelled using complex mathematical models for large populations, where variability only enters through a stochastic observation process. In this work it is shown that a rather simplistic, but truly stochastic transmission model, is competitive with respect to model fit when compared with more detailed deterministic transmission models and even preferable because the role of each parameter and its identifiability is clearly understood in the simpler model. The inference framework for the stochastic model is provided by iterated filtering methods which are readily implemented in the R package pomp. We illustrate our findings on German rotavirus surveillance data from 2001 to 2008 and calculate a model based estimate for the basic reproduction number R0 using these data.

epidemiology↗

bioRxiv2017

Systematic Identification of Correlates of HIV-1 Infection: An X-Wide Association Study in Zambia

BackgroundHIV-1 remains the leading cause of death among adults in Sub-Saharan Africa, and over 1 million people are infected annually. Better identification of at-risk groups could benefit prevention and treatment programmes. We systematically identified factors related to HIV-1 infection in two nationally representative cohorts of women that participated in Zambias Demographic and Health Surveys (DHS).\n\nMethodsWe conducted a comprehensive analysis to identify and replicate the association of 1,415 social, economic, environmental, and behavioral indicators with HIV-1 status. We used the 2007 and 2013-2014 DHS surveys conducted among 5,715 and 15,433 Zambian women, respectively (727 indicators in 2007; 688 in 2013-2014; 688 in both). We used false discovery rate criteria to identify indicators that are strongly associated with HIV-1 in univariate and multivariate models in the entire population, as well as in subgroups stratified by wealth, residence, age, and history of HIV-1 testing.\n\nFindingsIn the univariate analysis we identified 102 and 182 variables that are associated with HIV-1 in the 2007 and 2013-2014 surveys, respectively, among which 79 were associated in both. Variables that were associated with HIV-1 status in all full-sample models (unadjusted and adjusted) as well as in at least 17 out of 18 subgroups include being formerly in a union (adjusted OR 2007 2.8, p<10-16; 2013-2014 2.8, p<10-29), widowhood (adjusted OR 2007 3.7, p<10-12; 2013-2014 4.2, p<10-30), history of genital ulcers in the last 12 months (adjusted 2007 OR 2.4, p<10-5; 2013-2014 2.2, p<10-6), and having a woman for the head of the household (2007 OR 1.7, p<10-7; 2013-2014 OR 2.1, p<10-26), while owning a bicycle (adjusted 2007 OR 0.6, p<10-6; 2013-2014 0.6, p<10-8) and currently breastfeeding (adjusted 2007 OR 0.5, p<10-9; 2013-2014 0.4, p<10-26) were associated with decreased risk. Using the identified variables, area under the curve for HIV-1 positivity ranged from 0.76 to 0.82.\n\nInterpretationOur X-wide association study in Zambian women identifies multiple under-recognized factors correlated with HIV-1 infection in 2007 and 2013-2014, including widowhood, breastfeeding, and being the head of the household. These variables could be used to improve HIV-1 testing and identification programs.

epidemiology↗

bioRxiv2017

Evaluating Clinical Stop-Smoking Services Globally: Proposal For A Minimum Data Set

Background and aimsBehavioural and pharmacological support for smoking cessation improves the chances of success and represents a highly cost-effective way of preventing chronic disease and premature death. There are a large number of clinical stop-smoking services around the world. These could be connected into a global network to provide data to assess what treatment components are most effective, for what populations, in what settings. This requires data to be collected according to a minimum standard set of data items. This paper sets out a proposal for this global minimum data set.\n\nMethodsWe reviewed sets of data items used in clinical services that have already benefited from standardised approaches to using data. We identified client and treatment data items that may directly or indirectly influence outcome, and outcome variables that were practicable to obtain in clinical practice. We then consulted service providers in countries that may have an interest in taking part in a global network of smoking cessation services, and revised the sets of data items according to their feedback.\n\nResultsThree sets of data items are proposed. The first is a set of features characterising treatments offered by a service. The second is a core set of data items describing clients characteristics, engagement with the service, and outcomes. The third is an extended set of client data items to be captured in addition to the core data items wherever resources permit.\n\nConclusionsWe propose minimum standards for capturing data from clinical smoking cessation services globally. This could provide a basis for meaningful evaluations of different smoking cessation treatments in different populations in a variety of settings across many countries.

epidemiology↗

bioRxiv2017

Robust Inference In Two-Sample Mendelian Randomisation Via The Zero Modal Pleiotropy Assumption

BackgroundMendelian randomisation (MR) is being increasingly used to strengthen causal inference in observational studies. Availability of summary data of genetic associations for a variety of phenotypes from large genome-wide association studies (GWAS) allows straightforward application of MR using summary data methods, typically in a two-sample design. In addition to the conventional inverse variance weighting (IVW) method, recently developed summary data MR methods, such as the MR-Egger and weighted median approaches, allow a relaxation of the instrumental variable assumptions.\n\nMethodsHere, a new method -the mode-based estimate (MBE) - is proposed to obtain a single causal effect estimate from multiple genetic instruments. The MBE is consistent when the largest number of similar (identical in infinite samples) individual-instrument causal effect estimates comes from valid instruments, even if the majority of instruments are invalid. We evaluate the performance of the method in simulations designed to mimic the two-sample summary data setting, and demonstrate its use by investigating the causal effect of plasma lipid fractions and urate levels on coronary heart disease risk.\n\nResultsThe MBE presented less bias and type-I error rates than other methods under the null in many situations. Its power to detect a causal effect was smaller compared to the IVW and weighted median methods, but was larger than that of MR-Egger regression, with sample size requirements typically smaller than those available from GWAS consortia.\n\nConclusionsThe MBE relaxes the instrumental variable assumptions, and should be used in combination with other approaches in a sensitivity analysis.\n\nKey MessagesO_LISummary data Mendelian randomisation, typically in a two-sample setting, is being increasingly used due to the availability of summary association results from large genome- wide association studies.\nC_LIO_LIMendelian randomisation analyses using multiple genetic instruments are prone to bias due to horizontal pleiotropy, especially when genetic instruments are selected based solely on statistical criteria.\nC_LIO_LIA causal effect estimate robust to horizontal pleiotropy can be obtained using the mode- based estimate (MBE).\nC_LIO_LIThe MBE requires that the most common causal effect estimate is a consistent estimate of the true causal effect, even if the majority of instruments are invalid (i.e., the ZEro Modal Pleiotropy Assumption, or ZEMPA).\nC_LIO_LIPlotting the smoothed empirical density function is useful to explore the distribution of causal effect estimates, and to understand how the MBE is determined.\nC_LI

epidemiology↗

bioRxiv2017

Biologics-associated Risks for Incident Skin and Soft Tissue Infections in Psoriasis Patients: Results from Propensity Score-Stratified Survival Analysis

BackgroundHow biologics affect psoriasis patients risks for SSTIs in a pragmatic clinical setting remains unclear.\n\nMethodsIn a cohort of adult psoriasis outpatients (aged 20 years or older) who visited the Dermatology Clinic in 2010-2015, we compared incident SSTI risks between patients using biologics (users) versus nonbiologics (nonusers). We also estimated SSTI risks in biologics-associated time-periods relative to nonbiologics only in users. We applied random effects Cox proportional hazard models with propensity score-stratification to account for differential baseline hazards.\n\nResultsOver a median follow-up of 2.8 years (interquartile range: 1.5, 4.3), 172 of 922 patients ever received biologics (18.7%); 233 SSTI incidents occurred during 2518.3 person-years, with an overall incidence of 9.3/100 person-years (95% confidence interval [CI]: 8.1, 10.6). In univariate analysis, users showed an 89% lower risk for SSTIs than nonusers (hazard ratio [HR]: 0.11, 95%CI: 0.05, 0.26); the association persisted in a multivariable model (adjusted HR: 0.26, 95%CI: 0.12, 0.58). Among biologics users, biologics-exposed time-periods were associated with a nonsignificant 21% increased risk (adjusted HR: 1.21, 95%CI: 0.41, 3.59).\n\nConclusionsDespite of adjusting for the underlying risk profiles, risk comparisons between biologics users and nonusers remained confounded by treatment selection. By comparing time-periods being exposed versus unexposed to biologics among users, the current analysis did not find evidence for an increased SSTI risk that was associated with biologics use in psoriasis patients.

epidemiology↗

bioRxiv2017

Case fatality as an indicator for the human toxicity of pesticides - a systematic review on the availability and variability of severity indicators of pesticide poisoning

ObjectiveTo investigate if case fatality and other indicators of severity of human pesticide poisonings can be used to prioritize pesticides of public health concern. To study the heterogeneity of data across countries, cause of poisonings, and treatment facilities.\n\nMethodsWe searched literature databases as well as the internet for studies on case-fatality and severity scores of pesticide poisoning. Studies published between 1990 and 2014 providing information on active ingredients in pesticides or chemical groups of active ingredients were included. The variability of case-fatality-ratios was analyzed by computing the coefficient of variation as the ratio of the standard deviation to the mean.\n\nFindingsWe identified 145 studies of which 67 could be included after assessment. Case-fatality-ratio (CFR) on 68 active ingredients and additionally on 13 groups of active ingredients were reported from 20 countries. Mean CFR for group of pesticides is 12 %, for single pesticides 15 %. Of those 12 active ingredients with a CFR above 20 % only two are WHO-classified as \"extremely hazardous\" or \"highly hazardous\", respectively. Two of seven pesticides considered \"unlikely to present hazard in normal use\" show CFR above 20 %. The variability of reported case fatality was rather low.\n\nConclusionAlthough human pesticide poisoning is a serious public health problem an unexpected small number of publications report on the clinical outcomes. However, CFR of acute human pesticide poisoning are available for several groups of pesticides as well as for active ingredients and show little variability. Therefore the CFR might be utilized to prioritize highly hazardous pesticides especially since there is limited correspondence between the animal-test-based hazard classification and the human CFR of the respective pesticide. Reporting of available poisoning data should be improved, human case-fatality data are a reasonable tool to be included systematically in pesticide registration and regulation.

epidemiology↗

bioRxiv2017

Metabolic profiling of adiponectin levels in adults: Mendelian randomization analysis

BackgroundAdiponectin, a circulating adipocyte-derived protein has insulin-sensitizing, anti-inflammatory, anti-atherogenic, and cardiomyocyte-protective properties in animal models. However, the systemic effects of adiponectin in humans are unknown.\n\nObjectivesOur aims were to define the metabolic profile associated with higher blood adiponectin concentration and investigate whether variation in adiponectin concentration affects the systemic metabolic profile.\n\nMethodsWe applied multivariable regression in up to 5,906 adults and Mendelian randomization (using cis-acting genetic variants in the vicinity of the adiponectin gene as instrumental variables) for analysing the causal effect of adiponectin in the metabolic profile of up to 38,058 adults. Participants were largely European from six longitudinal studies and one genome-wide association consortium.\n\nResultsIn the multivariable regression analyses, higher circulating adiponectin was associated with higher HDL lipids and lower VLDL lipids, glucose levels, branched-chain amino acids, and inflammatory markers. However, these findings were not supported by Mendelian randomization analyses for most metabolites. Findings were consistent between sexes and after excluding high risk groups (defined by age and occurrence of previous cardiovascular event) and one study with admixed population.\n\nConclusionOur findings indicate that blood adiponectin concentration is more likely to be an epiphenomenon in the context of metabolic disease than a key determinant.

epidemiology↗

bioRxiv2017

The causal effect of educational attainment on Alzheimer’s disease: A two-sample Mendelian randomization study

BackgroundObservational evidence suggests that higher educational attainment is protective for Alzheimers disease (AD). It is unclear whether this association is causal or confounded by demographic and socioeconomic characteristics. We examined the causal effect of educational attainment on AD in a two-sample MR framework.\n\nMethodsWe extracted all available effect estimates of the 74 single nucleotide polymorphisms (SNPs) associated with years of schooling from the largest genome-wide association study (GWAS) of educational attainment (N=293,723) and the GWAS of AD conducted by the International Genomics of Alzheimers Project (n=17,008 AD cases and 37,154 controls). SNP-exposure and SNP-outcome coefficients were combined using an inverse variance weighted approach, providing an estimate of the causal effect of each SD increase in years of schooling on AD. We also performed appropriate sensitivity analyses examining the robustness of causal effect estimates to the various assumptions and conducted simulation analyses to examine potential survival bias of MR analyses.\n\nFindingsWith each SD increase in years of schooling (3.51 years), the odds of AD were, on average, reduced by approximately one third (odds ratio= 0.63, 95% confidence interval [CI]: 0.48 to 0.83, p<0.001). Causal effect estimates were consistent when using causal methods with varying MR assumptions or different sets of SNPs for educational attainment, lending confidence to the magnitude and direction of effect in our main findings. There was also no evidence of survival bias in our study.\n\nInterpretationOur findings support a causal role of educational attainment on AD, whereby an additional [~]3.5 years of schooling reduces the odds of AD by approximately one third.

epidemiology↗

bioRxiv2017

Severe population collapses and species extinctions in multi-host epidemic dynamics

Most infectious diseases including more than half of known human pathogens are not restricted to just one host, yet much of the mathematical modeling of infections has been limited to a single species. We investigate consequences of a single epidemic propagating in multiple species and compare and contrast it with the endemic steady state of the disease. We use the two-species Susceptible-Infected-Recovered (SIR) model to calculate the severity of post-epidemic collapses in populations of two host species as a function of their initial population sizes, the times individuals remain infectious, and the matrix of infection rates. We derive the criteria for a very large, extinction-level, population collapse in one or both of the species. The main conclusion of our study is that a single epidemic could drive a species with high mortality rate to local or even global extinction provided that it is co-infected with an abundant species. Such collapse-driven extinctions depend on factors different than those in the endemic steady state of the disease.

epidemiology↗

bioRxiv2017

Gestational Age At Birth And Risk Of Intellectual Disability Without A Common Genetic Cause: Findings From The Stockholm Youth Cohort

BackgroundPreterm birth is linked to intellectual disability and there is evidence to suggest post-term birth may also incur risk. However, these associations have not yet been investigated in the absence of common genetic causes of intellectual disability (where risk associated with late delivery may be preventable) or with methods allowing stronger causal inference from non-experimental data. We aimed to examine risk of intellectual disability without a common genetic cause across the entire range of gestation, using a matched-sibling design to account for unmeasured confounding by shared familial factors.\n\nMethods and FindingsWe conducted a population-based retrospective study using data from the Stockholm Youth Cohort (n=499,621) and examined associations in a nested cohort of matched siblings (n=8,034). Children born at non-optimal gestational duration (before/after 40 weeks 3 days) were at greater risk of intellectual disability. Risk was greatest among those born extremely early (adjusted OR24 weeks=14.54 [95% CI 11.46-18.44]), lessening with advancing gestational age toward term (aOR32 weeks=3.59 [3.22-4.01]; aOR37 weeks=1.50 [1.38-1.63]); aOR38 weeks=1.26 [1.16-1.37]; aOR39 weeks=1.10 [1.04-1.17]) and increasing with advancing gestational age post-term (aOR42 weeks=1.16 [1.08-1.25]; aOR42 weeks=1.41 [1.21-1.64]; aOR44 weeks=1.71 [1.34-2.18]; aOR45 weeks=2.07 [1.47-2.92]). Associations persisted in a nested cohort of matched outcome-discordant siblings suggesting they were robust against confounding from shared genetic or environmental traits, although there may have been residual confounding by unobserved non-shared characteristics. Risk of intellectual disability was greatest among children showing evidence of fetal growth restriction, especially when birth occurred before or after term.\n\nConclusionsBirth at non-optimal gestational duration may be linked causally with greater risk of intellectual disability. The mechanisms underlying these associations need to be elucidated as they will be relevant to clinical practice concerning elective delivery within the term period and the mitigation of risk in children who are born post-term.

epidemiology↗

bioRxiv2017

Cadmium-associated differential methylation throughout the placental genome: epigenome-wide association study of two US birth cohorts

BackgroundCadmium (Cd) is a ubiquitous toxicant that during pregnancy can impair fetal development. Cd sequesters in the placenta where it can impair placental function, impacting fetal development. We aimed to investigate Cd-associated variations in placental DNA methylation (DNAM), associations with gene expression, and identify novel pathways involved in Cd-associated reproductive toxicity.\n\nMethodsUsing placental DNAM and Cd concentrations in the New Hampshire Birth Cohort Study (NHBCS, n=343) and the Rhode Island Child Health Study (RICHS, n=141), we performed an EWAS between Cd and DNAM, adjusting for tissue heterogeneity using a reference-free method. Cohort-specific results were aggregated via inverse variance weighted fixed effects meta-analysis, and variably methylated CpGs were associated with gene expression. We then performed functional enrichment analysis and tests for associations between gene expression and birth metrics.\n\nResultsWe identified 17 Cd-associated differentially methylated CpG sites with meta-analysis p-values < 1e-05, two of which were within a 5% false discovery rate (FDR). Methylation levels at 9 of the 17 loci were associated with increased expression of 6 genes (5% FDR): TNFAIP2, EXOC3L4, GAS7, SREBF1, ACOT7, and RORA. Higher placental expression of TNFAIP2 and ACOT7, and lower expression of RORA, were associated with lower birth weight z-scores (p-values < 0.05).\n\nConclusionCd associated differential DNAM and corresponding DNAM-expression associations at these loci are involved in inflammatory signaling and cell growth. The expression levels of genes involved in inflammatory signaling (TNFAIP2, ACOT7, and RORA), were also associated with birth metrics, suggesting a role for inflammatory processes in Cd-associated reproductive toxicity.\n\nSignificanceCadmium is a toxic environmental pollutant that can impair fetal development. The mechanisms underlying this toxicity are unclear, though disrupted placental functions could play an important role. In this study we examined associations between cadmium concentrations and DNA methylation throughout the placental genome, across two US birth cohorts. We observed cadmium-associated differential methylation, and corresponding methylation-expression associations at genes involved in cellular growth processes and/or immune and inflammatory signaling. This study provides supporting evidence that disrupted placental epigenetic regulation of cellular growth and immune/inflammatory signaling could play a role in cadmium associated reproductive toxicity in human pregnancies.

epidemiology↗

bioRxiv2017

Assessing The Dynamics And Control Of Droplet- and Aerosol-Transmitted Influenza Using An Indoor Positioning System

There is increasing evidence that aerosol transmission is a major contributor to the spread of influenza. Despite this, virtually all studies assessing the dynamics and control of influenza assume that it is transmitted solely through direct contact and large droplets, requiring close physical proximity. Here, we use wireless sensors to measure simultaneously both the location and close proximity contacts in the population of a US high school. This dataset, highly resolved in space and time, allows us to model both droplet and aerosol transmission either in isolation or in combination. In particular, it allows us to computationally assess the effectiveness of overlooked mitigation strategies such as improved ventilation that are available in the case of aerosol transmission. While the effects of the type of transmission on disease outbreak dynamics appear to be weak, we find that good ventilation could be as effective in mitigating outbreaks as vaccinating the majority of the population. In simulations using empirical transmission levels observed in households, we find that bringing ventilation to recommended levels has the same mitigating effect as a vaccination coverage of 50% to 60%. Our results therefore suggest that improvements of ventilation in public spaces could be an important and easy-to-implement strategy supplementing vaccination efforts for effective control of influenza spread.

epidemiology↗