Dental caries and periodontitis account for a vast burden of morbidity and healthcare spending, yet their genetic basis remains largely uncharacterized. Here, we identify self-reported dental disease proxies which have similar underlying genetic contributions to clinical disease measures and then combine these in a genome-wide association study meta-analysis, identifying 47 novel and conditionally-independent risk loci for dental caries. We show that the heritability of dental caries is enriched for conserved genomic regions and partially overlapping with a range of complex traits including smoking, education, personality traits and metabolic measures. Using cardio-metabolic traits as an example in Mendelian randomization analysis, we estimate causal relationships and provide evidence suggesting that the processes contributing to dental caries may have undesirable downstream effects on health. Dental caries and periodontitis are among the most common medical conditions. Here, the authors report a GWAS for measures of oral health that reveals 47 risk loci for caries, find genetic correlation with 31 other complex traits and use Mendelian randomization analyses to explore potential causal relationships. Characterising the aetiology of these diseases is a priority as they confer major health2 and financial burden, with the global cost of dental diseases exceeding 540 billion US dollars in 20153. Part of this story is the genetic contribution to oral health outcomes and the heritability of dental caries and periodontitis have been reported to be as high as 50%5. However, the nature of this contribution remains poorly characterised despite the promise that increased understanding of genetic factors can bring with respect to aetiology dissection and theoretically, clinical managementThe 2016 Global Burden of Diseases, Injuries and Risk Factors Study7, specific presentations of disease and the presence or absence of disease in paediatric populations9. To date, few reliable genetic-association signals have been found, and this is likely to reflect different measurement approaches used, complex genetic architecture10 of dental caries or limited statistical power to detect associations. GWAS for periodontitis have investigated measures, including the presence or absence of disease11, quantitative measures of periodontal status12, severe presentations of disease13, molecular and microbial intermediaries of disease14 and composite phenotypes such as GWAS for principal components which aim to capture multiple facets of periodontal health15. These studies have not yielded consistent evidence of specific genetic contributions to periodontitis9.Genome-wide association studies (GWAS) for dental caries have investigated measures, including overall caries experience16. The presence of less well defined but informative phenotypes has enabled successful association signal discoveries for several complex traits, yielding important biological insights17. In order to achieve further understanding of genetic contributions to caries and periodontitis, a shift in analysis scale—afforded by a similar approach to measurement—is required.Currently, there is a trade-off between phenotypic refinement and obtaining valid phenotype data in sufficiently large cohorts to allow statistical power for genome-wide analyses. Given the logistical and economic challenges in obtaining detailed phenotypes in large populations, studies have focused on clinical outcomes indicating the presence or absence of manifest disease. Recent studies of other complex traits have taken a different approach and circumvented the limited availability of refined clinical phenotypes by taking advantage of extremely large, population-based, cohorts with both genetic data and less-refined proxy phenotypes. The UK Biobank (UKB), for example, includes information from approximately half a million participants18, which is a unique collection of epidemiological cohorts with detailed information on clinical endpoints of dental diseases; and UKB, which contains less-refined self-reported oral health data at a larger scale. In isolation, the biological meaning and relevance of the approximate measures in UKB would not be clear, but anchored against and unified with the more detailed clinical information in GLIDE, this combination of complementary resources provides a unique opportunity for genetic association discovery and application.Here, we synthesise evidence from two sources; the Gene-Lifestyle Interactions in Dental Endpoints (GLIDE) consortiumUsing this combination of resources, we identify 47 novel risk loci for dental caries and show that the heritability of dental caries is partially shared with a range of complex traits. Applied analysis using Mendelian randomisation suggests that dental caries has undesirable downstream effects on health. Together, these findings improve our understanding of the potential causes and consequences of an important complex disease.19  were undertaken within the GLIDE consortium, using clinical measures of dental diseases and imputed genotype data, accounting for age-specific, sex-specific and other study-specific covariates. The primary traits were measures of caries experience  and the sum of Decayed and Filled tooth Surfaces per available tooth Surface (DFSS)), number of teeth (Nteeth) and a dichotomous classification of periodontal health or disease Table . All metn = 461,031 for all traits; see the Methods section)In parallel, genetic contributions to self-reported measures of oral health were characterised in UK Biobank (UKB). Participants were asked to report whether they had bleeding gums, painful gums, dentures, loose teeth, toothache or mouth ulcers as part of a baseline study questionnaire. GWAS for each trait was performed within individuals of European ancestry, accounting for age, sex and relatedness using a linear mixed model (2LDSR) was estimated using univariate linkage-disequilibrium score regression (LDSR)20 (Methods). In GLIDE, the highest and lowest heritability estimates were reported for Nteeth  and periodontitis , respectively; while in UKB the highest and lowest heritability estimates were for dentures  and toothache , respectively -based heritability  were estimated using bivariate LDSR21 with an unconstrained intercept term to allow for sample overlap. For clinical measures within GLIDE, there were strong genetic correlations (Rg > 0.4 or Rg < −0.4) between DMFS and DFSS, DMFS and Nteeth and DFSS and Nteeth  . For periodontitis, the highest Rg value was seen for loose teeth (Rg~1); however, this was imprecisely estimated due to the low heritability of periodontitis .To guide interpretation of dental disease traits and identify those with similar genetic contributions, genetic correlations  and dentures ; the other combining periodontitis  and loose teeth . These analyses included ~8.9 million SNPs and insertion/deletions (INDELS) present in both GLIDE and UKB. There was evidence of a polygenic contribution to phenotype in both combined analyses with reasonable inflation given the nature of the traits and anticipated genetic architecture .Exploiting this shared heritability for gene discovery, single-variant association statistics from GLIDE and UKB were combined using a z-score genome-wide meta-analysis weighted by effective sample size. There were two principal analyses; one combining DMFS (P < 5 × 10−8) in the unconditional results and following a stepwise selection procedure  change in DMFS residuals, odds ratio [OR] for having dentures = 0.85 ). rs121908120 is a missense variant within WNT10A which results in a phenylalanine to isoleucine substitution and is predicted to have deleterious consequences in multiple WNT10A transcripts using the ExAC browser22. In a population of 28,691 adults aged 30–75 years who represent the Northern Swedish adult population with access to dental care, the estimated effect of the A allele corresponded to 2.1  fewer decayed, filled or missing tooth surfaces (Methods).The largest estimated per-allele effect of any variant in the combined analysis was observed for rs121908120, a low-frequency variant ), with an estimated effect corresponding to 1.2  additional decayed, missing or filled tooth surfaces per T allele. The lead variant lies within an uncharacterised protein-coding region, C5orf66, however, putative gene mapping using reference expression quantitative trait locus (eQTL) and chromatin interaction data implemented in FUMA23 highlighted 25 potential genes at this locus  to make comparison with published studies, 46/47 variants or proxies  were available in the PhenoScanner database, and 26 of these (57%) have previously reported association with one or more non-dental diseases or health traits, termed ‘overlaps’ in this description. Traits seen repeatedly in this overlap analysis include adiposity traits (11/26 overlaps), height (9/26 overlaps) and bone mineral density (3/26 overlaps). A summary is shown in Supplementary Table The remaining 45 genetic risk loci in the DMFS/dentures combined analysis include some investigated in candidate gene studies for dental caries, such as the Human Leucocyte Antigen (HLA) regionSIGLEC5, which was recently reported as a risk locus for aggressive periodontitis13 . Effect estimates in GLIDE and UKB were consistent at this lead locus, and there was also evidence for consistency in effect estimates at conditionally independent single variants passing an arbitrary threshold for suggestive association . In the DMFS/dentures, meta-analysis aggregate results were available for 15,522 transcripts. Of these, varying expression levels at 221 transcripts were predicted to influence the phenotype, including multiple HLA-region transcripts. Outside the HLA region, the strongest evidence was seen for CA12, located in the region of single-variant association signal at 15q22, (P = 2.8 × 10−17 in Z-test). CA12 encodes a member of the carbonic anhydrase family of zinc enzymes which catalyse the hydration of carbon dioxide to form bicarbonate and hydrogen ions to regulate pH. This family has several functions relevant to dental caries, including tooth formation, where multiple carbonic anhydrases are produced by maturation-stage ameloblasts27, salivary buffering, where defects in CA12 lead to poor salivary function and xerostomia28; and regulation of tooth biofilm microbiota, where CA6 may affect colonisation by the cariogenic microorganism Streptococcus mutans29. In the region of the lead single-variant signal in 5q31, the S-TissueXcan approach prioritised PITX1 as the most relevant transcript (P = 2.9 × 10−12). PITX1 encodes a developmentally expressed transcription factor with roles in skeletal and mandibular growth and tooth development, and deletion of the Pitx1 locus in animal models results in abnormal mandibular tooth morphology30. The results are given in Supplementary Data In an exploratory hypothesis-generating investigation, summary statistics from the two primary combined analyses and eQTL data were integrated using the S-PrediXcanSIGLEC5 was predicted to associate with increasing odds of periodontitis/loose teeth (P = 8.7 × 10−07). Full results are given in Supplementary Data In the periodontitis/loose teeth analysis, the same 15,222 transcripts were tested, but here only a single transcript was associated with the phenotype after correction for multiple testing. Increasing transcription of 31, which tests whether loci housing dental disease-associated single variants are over-represented in predefined sets of functionally related genes. For the DMFS/dentures analysis, there was no evidence for enrichment in gene sets passing an acceptable false discovery rate (Supplementary Data 23 using a hypergeometric test to test whether the transcripts prioritised by S-TissueXcan were over-represented in curated gene sets defined in the Molecular Signatures Database (MSigDB C2). No enrichment beyond chance was observed after correction for multiple testing for DMFS/dentures loci, and there were insufficient loci to perform this analysis for periodontitis/loose teeth.Gene set enrichment was assessed using DEPICT32 or in regions surrounding genes with tissue-specific expression patterns33. In the DMFS/dentures combined analysis, there was evidence for enrichment in 38/85 functional annotations including annotations providing evidence for evolutionary conservation. Treating Genomic Evolutionary Rate Profiling (GERP) scores as a continuous annotation, DMFS/dentures association signal was enriched in genomic regions under evolutionary constraint (P = 1.5 × 10−28 in Z-test for enrichment), while the 1.9% of variants annotated as highly conserved from primates to humans accounted for 30% of the heritability of DMFS/dentures  using HLA haplotype dosage as the exposure and ‘Dentures’ as the outcome. Ten haplotypes were associated with dentures, including haplotypes of HLA class I and class II. The strongest evidence for association was observed for DQB1_201, a common haplotype encoding the DQ-beta 1 chain of the HLA class II complex , P = 8.9 × 10−13 in χ2 test) . For the periodontitis/loose teeth analysis, effect estimates at the lead variant were obtained from a meta-analysis of independent studies within GLIDE of East Asian ancestry . There was no strong evidence for association at rs12461706 in this population , where the A allele is common (EAF = 0.96) compared with the European ancestry population.The composition of the samples in GLIDE affords an opportunity to assess heterogeneity across strata of ancestry or clinical status. To explore whether lead variants identified the DMFS/dentures combined analysis had effects driven by periodontal tooth loss, genetic effect sizes were estimated in individuals with or without periodontitis and contrasted (GLIDE only). There was little evidence for different effect sizes between groups  between oral disease traits and all available traits with genome-wide association data, excluding any GWAS results obtained solely in UKB (Methods). For DMFS/dentures combined analysis, positive genetic correlations were seen for smoking traits, for example ever vs. never smoked , adiposity traits, such as body mass index  and smoking-related diseases, such as lung cancer  and coronary artery disease . Negative genetic correlations were seen for longevity  and complex traits reflecting socio-demographics and cognition, in particular educational attainment   Fig. . For the40 approach for primary analysis. Treating DMFS/dentures as an exposure, a one standard deviation greater burden of dental disease  was nominally associated (P < 0.05) with greater waist-to-hip ratio  , higher plasma triglyceride levels ), increased odds of type 2 diabetes ) and increased odds of all stroke ). Of these findings, only waist-to-hip ratio and triglycerides survived a Bonferroni correction for multiple testing. The primary results are given in Table The genetic correlations between dental diseases and metabolic traits and cardiac outcomes suggest shared genetic contributions to the same biological underpinnings, but also can be due to pathway effects where dental diseases are a risk factor for health outcomes. To explore this, we undertook bidirectional two-sample Mendelian randomisation (MR) to estimate causal relationships between DMFS/dentures and a subset of traits reflecting metabolic and cardiovascular health, using the Generalized Summary Mendelian Randomisation (GSMR)) CI: 0.0, 0.13, hSensitivity analysis used alternative estimation tools to explore whether these findings were robust under different modelling assumptions  and fasting blood glucose were nominally associated with greater burden of dental disease, but only body mass index survived correction for multiple testing  for 1 KgM−2 greater BMI, with consistent effect estimates in sensitivity analysis  for 1 KgMThis investigation used detailed clinical measures in combination with genetically validated proxy phenotypes to investigate the two major dental diseases, caries and periodontitis.PITX1, CA12 and in the HLA region in addition to uncommon variation with large effects in WNT10A. Combined analysis of periodontitis and loose teeth (a late symptom of advanced periodontitis) confirmed association at a previously reported locus, SIGLEC5. Integration of GWAS results with external sources of expression data prioritised 221 gene transcripts which may be involved in the pathogenesis of dental caries, while integration with functional annotation data showed that heritability of dental caries was enriched in conserved genomic regions, with a fold-enrichment value similar to other complex traits with serious health consequences32. Cross-trait comparisons showed overlap in the genetic determinants of dental diseases and complex non-oral health traits at both a single-variant level and genome-wide level. Finally, using a Mendelian randomisation analysis framework, there was evidence suggesting that biological processes leading to dental caries may have downstream effects on general health.Combined analysis of DMFS and dentures identified 47 novel risk loci, including common variation near 41, but here we extend this approach to the selection of disease proxies where the prior expectation is less clear. This workflow may be adaptable to other complex diseases where it is difficult to obtain detailed phenotypic information in large collections.This investigation used an empirical approach informed by shared heritability to select dental disease proxy measures with similar biological meaning to detailed clinical measures. This approach has similarities to a recent investigation which used genetic correlation for post hoc confirmation of a prior expectation that family history of Alzheimer’s disease is a satisfactory proxy of clinical diagnosisWNT10A, the locus harbouring the variant with the largest associated effect in the DMFS/dentures analysis, encodes a member of the WNT/β-catenin family of signalling proteins which have documented roles in inducing and regulating tooth formation in animal models44 in addition to their widely known functions in embryological patterning and oncogenesis. In humans, WNT10A mutations have been reported to cause isolated defects in tooth number45 and quality46 and to regulate the cusp architecture and other morphological characteristics of teeth47. Genes encoding other proteins in the WNT signalling cascade (but not WNT10A) were identified as candidates in an early GWAS for dental caries with some sample overlap with this study6. Other examples with plausible biological relevance, including HLA, CA12 and PITX1, are flagged in the results.At a single-variant level, the associated loci in this study may provide insight into the biological processes that are relevant to dental diseases. As an example, These genetic associations improve disease understanding and may provide a foundation for innovative approaches to risk assessment, outcome prediction, disease management or treatment. The availability of genetic proxies for dental diseases in large data sets also unlocks previously unavailable approaches, such as two-sample MR to infer potential consequences of dental diseases. As an illustrative example, the MR analysis included in this work provides some support for the hypothesis that dental diseases proxied by the DMFS/dentures may be an upstream risk factor for metabolic disturbance and cardiovascular disease events and prioritises specific relationships for additional investigation. This analysis also provides a broader demonstration of the utility of these data for generating and testing research hypotheses.48. This might be due to heterogeneity introduced by the different approaches to disease classification, different patterns of periodontal treatment and varying distributions of age in the GLIDE cohorts or gene–environment interactions not accounted for in the study design. Here, DMFS/dentures is described as a measure of dental caries. This measure might capture some variation in periodontal status, as periodontitis is a major cause of tooth loss49. Conversely, we note that the SIGLEC5 periodontitis risk locus is not a main finding for DMFS/dentures and that there is little evidence for heterogeneity in DMFS effect sizes between periodontal cases and controls, supporting the idea that the two primary meta-analyses capture distinct dental diseases.The dental traits examined in this study appeared moderately heritable, except for periodontitis where the quantifiable heritable signal was much lower than estimates reported in the literatureThe combination of genetically similar but non-identical pairs of phenotypes creates challenges in harmonising effect sizes, which we addressed using standardised regression coefficients, allowing valid comparison of the relative magnitude of genetic or causal effect estimates and valid inference about the probability of a non-zero effect. Indicative estimates on a tooth surface scale are also provided, however, these rely on assumptions about the variance in DMFS scores in any given population and should be interpreted with caution.50, they are limited by the quality and availability of the external data, for example the data on odontoblast or ameloblast tissue are not available in GTEx. Cross-trait comparisons of dental diseases with other traits at single-variant level are only possible when GWAS results are available for any given trait, and well-powered investigations are likely to report more associations than small studies. Together, this means that the list of observed overlaps between dental diseases and other traits will be biased towards well-investigated traits and outcomes.GWAS results were explored in follow-up analyses using approaches which exploit external sources of information, including gene expression data. While these approaches maximise value from GWAS and improve statistical power to identify relevant genes51 or confounded if both the exposure and outcome are influenced by a latent shared trait with genetic determinants52. The different approaches to detect and account for horizontal pleiotropy used in this study yielded similar causal effect estimates; however, lack of precision in these estimates may have masked important differences or evidence for horizontal pleiotropy which will only emerge in future experiments with greater statistical power. Finally, the non-specific-nature of the DMFS/dentures phenotype may capture a range of latent treats upstream of clinically manifest disease and tooth loss due to periodontitis, meaning that the downstream effects of DMFS/dentures might involve a wide range of potential mechanisms or mediators.Causal effect estimates in MR experiments may be biased by unaddressed horizontal pleiotropyIn summary, this study leveraged self-reported dental disease proxies and clinical disease measures in meta-analysis to identify novel risk loci for dental caries. Characterising the functional biology at these loci may provide insight to improve diagnosis or guide the development of new therapeutic approaches targeting the most prevalent global disease. At a single-variant and whole-genome level, the heritability of dental caries partially overlaps with other complex traits and diseases, arguing against the notion that dental diseases can be diagnosed, managed or researched in isolation. Finally, the results of MR analysis support the idea that population-level interventions to reduce the burden of dental diseases may have benefits for population health more generally.Each contributing study obtained informed consent from all study participants. This study complied with all relevant ethical regulations, including the Declaration of Helsinki, and ethical approval for data collection and analysis was obtained by each study from local boards as described in Supplementary Data The contributing studies were 1) Atherosclerosis Risk in Communities (ARIC); 2) The Center for Oral Health in Appalachia cohort 1 (COHRA1), which is part of the GENEVA caries consortium; (3) the Dental Registry and DNA Repository of the University of Pittsburgh School of Dental Medicine, (DRDR), also part of the GENEVA caries consortium; (4) the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); (5) the Malmö Diet and Cancer Study (MDC); 6) the Northern Finland Birth Cohort 1966 (NFBC 1966); (7) the Study of Health in Pomerania (SHIP), (8) the Study of Health in Pomerania Trend (SHIP Trend); (9) TWINGENE, which is a genotyped epidemiological study recruited from the Swedish Twin Registry (TWINGENE); (10) the Women’s Genome Health Study (WGHS); (11) Biobank Japan (BBJ) and (12) Tokyo Medical and Dental University Aggressive Periodontitis Study (TMDUAGP). A detailed description of each study is included in . In one study (HCHS/SOL), participants were recruited from Hispanic and Latino communities in the USA, who self-reported ancestry from six broad groups . To undertake analyses within this highly admixed population, a bespoke modelling approach was undertaken. Multi-dimensional clustering was used to generate genetic analysis groups containing participants of similar ancestry. These group allocations were then used as covariates in a linear mixed model  alongside the first five genetic principal components, study center and log-transformed sampling weightsFor periodontitis only, there were two studies with participants of East Asian ancestry , totalling 17,287 participants. For periodontitis, separate meta-analyses were performed for studies of European ancestry and studies of East Asian ancestry.Dental records used to calculate DMFS, DFSS and Nteeth were either obtained by a trained assessor as part of the study protocol, or from index linkage to records completed by a dental professional in primary care (MDC and TWINGENE). The examination protocols used by each study are described in Supplementary Data Nteeth was obtained by counting the number of remaining natural permanent teeth . This was derived from records of clinical dental examination for all studies apart from WGHS, where participants were asked to self-report this information. Participants were asked whether they had lost any teeth and, if so, asked to specify the number of teeth lost.54 were used. In COHRA1, participants were classified as cases if two or more sextants had probing depth of at least 5.5 mm, or if participants reported ever having ‘gum surgery'. In TwinGene and MDC, participants were classified as cases if at least two tooth surfaces had probing depth of 5 mm or deeper, or at least four tooth surfaces had probing depth of 4 mm or deeper. In BBJ, participants were classified as cases or controls based on clinical diagnosis by physicians at participating hospitals, with data retrieved from diagnosis codes in hospital registers. In TMDUAGP, the participants were classified as cases based on the classification developed at the 1999 international workshop for a classification of periodontal disease and conditions55. In WGHS, the participants reported if they had periodontal disease or not. The question stems were ‘Since you started the trial (around 3 years ago)/In the past year, were you newly diagnosed with/have you had any of the following', with ‘Periodontal disease' as one possible response. Participants who selected this response were asked to provide the month and year of diagnosis. Participants with no teeth were excluded from scoring the primary oral health traits in GLIDE.For periodontal status, participants were classified as having (cases) or not having (reference) clinical symptoms of periodontitis, using definitions applied by each participating cohort. In ARIC, SHIP, SHIP-Trend and HCHS/SOL, criteria published by the Centers for Disease Control and Prevention/American Academy of Periodontology (CDC/AAP)56 (1000 Genomes project (1kGp) phase 1 version 3 (March 2012) release for all studies apart from COHRA, which used the 1000 Genomes project phase 1 version 2 release).Genotyping was performed using commercially available arrays , derived variables were created to account for major covariates. Raw phenotype counts were regressed on age, age squared, genetic principal components and other study-specific covariates as described in Supplementary Data 57. Variants were excluded if they had low imputation quality , departed from Hardy–Weinberg equilibrium (PHWE < 10−6 in the entire sample for continuous traits or in controls for periodontitis), or had per-file minor allele count <6. Directly genotyped SNPs with poor call rate (<95%) were also excluded. Association statistics within each study were corrected using genomic control inflation factor (max λGC = 1.07).In addition to study-specific measures, central QC of the association result files was performed using EasyQC software and a previously published protocol19.Fixed effect inverse-variance weighted meta-analyses were performed using METAL software58. The HCHS/SOL study contains participants of Latino/Hispanic ancestry. To assess for ancestry-related heterogeneity, meta-analyses in GLIDE were repeated, excluding HCHS/SOL, and tests for heterogeneity were performed between these results and results from HCHS/SOL for the lead SNPs, again using EasyStrata.For lead associated variants, DMFS effect sizes were compared between periodontitis cases and controls in stratified meta-analysis. Tests for difference in effect size were performed using the CALCPDIFF function of EasyStrataWhere available, genotype data for chromosome X were analysed. Haploid allele calls for male participants were coded as 0 or 2. Genotypes for female participants were coded as 0, 1 or 2 under the additive genetic model. Summary statistics from the participating studies were combined using fixed effects, inverse-variance weighted meta-analyses following the same workflow described for autosomal results.16.UK Biobank is a population-based health research resource consisting of ~500,000 people, aged between 40 and 69 years, who were recruited between the years 2006 and 2010 from densely populated regions of England, Scotland and Wales16. Single-variant analysis used the 2018 (v3) imputed data release including imputation to both Haplotype Reference Consortium and UK10K/1000 genomes combined panel. Additional QC of the imputed data was performed at the University of Bristol. Participant-level QC involved restricting analysis to participants of European ancestry  as well as standard exclusions for mismatch between reported and genetic sex, possible sex chromosome aneuploidy, outliers in heterozygosity and missing rates. An additional two participants were removed as they were apparently related to a very large number of participants at 3rd degree or closer; otherwise related participants passing all other quality control were included in single-variant analysis59. For HLA haplotype analysis, imputation of classical HLA haplotypes was performed using the HLA*IMP:02 algorithm with a multi-population reference panel16 and analysis was restricted to unrelated participants who self-identified as ‘White British’ and were located within the largest cluster in k-means analysis.Participants in UKB were genotyped using the UK BiLEVE and UK Biobank axiom array '. The possible answers included ‘Dentures', ‘Bleeding gums', ‘Painful gums', ‘Loose teeth', ‘Toothache' or ‘Ulcers'. Participants who selected one of these answers were coded as cases for each respective analysis. Participants who did not select this answer were coded as reference. GWAS included the following number of cases; dentures: 60. Age, age squared, sex and genotyping array were included as covariates in association testing. BOLT-LMM association statistics on a linear scale were transformed to log odds ratios and their corresponding 95% confidence intervals on the liability scale using a Taylor transformation expansion series as detailed in a full description of the GWAS pipeline which has been published online61. The association statistics were corrected using the estimated intercept term from univariate LDSR20  prior to meta-analysis with GLIDE.GWAS were performed using a linear mixed model (LMM) implemented in BOLT-LMM (v2.3)20 was used to estimate heritability attributable to common genetic variants (h2LDSR). Scripts are available at (https://github.com/bulik/ldsc). Pre-computed reference LD scores and weights derived from 1000 Genomes European ancestry data were downloaded from . In GLIDE, summary statistics from the primary meta-analysis for each trait were used. A subset of high-confidence SNPs  were used to minimise bias related to imputation accuracy. Summary statistics for each phenotype were first re-formatted with the munge_sumstats.py python script and then heritability was estimated using the–h2 option of ldsc.py.Univariate LDSRg) for all pairs of traits between GLIDE and UKB were estimated using the–rg option of ldsc.py script (https://github.com/bulik/ldsc), and files were prepared using the same criteria described above. To estimate Rg with a range of publicly available GWAS summary statistics, the prepared files for dental traits were uploaded to the LD hub39 resource (ldsc.broadinstitute.org) using all available traits with genome-wide data available on 9th January 2019, apart from those obtained solely in UKB. The logical maximum and minimum values of Rg are +1 and −1, however, the mathematical derivation used by LDSC can occasionally create values >+1 or <−1, which should be interpreted as values lying near +1 or −1, respectively.Genome-wide genetic correlations . Segmented LDSR using tissue-specific annotations was performed using the –h2-cts flag and multi-tissue gene expression files derived using 1000 Genome phase 3 data (April 2018 release).19. The contributions of GLIDE and UKB were weighted by sample size for continuous traits (DMFS) and by effective sample size for binary traits . The effective sample size was estimated from the number of cases and number of controls using the formula recommended by METAL’s authors19.Combined two-way meta-analysis of association results between GLIDE and UKB was performed using the fixed effects z-score method implemented in METALP < 5 × 10−8. Within any given genomic locus, the lead SNP was defined as the variant with the lowest association P-value within a+/− 500-kb distance, using EasyStrata58. To test for conditional independence of lead variants, a stepwise selection procedure was performed using approximate conditional analysis62, implemented using the cojo-slct function of GCTA (version 1.91.4)63. Loci were only considered functionally independent if at least one variant reaching genome-wide significance was selected in that risk locus during this procedure. For the HLA region (chr6: 25–35 Mb), the broad association signal and complex LD structure prevented testing for conditional independence between variants, so only a single lead variant was reported for this region. Where more than one conditionally independent variant was selected within a single-risk locus, the lead variant was presented in Table Genome-wide significance was set at To understand the relative size of genetic effects for variants in the Z-score combined analysis, beta coefficients and corresponding standard errors were derived using a transformation described in Supplementary Note Standardised regression coefficients in combined analysis were transformed to provide indicative effect estimates in a clinically interpretable scale of affected tooth surfaces or log odds of disease. The transformation is described in Supplementary Note P < 1 × 10−5) in the combined analysis were used to test for correlation in effect sizes.Directional consistency of effects for lead in combined meta-analysis of GLIDE and UKB data was assessed by counting the number of directionally consistent SNPs between the GLIDE and UKB data sets. Correlation in effect sizes was assessed by calculating Pearson correlation coefficient weighted by inverse variance (1/SE) in the GLIDE meta-analysis. For periodontitis/loose teeth, there was only a single risk locus, therefore independent suggestively-associated single variants (http://www.phenoscanner.medschl.cam.ac.uk/phenoscanner), an online curated database of publicly available GWAS summary statistics results. The results were retrieved for variants identified in combined analyses and their proxies . If variants had previously been associated with a non-dental disease trait (P < 5 × 10−8 in GWAS), then details of the traits, association test statistics and publication references were retrieved.Cross-trait analysis of single variants was performed using PhenoScanner , was used to test whether associated loci are preferentially located within predefined functionally similar gene sets, assessed against a null expectation informed by GWAS results for randomly distributed phenotypes. Associated loci were defined at (P < 5 × 10−8) in combined analysis. Reconstituted gene sets, tissue expression matrix and gene annotation files were downloaded from the DEPICT repository (data.broadinstitute.org/mgp/depict/documentation).DEPICT23. Associated genes were defined as those passing Bonferroni correction in S-TissueXcan analysis. Pathways and gene sets were taken from the Molecular Signatures Database (MSigDB C2), and all protein-coding genes in the FUMA database were used as background. Enrichment P-values were corrected for multiple testing using Bonferroni correction.A hypergeometric test for gene set enrichment was performed using FUMA25 web pipeline (https://cloud.hakyimlab.org/). Gene-level mediating effects of expression levels using were estimated using the summary GWAS association results and pre-fitted elastic net prediction models of gene expression levels in the 48 GTEx tissues26, which are available online (http://predictdb.org/). Following this, multi-tissue results were aggregated using the S-TissueXcan64 pipeline and post-processing pipeline (both hosted at (https://cloud.hakyimlab.org/). A Bonferroni correction was applied to account for the number of gene transcripts tested.Summary results from the combined meta-analyses were uploaded to the S-PrediXcan23. eQTL mapping included data on cis-eQTLs (up to 1MB between SNP and gene) from all available tissues in GTEx v6 and v7. Chromatin interaction mapping included 21 tissues with HiC data and enhancer/promoter regions defined in Roadmap 111 epigenomes. By default, sites 250 bp upstream to and 500 bp downstream from transcription factor start sites were considered promoter region windows.Associated single variants were mapped to candidate genes using the ‘SNP2GENE’ function in the online functional annotation tool FUMA40 (GSMR), implemented in GCTA (v1.92.0). Compared with other summary-statistic based estimators, GSMR is reported to have greater statistical power because GSMR uses genome-wide data to account for sampling variance in SNP-exposure and SNP-outcome estimates40.Primary analysis was performed using Generalized Summary Mendelian Randomisation65; for waist-to-hip ratio adjusted for BMI; GIANT consortium66, for coronary artery disease CARDIOGRAM plus C4D meta-analysis67; for stroke the MEGASTROKE consortium68; for type 2 diabetes, the DIAGRAM consortium69; for fasting glucose the ENGAGE consortium70; for HDL cholesterol, LDL cholesterol and triglycerides, the GLGC data sets were used71.Genome-wide summary statistics for seven metabolic traits and two cardiovascular outcomes were selected as follows: BMI; meta-analysis of GIANT with UK BiobankP < 5 × 10−8) after LD clumping using reference data from the cohorts arm of the UK10K project (https://www.uk10k.org/data.html) to produce index SNPs  were included as potential instrumental variables. No attempt was made to manually screen variants for possible undesirable pleiotropic effects, with filtering instead performed as part of the HEIDI-outlier procedure.To achieve adequate variance explained and therefore statistical power, multiple SNPs were included as instrumental variables for all traits. All variants associated with dental disease or metabolic traits  estimated from a non-outlying genetic instrumental variable, and tests whether other single nucleotide polymorphisms (SNPs) have values of βxy compatible with this estimate, on the assumption that pleiotropic variants will have outlying values40. Following default criteria, potentially outlying variants with (P < 0.01 for pleiotropy) were removed and βxy was estimated from the remaining instruments.HEIDI-outlier filtering, is an extension of the heterogeneity in dependent instruments methodIn the primary analysis, variants in the HLA region (chr6: 25–35 Mb) were removed for estimation of casual effects of DMFS/dentures, except for a single-lead variant. For estimation of causal effects of other traits on DMFS/dentures, full genome-wide data were used.Methods used for sensitivity analysis are described in Supplementary Note Further information on research design is available in the Peer Review FileSupplementary InformationDescription of Additional Supplementary FilesSupplementary Dataset 1Supplementary Dataset 2Supplementary Dataset 3Supplementary Dataset 4Supplementary Dataset 5Supplementary Dataset 6Supplementary Dataset 7Supplementary Dataset 8Supplementary Dataset 9Supplementary Dataset 10Supplementary Dataset 11Supplementary Dataset 12Supplementary Dataset 13Supplementary Dataset 14Supplementary Dataset 15Reporting Summary


BackgroundIntravenous (IV) tissue plasminogen activator (rt-PA) is a proven therapy for stroke in the acute treatment window. Recent published data has shown efﬁcacy for embolectomy for acute ischemic strokes within up to six, 16 and 24 hours in the anterior circulation but there is no guideline for optimal therapy for patients with posterior circulation stroke, specifically basilar artery occlusion (BAO) outside the standard IV rt-PA treatment window.AimTo evaluate differences in outcomes between maximal medical treatment versus thrombectomy in BAO.MethodWe retrospectively evaluated prospectively collected acute stroke code patients from our stroke registry from 7/2004 to 7/2016. Patients who received IV rt-PA were excluded. Patients with evidence of posterior circulation ischemia and a hyper dense artery sign on initial non-contrast CT were included as a surrogate for direct vessel data before 2014. Patients after 9/2014 were selected by evidence of BAO on vessel imaging. All patients were categorized either as endovascular therapy or standard medical treatment alone. Demographics, hospital discharge location and Modified Rankin Scale (mRS) at 90 days were compared. Two-sample t-test and Fisher’s exact test compared continuous and categorical variables across groups respectively.ResultsA total of 18 patients were included . There were no significant differences in demographic data . Results for outcome and efficacies showed no statistical difference between medical management and endovascular intervention for functional outcome mRS (0-3) at 90 days (p = 0.2) and discharge location of home/inpatient rehabilitation vs other locations (p = 0.52).ConclusionsOur single-center review showed the expected transition from predominantly medically treated posterior circulation BAOs, to a mixed pattern including embolectomy. Although the sample size was small, this study also illustrates the lack of clear efficacy data for optimal treatment strategies, and the ongoing treatment challenges in posterior circulation stroke population in a population of patients outside the rt-PA window. Stroke is the fifth leading cause of death and disability in the United States. Posterior circulation stroke accounts for twenty percent of all ischemic strokes . The basA posterior circulation stroke, especially basilar artery occlusion (BAO), has a devastating and extremely high mortality rate (80%) -5. Most Current evidence based on randomized controlled trial data has resulted in the Food and Drug Administration (FDA) approval for intravenous (IV) recombinant tissue plasminogen activator (rt-PA) within three hours from stroke symptom onset while mechanical embolectomy now has evidentiary support for zero to six hour cases and a specific subset of patient’s out to 24 hours -8. AlthoConsidering the potentially devastating consequences of this type of stroke, optimized treatment strategies should be determined. Our aim was to first assess current treatment patterns and relative outcomes for posterior circulation occlusions, as an initial step toward determining future optimal treatment paradigms  in posterior circulation large vessel occlusions (LVOs).We retrospectively evaluated prospectively collected acute stroke code patients’ registry data from our center’s institutional review board (IRB) approved datasets; Core C (CC), from July 2004 to September 2014, and Stroke Registry (SR) from October 2014 to July 2016.Patients who received IV rt-PA were excluded from analyses to assess the effect of medical therapy vs. embolectomy in a clean dataset. Since in our early registry (CC) direct vessel imaging data was not collected, surrogate ascertainment of basilar occlusion was defined by cases with registry documentation of both radiographic evidence of ischemia in the posterior circulation  and the presence of a hyper dense artery sign on initial non-contrast brain CT imaging. This data was combined with the subsequent, more refined, registry (SR) which did include direct documentation of basilar artery occlusion on vessel imaging (CT Angiogram [CTA] or MR Angiogram [MRA]). Patients were then categorized by whether they received endovascular therapy  or standard medical treatment (antiplatelet or anticoagulant therapy), and the two groups were compared.Baseline characteristics including age, gender, race, ethnicity, history of diabetes, history of hypertension, blood pressure, history of atrial fibrillation, history of coronary artery disease (CAD), history of smoking or drinking alcohol and initial National institute of Health Stroke Scale (NIHSS) were compared. Functional outcome variables included both hospital discharge location and Modified Rankin Scale (mRS) at 90 days. Good outcomes were defined as hospital location of home or acute rehab, and an mRS of 0 to 3 at 90 days . Safety A total of 18 stroke code patients with vertebra-basilar occlusion who were outside of standard IV rt-PA consideration were included in our assessment. In our data, 15 received medical therapy while three underwent posterior circulation embolectomy. There were no statistically significant differences in demographic data including age, gender, race, ethnicity, blood pressure, diabetes mellitus, hypertension, atrial fibrillation, tobacco use, alcohol use and initial NIH Stroke Scale Score (NIHSS). Median NIHSS score was not different between groups (p = 0.74) , good outcome was not different for mRS p = 0.20) (Table 0 (Table There was no difference in discharge location between groups (p = 0.52) Table .This exploratory assessment sought to determine current treatment strategies for posterior circulation occlusions (BAOs) outside of the standard IV rt-PA window, prior to a more prospective assessment of standardized treatment options.Our single center experience showed the expected transition from predominantly medically treated posterior circulation BAOs, to a more mixed pattern including embolectomy over time. This is in keeping with the evolution of evidence from landmark trials supporting the use of embolectomy for LVOs. The fact that the majority of patients were treated medically overall is consistent with the lack of evidence for embolectomy before the publication of multiple positive embolectomy trials since 2014 -8,11. AlWe did not find a difference in 90-day outcomes for either modality of treatment. This is likely at least partially due to small sample size, and a future, larger study would also utilize multivariate analysis. Nevertheless this study does illustrate the lack of clear efficacy data for optimal treatment strategies in BAOs or posterior circulation LVOs, and the ongoing treatment challenges in these populations.Our choice to exclude IV rt-PA patients may have lessened the sample size further. Nevertheless, it provided a clean study population and helped assess our goal of determining best therapy for patients outside of the standard IV rt-PA treatment window, a common clinical situation. A recent small retrospective demonstrated possible improved outcomes in BAOs that required delayed thrombectomy . Other nThere is great need in the literature to determine the current environment of treatment options and relative outcome. The current literature suffers from small numbers of patients being reported, in part because of the devastating nature of the disease and difficulty in enrollment into these types of trials. The largest prospective cohort for BAO (BASIC Study) evaluated different treatment intervals within the modality, but time to treatment was not recorded for medical therapy and this modality was not compared to thrombectomy . A recenUltimately, at this time, there is limited evidence to strongly support aggressive treatment strategy in posterior circulation LVO patients such as BAOs outside the rt-PA window, and further prospective, large trial assessments are warranted.Our data was able to assess current treatment strategies and adds to the overall limited data set on posterior LVOs outside of the rt-PA window. We did not find a difference in outcomes related to modality studied, with the caveat of small sample size and limited power. Our present analysis illustrates the ongoing treatment challenges in posterior circulation LVOs in general and specifically in BAOs. There continues to be a need for further investigation in larger sample sizes, and in the setting of prospective randomized clinical trials.


Preterm premature rupture of membranes (PPROM) is the leading identifiable cause of preterm birth, a complication that is more common in African Americans. Attempts to identify genetic loci associated with preterm birth using genome-wide association studies (GWAS) have only been successful with large numbers of cases and controls, and there has yet to be a convincing genetic association to explain racial/ethnic disparities. Indeed, the search for ancestry-specific variants associated with preterm birth has led to the conclusion that spontaneous preterm birth could be the consequence of multiple rare variants. The hypothesis that preterm birth is due to rare genetic variants that would go undetected in standard GWAS has been explored in the present study. The detection and validation of these rare variants present challenges because of the low allele frequency. However, some success in the identification of fetal loci/genes associated with preterm birth using whole genome sequencing and whole exome sequencing (WES) has recently been reported. While encouraging, this is currently an expensive technology, and methods to leverage the sequencing data to quickly identify and cost-effectively validate variants are needed.We developed a WES data analysis strategy based on neonatal genomic DNA from PPROM cases and term controls that was unencumbered by preselection of candidate genes, and capable of identifying variants in African Americans worthy of focused evaluation to establish statistically significant associations.DEFB1 and MBL2 genes that encode anti-microbial proteins that presumably defend the fetal membranes from infectious agents. Our approach also enabled us to rule out a likely contribution of a predicted damaging nonsense variant in the METTL7B gene.We describe this approach and the identification of damaging nonsense variants of African ancestry in the Our findings support the notion that multiple rare population-specific variants in the fetal genome contribute to preterm birth associated with PPROM.The online version of this article (10.1186/s12881-018-0696-4) contains supplementary material, which is available to authorized users. There are significant disparities in preterm birth rates in the United States, with African Americans experiencing an increased burden , 2. DeliTwin studies have revealed that both fetal and maternal genetic factors contribute to gestational age at delivery, but there is uncertainty about the roles played by specific fetal and maternal genes. Attempts to identify genetic loci associated with gestational age at delivery and preterm birth using genome-wide association studies (GWAS) have only been successful with large numbers of cases and controls  has recently been reported –9. WhileWe recently pursued the approach of searching for rare variants in fetal genes that could contribute to risk of PPROM, employing WES to identify the burden of damaging mutations in African-American fetal  samples , 9. In oDEFB1 and MBL2 nonsense variants (188 PPROM cases and 175 term controls) have been previously described [METTL7B SNPs were evaluated with the WES cohort. They were neonates born of self-reported African-American women. Term controls consisted of neonates born from uncomplicated singleton pregnancies (> 37 weeks gestation). PPROM cases were from singleton pregnancies prior to 37 weeks of completed gestation. The diagnosis of membrane rupture was based on pooling of amniotic fluid in the vagina, amniotic fluid ferning patterns and a positive nitrazine test. Women with multiple gestations, fetal anomalies, trauma, connective tissue diseases and medical complications of pregnancy requiring induction of labor were excluded as previously described [The subjects in the discovery WES (76 PPROM cases and 43 term controls) and initial confirmatory targeted genotyping for escribed . The METescribed .DEFB1 and MBL2 nonsense variants included the WES cohort and initial confirmatory targeted genotyping cohort described above [METTL7B SNPs were evaluated with the original WES cohort. In addition, we performed targeted genotyping for the DEFB1 and MBL2 nonsense variants on 119 PPROM cases and 199 controls not previously reported. The subjects were recruited from the same populations as the previously reported cohorts using identical inclusion and exclusion criteria. Ninety-four of these PPROM cases and 94 term controls were used for genotyping METTL7B SNPs.The previously published analysis of the ed above . In the METTL7B genotyping are presented in Additional file The methods used for WES (50-100X coverage) and analysis of the sequencing data have been described in detail in previous publications , 9. With+/− S.D.; West African ancestry: PPROM cases: 0.695 +/− 0.073 (mean + S.D.); Term controls 0.698 +/− 0.087 (p > 0.10)) [To reduce the potential risk that population stratification biased the genetic association tests, the percent African ancestry of the PPROM neonates and term control neonates was determined using ancestry-informative markers as previously described , 9. No sDetection of DEFB1 and METTL7B transcripts in fetal membrane RNA (1 μg) was accomplished by PCR as previously described . The prihttp://gnomad.broadinstitute.org/); 4) Determine whether the variant/mutation is of African ancestry using a public database (gnomAD); 5) Determine whether the gene is under selective pressure, consistent with an essential role in a biological or pathophysiological process, by a literature review (PubMed: https://www.ncbi.nlm.nih.gov/pubmed/); 6) Assess whether heterozygous variants could potentially cause a biological effect by altering the expression level or activity of mature protein; 7) Determine whether the gene harboring the nonsense variant is expressed in fetal membranes; 8) Evaluate whether the gene could play a role in the existing pathophysiological concepts of PPROM from the literature; and 9) Conduct follow-up genotyping of the nonsense variant in independent cohorts to test the association of the identified variant with PPROM.We developed the following simple screening method for analyzing the WES data: 1) Identify predicted damaging nonsense variants (gnomAD “high confidence”) present only in PPROM cases in the WES discovery panel; 2) Validate the nonsense variants by Sanger sequencing; 3) Verify it is a rare variant  based on the genome aggregation database  a, p value of < 0.017 would be considered the threshold for statistical significance, which was met for the DEFB1 and MBL2 nonsense variants studied.Associations were examined for statistical significance using Fisher’s Exact test (1-tailed) to determine whether the nonsense variant was overrepresented in PPROM cases. Nominal We detected more than 800 different nonsense variants  in the discovery WES sample of PPROM cases and term controls, approximately 33% of which were unique to PPROM, the majority of which occurred in only one PPROM case, and 30% of the variant types were unique to term controls, with the majority occurring in one term control Table  The remaDEFB1) gene, which encodes a small cysteine-rich cationic peptide that damages the cellular membranes of bacteria and some viruses, was found in PPROM cases in our initial WES and targeted genotyping [DEFB1 in our WES. DEFB1 is expressed by the fetal membranes [A heterozygous nonsense variant rs5743490) of African ancestry in the Defensin Beta 1 , which creates a stop codon; and G/A (Latino ancestry), which produces a synonymous amino acid change. We verified by Sanger sequencing that the minor allele of rs5743490 that we detected encoded a stop codon [DEFB1 nonsense variant truncates the DEFB1 protein 4 amino acids into the mature peptide amino acid sequence so that no functional DEFB1 would be made [The  be made . HoweverDEFB1 nonsense mutation, yielding more nonsense mutations in PPROM cases, including a neonate with a homozygous DEFB1 nonsense variant, and only one mutant allele in a term control .An additional 115 PPROM cases and 191 controls were subsequently genotyped for the ol Table . A statiol Table   (Table We discovered another rare nonsense variant of African ancestry rs74754826) in the  defense . It was 6 in the METTL7B) gene in the WES discovery panel in PPROM cases, and none in term controls. This was the largest number of unique “PPROM mutation alleles”. METTL7B transcripts were detected in human placenta and amnion by PCR with sequence verification of the amplicon  adjacent to rs115687886 that is in phase modifies the codon to create a benign missense variant (p.Arg224Leu). Subjects with both rs115687886 and rs146636131 minor alleles were considered to have the missense variant rather than the nonsense mutation  and another (G/A), which encodes a predicted damaging variant of South Asian ancestry.A 7B SNP rs46636131 ant p.Arg24Leu. SuMETTL7B SNPs of interest on 94 PPROM cases and 94 term controls detected the nonsense variant in term controls, including a homozygote mutant. Statistical analysis of the combined analysis WES data and follow-up genotyping revealed no statistically significant association of the METTL7B rs115687886 nonsense mutation with PPROM  in 19 PPROM cases, including 1 homozygote , and 5 term controls, including 1 homozygote. A start-loss variant detected in DEFB128 (rs145944118) was found in one PPROM case, and another start-loss variant (rs18818350) was detected in DEFB132 in one term control. The functional significance of these variants and their relationship to preterm birth are currently unknown.The discovery that the MBL2, and PPROM. This association is consistent with the work of others who examined common MBL2 polymorphisms in fetal DNA from European populations and found increased risk of preterm birth [We discovered a significant association between a nonsense variant in an anti-microbial gene, rm birth , 14. MBLDEFB1 and MBL2 nonsense variants, the nonsense variant (rs115687886) in the METTL7B gene did not stand up to further scrutiny as a PPROM candidate. METTL7B encodes a putative methyltransferase whose transcript is elevated in blood leukocytes in the context of infection in pregnancy, providing a potential link to PPROM mechanisms [In contrast to our findings with the riant rs1687886 inMETTL7B rs115687886 minor allele (in the absence of the adjacent in phase SNP) truncates the protein at amino acid position 224 of the 244-amino acid protein. This truncation is outside of the methyltransferase domain (amino acids 75–172). The functional significance of this protein truncation has not been established to the best of our knowledge, which could make the mutation “ineligible” in our screening criteria. Moreover, the rs115687886 minor allele frequencies in our African-American term controls and PPROM cases are relatively high , found in both a PPROM case and a term control, truncates the protein at amino acid residue 80, which likely damages the protein. Genotyping of additional PPROM cases and controls is required to determine if this nonsense variant is associated with PPROM. We could find no information in the literature regarding selective pressures impinging on the DEFB1 nonsense mutation would not lead to production of a mature peptide, so it is most certainly damaging. However, its potential to be a dominant negative inhibiting processing of full length DEFB1 pro-peptide from the major allele in heterozygous mutants remains to be explored. Likewise, the impact of the MBL2 nonsense mutation on protein function is only predicted, and studies need to be conducted with recombinant proteins to prove loss of function.Although our proposed strategy is consistent with guidelines for investigating causality of sequence variants in human disease, our approach has limitations including the current cost of WES and the use of modest sample sizes which may not have the power to detect pathophysiologic important rare variants/mutations . The focDEFB1 and MBL2 nonsense mutations are consistent with the notion that rare fetal mutations contribute to the disparities in preterm birth among African-Americans, and support the mining of rare mutations identified in WES as a portal to discovery of genes playing a role in preterm birth. A similar approach could be applied to other populations focusing on ancestry-enriched damaging variants. For example, there are rare damaging Latino  and East Asian  nonsense variants in the DEFB1 gene that could be evaluated for association with PPROM in the respective populations.Our findings on the Our findings based on a simple and cost-effective data analysis strategy support the notion that multiple rare population-specific variants in the fetal genome contribute to preterm birth associated with PPROM.Additional file 1:Table S1. Primers used for METTL7B SNP genotyping. Primers used for genotyping rs115687886, rs138407179, rs146636131. (DOCX 11 kb)Additional file 2:Figure S1. RT-PCR analysis for expression of DEFB1 and METTL7B. A. The first well shows the expression of DEFB1 in a sample from amnion and the second well a sample from placental tissue. A negative control was loaded in the third well. The primers used for the transcript amplification were forward 5’-CTGAAATCCTGGGTGTTGCC-3′ and reverse 5′- CTTCTGGTCACTCCCAGCTC- 3′. Amplified bands were sequence verified. B. The first well shows MBL2 expression in amnion and the second well a sample from placental tissue. A negative control was loaded in the third well. The primers used for the transcript amplification were forward 5’-ACCTGCCTAGACCCAAATCC-3′ and reverse 5′- TTATTTGACAGCCTTTCCCATGA-3′. Amplified bands were sequence verified. (TIF 789 kb)


To determine the association between circadian pathway genetic variants and the risk of prostate cancer progression.We systematically evaluated 79 germline variants in nine circadian pathway genes in a cohort of 458 patients with localized prostate cancer as the discovery phase. We then replicated the significant findings in another cohort of 324 men with more advanced disease. The association of each variant with prostate cancer progression was evaluated by a log-rank test and Cox regression.NPAS2) gene (rs6542993 A>T) was found to be associated with a significantly higher risk of disease progression in both localized (P = 0.001) and advanced (P = 0.039) prostate cancer cases. In silico analysis revealed decreased expression levels of NPAS2 in carriers of the T allele of rs6542993 compared with those carrying the A allele. Consistently, downregulation of NPAS2 expression was associated with more aggressive prostate cancer and poor progression-free survival (log-rank P = 0.002).A single nucleotide polymorphism of the neuronal PAS domain protein 2  contains supplementary material, which is available to authorized users. The circadian rhythm is driven by an internal biological clock, which allows organisms to sustain an approximate 24-h cycle of physiological activities such as the sleep–wake cycle, basal metabolism, hormone production, and immunity . The corShift-work, sleep deprivation, jet lag, and light exposure at night potentially cause circadian disruption, which has been linked to the risk of various diseases such as diabetes, depression, cardiovascular problems, and cancer –10. In pBased on accumulating evidence for a relationship between the circadian rhythm and cancer, we hypothesized that genetic variants in circadian pathway genes might have impacts on the prognosis of patients with prostate cancer. To test this hypothesis, we systematically evaluated the influence of 79 circadian gene variants on disease progression in patients with localized prostate cancers and then verified the findings in another group of patients with advanced prostate cancers.A total of 458 patients with localized prostate cancer who underwent radical prostatectomy as initial treatment and 324 patients with advanced prostate cancer who were on androgen-deprivation therapy (ADT) were included in the present study. The recruitment process and patient characteristics were described previously –22. In tARNTL, CLOCK, CRY1, CRY2, CSNK1E, NPAS2, PER1, PER2, and PER3) using the Tagger pairwise method [r2 value of 0.8 or higher and a minor allele frequency of at least 0.2 in the HapMap Chinese Han population [N = 7), deviated from Hardy–Weinberg equilibrium , or fell below a genotyping call rate of 0.85 (N = 3) was removed, leaving 79 SNPs for further analysis. The average genotype call rate was 99.2%, and the concordance rate was 100% among 10 duplicated samples.TagSNPs were chosen from nine circadian-related genes  Prostate Oncogenome Project [We annotated the regulatory potential of the region adjoining the tagSNPs using HaploReg v4.1  and ENCO Project .NPAS2 expression with clinical characteristics of the patients. All statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) software version 19.0.0 , and a two-sided P value of < 0.05 was considered statistically significant.Kaplan–Meier analysis with the log-rank test was first used to assess the association of time to disease progression with each tagSNP under dominant, recessive, and additive models of inheritance. Since many tagSNPs were analysed, we conducted bootstrap resampling  to interThe clinical characteristics of the study groups are presented in Table NPAS2 rs6542993 was significantly associated with BCR  of rs6542993 with respect to regulatory elements, and predicted functional motifs catalogued in ENCODE and HaploReg  population  block r ≥ 0.9 ofNPAS2 expression with prostate cancer outcome using the MSKCC Prostate Oncogenome Project data. Consistently, the NPAS2 gene expression level was significantly lower in cases of more aggressive forms of prostate cancer  with the risk allele, showed a strong association with NPAS2 expression. The risk allele rs6542993 T was associated with reduced levels of NPAS2 expression. Only a few studies have examined the role of circadian gene variants on prostate cancer risk, with some suggestive general associations reported [NPAS2 has consistently emerged as one of the top genes with the greatest contribution to the observed statistical association between the circadian pathway and risk of prostate cancer in two meta-analyses of data from genome-wide association studies [NPAS2 is suggested to be a putative tumour suppressor playing an important role in transcriptional suppression of the protooncogene c-Myc [NPAS2 has been identified as a prognostic biomarker in breast and colorectal cancers [NPAS2 expression was associated with decreased disease-free and overall survival rates in patients with breast cancer [NPAS2 expression promoted the proliferation, invasion, and wound healing abilities of colorectal cancer cells [NPAS2 in tumour growth and metastasis. We found no association between NPAS2 rs6542993 polymorphism and prostate cancer risk when comparing our patient population to 1500 healthy controls from the Taiwan Biobank (data not shown). The NPAS2 gene expression levels also did not vary significantly when comparing prostate cancers and normal tissues using the MSKCC Prostate Oncogenome Project data. These data suggested that NPAS2 might play a role in prostate cancer progression but not in prostate cancer initiation. However, the functional roles of NPAS2 in prostate cancer progression remain largely unclear and need further investigation.The risk variant rs6542993 is located in the intronic region of reported , 17, 18. studies , 38. NPAne c-Myc , DNA damne c-Myc , and celne c-Myc . In addi cancers , in whict cancer , in lineP values could not reach a more stringent significance level to avoid multiple comparisons. However, the association between NPAS2 rs6542993 and prostate cancer progression was replicated across two independent and different types of cohorts, which largely reduces the chance of false-positive findings. In addition, functional analyses support the role of NPAS2 rs6542993 in patient prognosis. Since the tagSNPs evaluated in this study were selected based on haplotype diversities, the linked causal variants remain to be determined. Since circadian genes are expressed in a circadian manner, the timing of specimen collection and the measurements of genetic variants and gene expression should be consistent in the same population. Another potential limitation of the study is that our findings may not be generalized to other ethnic groups since the majority of patients in both cohorts were Taiwanese. However, this may also be a benefit of our study in reducing the effects of population heterogeneity to more clearly detect an association. Nevertheless, further independent, larger, and inter-ethnic studies, as well as functional experiments are needed to validate our findings.The modest sample size of both cohorts included in this study did not allow for optimal statistical power to detect associations; therefore, the observed NPAS2 rs6542993 was consistently associated with disease progression after adjusting for clinical confounders in two independent prostate cancer cohorts. This SNP might affect prostate cancer progression by reducing the expression level of NPAS2. Thus, our findings might help to improve understanding of the interaction of circadian dysfunction and prostate cancer progression, and can provide a promising biomarker toward realizing the personalized management of patients with prostate cancer.This is the first attempt to systematically evaluate the effect of genetic variants in the circadian pathway on prostate cancer progression. Additional file 1: Table S1. Genotyped SNPs and the P values of their association with biochemical recurrence after radical prostatectomy.


A chronic pro-inflammatory environment is a hallmark of retinal degenerative diseases and neurological disorders that affect vision. Inflammatory responses during retinal pathophysiology are orchestrated by microglial cells which constitute the resident immune cell population. Following activation, microglia cells lose their ramified protrusions, proliferate and rapidly migrate to the damaged areas and resolve tissue damage. However, sustained presence of tissue stress primes microglia to become overreactive and results in the excessive production of pro-inflammatory mediators that favor retinal degenerative changes. Consequently, interventions aimed at overriding microglial pro-inflammatory and pro-oxidative properties may attenuate photoreceptor demise and preserve retinal integrity. We highlight the positive effects of ligands for the translocator protein 18 kDa (TSPO) and the cytokine interferon beta (IFN-β) in modulating microgliosis during retinal pathologies and discuss their plausible mechanisms of action. These models recapitulate key biological processes involved in human retinal pathologies such as retinitis pigmentosa (RP) and the exudative form of AMD, respectively.Translocator protein 18 kDa (TSPO), previously referred to as the peripheral benzodiazepine receptor (PBR), is a highly conserved 5α-helical transmembrane protein located on the outer mitochondrial membrane , to influence microglial reactivity in the acute white light-induced retinal degeneration mouse model  enzyme activities Ifnar1 as well as microglial specific conditional depletion of IFN-β signaling (CreER:Ifnar1fl/flCx3cr1) in mice resulted in exacerbated disease progression  is a type I interferon that possesses strong antiviral and immunomodulatory properties  to establish an antiviral cellular state, it also induces the expression of negative regulators which restrain pro-inflammatory pathways (Ivashkiv and Donlin, −/−Ifn mice when compared to their wildtype counterparts (Liu et al., −/−Ifn neurons compared with IFNβ-competent neurons (Liu et al., 2 and PGD2 in primary microglial cultures (de Oliveira et al., IFN-β has also long been known to be a potent activator of the PI3K–AKT–mTOR-signaling axis (Platanias, There is strong evidence from murine models of experimental retinal pathologies that microglia play a critical role in the development and advancement of retinal degenerative disorders and pathological neoangiogenesis. Therefore, immune based therapies such as TSPO ligands and IFN-β that counter excessive microglia-mediated neuroinflammatory responses and pathological angiogenesis may have an important role in the future clinical management of retinal disorders such as RP and AMD. However, prior to the clinical evaluation of immunomodulatory therapies in retinal diseases, critical questions regarding the exact molecular mechanisms of each individual immunoregulatory compound need to be answered.KR, AW and TL contributed to the concept and writing of the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


This randomized clinical trial evaluates the efficacy, feasibility, and acceptability of a parent-targeted intervention for parent-adolescent communication about sexual health and alcohol use. Can parent-targeted interventions delivered within primary care settings affect parent-adolescent communication about sexual health and alcohol use?This randomized clinical trial included 118 parent-adolescent dyads and found that brief parent-targeted interventions in primary care pediatric settings were acceptable, were feasible, and significantly increased adolescent-reported frequency of parent-adolescent communication about sexual health and alcohol use.Delivering parent-targeted interventions in primary care settings may be an important strategy for influencing parent-adolescent communication and adolescent behaviors and improving health outcomes. Adolescent well care visits provide opportunities for clinicians to facilitate parent-adolescent communication (PAC) to reduce pregnancy, sexually transmitted infections, and alcohol-related harm among adolescents.To test the effect of brief parent-targeted interventions delivered in primary care settings on PAC about sexual and alcohol use behaviors.Randomized clinical trial conducted at a primary care pediatric practice from January 4, 2016, to April 10, 2017. Adolescents who were scheduled for a well care visit were recruited, along with their parent or guardian. Data analyses continued through April 30, 2018.During well care visits, parents in sexual health intervention and alcohol prevention intervention groups received coaching to discuss written intervention materials encouraging PAC about sex or alcohol, respectively, with their adolescent within 2 weeks, followed by a brief clinician endorsement. After 2 weeks, parents received a follow-up telephone call. Control group parents received usual care.Participants were surveyed 4 months after the well care visit. Parent-reported and adolescent-reported quality of PAC was measured using the 20-item Parent-Adolescent Communication Scale, in which a higher score indicates better PAC; and frequency of PAC about sex or alcohol was measured using a 4-point Likert-type scale with 1 indicating not at all or never, and 4 indicating a lot or often.P = .02); adolescents in the alcohol prevention intervention group reported a higher mean frequency score for PAC about alcohol compared with those in the control group . Parent-reported frequency scores for PAC about sex or alcohol did not differ by group.Of 196 parent-adolescent dyads assessed for eligibility, 118 (60.2%) were eligible to participate. These 118 dyads were randomized to 1 of 3 groups: (1) sexual health intervention (n = 38 [32.2%]); (2) alcohol prevention intervention (n = 40 [33.9%]); and control (n = 40 [33.9%]); 104 parents (88.1%) and 99 adolescents (83.9%) completed the study. Parents included 112 women (94.9%) and had a mean (SD) age of 45.8 (6.9) years. Adolescents included 60 girls (50.9%); 67 adolescents (56.8%) were aged 14 years, and 51 adolescents (43.2%) were aged 15 years. Participant race/ethnicity reflected that of the practice . At baseline, 15 adolescents (12.7%) reported a history of sexual behavior and 16 adolescents (13.6%) reported a history of alcohol use. Intention-to-treat analyses found that 4 months after the intervention, adolescents in the sexual health intervention group reported a higher mean frequency score for PAC about sex compared with those in the control group (2.32  vs 1.79 ; Brief parent-targeted interventions in primary care settings increased adolescent-reported frequency of PAC about sexual health and alcohol use and may be an important strategy for parents to influence adolescent behaviors and health outcomes.NCT02554682ClinicalTrials.gov identifier:  Our study was not sufficiently large or long enough to test influences of PAC on adolescent behaviors, but we adapted and tested interventions shown to improve both PAC and behavior  in other settings.Delivering effective PAC interventions in conjunction with annual adolescent well care visits in primary care clinics could provide a recurring mechanism to systematically reach sizable portions of adolescents and their parents or guardians.parent) and focused on improving PAC about sexual health and alcohol use. The trial was conducted from January 4, 2016, to April 10, 2017. Data analyses continued until April 30, 2018. Another study arm involved older adolescents and focused on PAC about safe driving; that study is reported elsewhere.16 The study protocol (CONSORT) reporting guideline.This randomized clinical trial included adolescents aged 14 to 15 years and their parent or caregiver . Parents later joined their adolescent in the examination room. Parents in the control group received usual care.Two weeks after the well care visit, intervention group parents were contacted via telephone call. Research assistants (RAs) covered material that was not completed during the in-person health coaching visit, if applicable, and administered a short survey. If parents had not had a conversation with their adolescent about the intervention topic in the preceding 2 weeks, barriers were identified and RAs discussed how the materials might be used to overcome them.Four months after the well care visit, parents and adolescents in all groups were contacted to complete a final survey. Parents and adolescents who completed the baseline survey each received $10. Parents who completed the 2-week telephone survey received $5. Parents and adolescents who completed the final follow-up survey each received $20.18 Further, selected interventions could be pragmatically adapted for use in busy primary care settings. The intervention process included a health coach discussing written materials with parents in the clinic lobby during a well care visit, conveying key messages, and encouraging PAC within 2 weeks Sexual health brochure and handbookGeneral communication handbook Key Messages:PAC about sexual health makes a differencePAC about sexual health can be hardUse materials to help you talk with your adolescent within 2 weeksAnticipated barriers to PAC and how to overcome them Research suggests it is important to convey these main points:Wait until you’re older to have sexIf you do have sex, use condomsIf you do have sex, go to a physician or clinic to talk about sexually transmitted infectionsPhysician or nurse practitioner provides a direct endorsement and written prescription reinforcing the key messages in the clinic room with the parent and adolescent at the end of the visit.Follow-up telephone call to the parent at 2 weeks to ask about PAC about sexual health, inquire about barriers, and review how materials can be used to overcome barriers.Health coach talks with parent in lobby to discuss:b Alcohol prevention brochure and handbookGeneral communication handbook Key Messages:PAC about alcohol use makes a differencePAC about alcohol can be hardUse materials to help you talk with your adolescent within 2 weeksAnticipated barriers to PAC and how to overcome them Research suggests it is important to convey these main points:Wait until you’re older to drink alcoholIf you do drink alcohol, minimize risk of injury or harmDo not drive or get into a vehicle with someone who has been drinkingPhysician or nurse practitioner provides a direct endorsement and written prescription reinforcing key messages in clinic room with the parent and adolescent at the end of the visitFollow-up telephone call to the parent at 2 weeks about PAC about alcohol, inquire about barriers, and review how materials can be used to overcome barriers.Abbreviation: PAC, parent-adolescent communication.aContent developed based on previous research identifying parental attitudes and beliefs that influence PAC about sexual health and adolescent attitudes and beliefs that influence sexual behaviors.bContent developed based on previous research identifying parental attitudes and beliefs that influence PAC about alcohol and adolescent attitudes and beliefs that influence alcohol use.Written materials were adapted to parents of our targeted age group, provided local data on sexual behaviors or alcohol use, and showed visual images reflecting the racial/ethnic composition of the local community and of gender-nonconforming adolescents and parents. Materials included colorful spiral-bound handbooks with discussion guides and activity sheets on general PAC and a similarly formatted handbook and brochure focused on PAC about sexual health or alcohol use prevention; written materials were also available electronically.Adolescents’ age was calculated based on date of birth; sex at birth, race, and ethnicity were measured by self-report. Parental age, marital status, and highest level of education were measured by self-report.Adolescent behaviors were measured by self-report at baseline. Sexual behavior was assessed by 4 items: “In your lifetime, have you ever engaged in vaginal sexual intercourse? …had anal sexual intercourse? …given oral sex? …received oral sex?” Alcohol use was assessed with the question, “Have you ever had a drink of alcohol, other than a few sips?” Adolescents were coded as having engaged in adolescent risk behavior if they responded yes to any of these items.19 in which a higher score indicates better PAC. Adolescents answered similar questions with minor word changes. Frequency of PAC about sex was measured with an item asking parents and adolescents how much they had talked about sex since the adolescent’s last well care visit using a 4-point Likert-type response categories with 1 indicating not at all or never and 4 indicating a lot or often. Frequency of PAC about alcohol was measured with a similar item asking parents and adolescents how much they had talked about alcohol since the adolescent’s last well care visit. Communication about a specific safety plan was measured by asking parents and adolescents about PAC since the adolescent’s last well care visit about strategies to avoid getting in a car being driven by someone who has been drinking, with responses coded as no communication or some PAC.There were 4 measures for reported PAC on the final survey. Quality of PAC was assessed by the 20-item Parent-Adolescent Communication Scale,Feasibility was assessed by measuring length of time the RA spent with the parent (RA report) and checklists to document content delivered . Acceptability was assessed by final surveys. Parents were asked about general helpfulness and intentions to use materials over the next 12 months . Adolescents were asked how helpful they thought the materials were to their parent. Clinicians received an anonymous web-based survey asking open-ended questions about implementing the study in their clinic and using these interventions in real life if they were found to be effective.We tested for differences in sociodemographic characteristics between participants who completed the follow-up survey and those who were lost to follow-up. We examined frequencies of parent- and adolescent-reported PAC and evaluated bivariate associations with adolescent sex, age, race/ethnicity, and risk behaviors using analysis of variance. Unadjusted and adjusted models were estimated. Covariates in the adjusted models were adolescent age, sex, race/ethnicity, and sexual behavior or alcohol use. Generalized linear models were conducted to compare differences between each intervention group vs the control group in quality of PAC and frequency of PAC about sex or alcohol. Depending on the distribution of the outcome variable being analyzed, different distributions and link functions were specified for the generalized linear models: linear to estimate outcome means, bivariate and adjusted, with 95% CIs or log-binomial to estimate unadjusted and adjusted risk ratios (RRs) with 95% CIs. We conducted similar analyses specifically for safety plan PAC content.d of 0.625, using a 2-sided P value of less than .05 for statistical significance. Further details on the trial protocol and statistical analysis can be found in Analyses were performed separately for adolescents and parents. Data were analyzed using an intent-to-treat principle and multiple imputation. To account for missing outcomes, multiple imputation with 100 imputations was used, analyses were conducted on each of the 100 imputed data set, and the parameter estimates across the data sets were combined to produce a unique point estimate and SE taking into account the uncertainty of the imputation process. Statistical analysis was performed using SAS statistical software version 14.2 (SAS Institute). Our sample size of 40 participants per group had 80% power to detect a difference in 2 population means corresponding to a Cohen A total of 118 parents and 118 adolescents participated. Among parents, 112 were women (94.9%), and the mean (SD) age was 45.8 (6.9) years . AdolescP = .01) or the control group (38 of 40 dyads [95%]) (P = .01) . Sociodemographic and behavior characteristics were similar between dyads who completed and those who did not complete the study.The study was completed by 104 parents (88.1%) and 99 adolescents (83.9%). Fewer parents and adolescents in the sexual health intervention group were available for the 4-month interview (25 of 38 dyads [66%]) than the alcohol prevention intervention group (36 of 40 dyads [90%]) (P = .009). Parents of younger adolescents reported a higher mean (SD) score for frequency of PAC about sex compared with parents of older adolescents . Parents of black adolescents reported a higher mean (SD) frequency score for PAC about sex compared with parents of white adolescents . Black adolescents also reported a higher mean (SD) score for frequency of PAC about sex compared with white adolescents . We found no significant bivariate associations of adolescent sex with parent-reported or adolescent-reported quality of PAC, frequency of PAC about sex, or frequency of PAC about alcohol. We found no significant bivariate associations of adolescent risk behaviors with parent-reported or adolescent-reported quality of PAC, frequency of PAC about sex, or frequency of PAC about alcohol.Responses to quality of PAC were summed into an index ranging from 41 to 96 for parents (α = .84) and 43 to 96 for adolescents (α = .87). Adolescent-reported quality of PAC varied by adolescent age; younger adolescents reported a significantly higher mean (SD) score for quality of PAC than older adolescents . Adolescents with parents in the sexual health intervention group did not report higher scores for quality of PAC or frequency of PAC about alcohol. Adolescents with parents in the alcohol prevention intervention group reported a higher mean score for frequency of PAC about alcohol during the 4 months after their last well care visit when compared with the control group ; they did not report higher frequency of general PAC or PAC about sex  . Parents and adolescents in the sexual health intervention group were more likely to report PAC about a specific safety strategy plan compared with those in the control group .Among 40 parents in the alcohol prevention intervention group, 25 (62.5%) reported that since their last well care visit they had communicated about a specific safety strategy plan to help adolescents avoid being in a car with a driver who had been drinking alcohol compared with 13 of 40 parents (33%) parents in the control group  . SimilarParents spent a median of 10  minutes in coaching sessions. Among 78 parents in the 2 intervention groups, 75 (96%) received an entire health coaching session in the clinic and 74 (95%) reported receiving an in-person clinician endorsement, which was consistent with clinician reports. We were able to contact 66 intervention parents (85%) for the 2-week follow-up call.Sixty-two parents in the intervention groups rated the intervention materials as moderately or very helpful (80%), 66 parents (85%) reported they would probably or definitely refer to materials during the next 12 months, 65 parents (83%) reported they would probably or definitely use materials with other children in their family, and 43 parents (55%) reported they would probably or definitely give materials to other parents during the next 12 months. Of the 78 adolescents in the intervention groups, 66 (85%) were aware that their parents had been given intervention materials; of these, 53 adolescents (80%) reported their parent showed them materials and 43 adolescents (65%) reported that the materials were moderately or very helpful to their parent.Seven of 9 participating clinicians (78%) completed the feedback survey and reported materials were high quality, important, well received, and easy to disseminate. Clinicians expressed needs for additional resources  to support the health coach role if interventions were to be provided in routine clinical care.16 similarly adapted a parent-targeted teenage driver safety intervention focused on older patients in the same clinic, which also demonstrated feasibility, acceptability, and initial evidence for efficacy. All interventions were adapted from interventions that, in other settings, influence PAC and adolescent behaviors associated with unintended pregnancy, sexually transmitted infections, alcohol-related injury, or motor vehicle crashes.20 Together, this provides strong support for future research testing the influence of pragmatic primary care–based parent-targeted interventions on PAC and adolescent health outcomes.These parent-targeted primary care-based interventions increased adolescent-reported frequency of PAC about sexual health and alcohol up to 4 months after a well care visit. Interventions were feasible to deliver and highly acceptable to participants. Mirman et al23 We observed that the reported frequency of PAC was higher for alcohol use than for sexual behavior, and more dyads in the alcohol prevention intervention and control groups were willing to complete follow-up surveys compared with those in our sexual health intervention group. This finding highlights that there are important nuances to take into consideration for PAC interventions about different topics  and suggests that tailoring choice of PAC interventions based on real or perceived value from the perspective of parents, adolescents, and clinicians should be considered. For example, instead of an age-based approach as used in this study, delivering PAC interventions linked to specific health topics could be informed by assessment of individual adolescent risk or adolescent or parent interest. Finally, compared with the control group, approximately 2-fold as many parents and adolescents in the intervention groups reported increased PAC about strategies for adolescents to avoid getting into a car with someone who has been drinking alcohol, although this specific content was only included in alcohol prevention intervention materials. This finding suggests that there may be broader beneficial effects of topic-specific parent-targeted interventions on PAC, which warrants further study.Several additional findings were notable. In stratified analyses, increases in frequency of PAC were reported by adolescents but not parents. This was an unexpected finding. Parents and adolescents may recognize or label PAC differently, especially about sensitive topics. Regardless, research has shown that adolescent perceptions of parental messages affect adolescent behavior, highlighting the importance of our adolescent-reported results.It is important to note that we found these interventions feasible within the context of a research study, which supplied health coach staffing resources to provide the interventions as well as the 2-week follow-up telephone call to parents. Clinicians reported that resources for health coach staffing would be needed to implement similar strategies in real-life conditions. Our health coaches were trained in the use of materials and protocols but were not trained in health care, suggesting that it may be possible to consider a range of staffing models. Our study was intentionally designed to leverage the influence of person-to-person contact within trusted, credible clinic settings, but strategies to minimize staff time to do this could be tested . Finally, future research showing that parent-targeted interventions delivered in or through primary care settings effectively change adolescent behavior and improve adolescent health outcomes would justify reimbursement for staff time to deliver interventions.This study has several limitations. It was conducted at a single site, which may limit generalizability. Parent-adolescent communication was measured by self-report and could be affected by recall or self-report biases. Clinicians were not blinded in this study, which may have influenced care to adolescents in all groups. A multisite study with additional measures of PAC and a longer follow-up period is needed to evaluate intervention impact on behaviors.9 The paucity of existing primary care parent-targeted interventions needs to be addressed, with a focus on developing a portfolio of interventions that effectively address a range of adolescent health issues. Developing and evaluating such interventions, and developing feasible models for incorporating them into practice, are important avenues for future research.Results suggest that there are innovative strategic opportunities for clinicians in primary care settings to join with parents to effectively achieve better health outcomes among sizable portions of adolescent patients.