Particulate matter (PM) is an important risk factor for asthma. Generation of oxidative stress by PM is a major mechanism of its health effects. Transcription factor nuclear factor (erythroid-derived 2)-like 2 (Nrf2) mediates antioxidant and phase II enzymes and is essential in protecting against oxidative stress and lung inflammation. We have previously shown that ambient ultrafine particles (UFP) could exert a potent adjuvant effect on allergic sensitization to ovalbumin (OVA) in mice. We hypothesized that Nrf2 deficiency in dendritic cells (DC) could enhance the adjuvant potential of UFP on allergic sensitization. We show that the adjuvant effect of intranasally instilled UFP is significantly enhanced in Nrf2 knockout (Nrf2-/-) mice compared with their wild-type (Nrf2+/+) counterparts. Under resting conditions Nrf2-/- DC displayed an intrinsic predilection to a T-helper 2 (Th2)-favoring cytokine profile characterized by low level of IL-12p70 and high level of IL-6 as compared to Nrf2+/+ DC. Adoptive transfer of OVA/UFP-treated Nrf2-/- DC provoked a more severe allergic inflammation in the lung than Nrf2+/+ DC in the same treatment group. We conclude that Nrf2 deficiency in DC may promote a constitutive immune-polarizing cytokine milieu, which we propose may have contributed to the augmented adjuvant effect of UFP on allergic sensitization.
Nrf2; Dendritic cell; Adjuvant; Allergic sensitization; Lung inflammation; Ultrafine particles; IL-12p70; IL-6; T-helper 2
The electronic Medical Records and Genomics (eMERGE) (Phase I) network was established in 2007 to further genomic discovery using biorepositories linked to the electronic health record (EHR). In Phase II, which began in 2011, genomic discovery efforts continue and in addition the network is investigating best practices for implementing genomic medicine, in particular, the return of genomic results in the EHR for use by physicians at point-of-care. To develop strategies for addressing the challenges of implementing genomic medicine in the clinical setting, the eMERGE network is conducting studies that return clinically-relevant genomic results to research participants and their health care providers. These genomic medicine pilot studies include returning individual genetic variants associated with disease susceptibility or drug response, as well as genetic risk scores for common “complex” disorders. Additionally, as part of a network-wide pharmacogenomics-related project, targeted resequencing of 84 pharmacogenes is being performed and select genotypes of pharmacogenetic relevance are being placed in the EHR to guide individualized drug therapy. Individual sites within the eMERGE network are exploring mechanisms to address incidental findings generated by resequencing of the 84 pharmacogenes. In this paper, we describe studies being conducted within the eMERGE network to develop best practices for integrating genomic findings into the EHR, and the challenges associated with such work.
genomics; electronic health records; incidental findings; implementation; genetic counseling; next generation sequencing; pharmacogenetics
Background and objectives
Worry is predominantly a verbal-linguistic process with relatively little imagery. This study investigated whether the verbal nature of worry contributes to the maintenance of worry by enhancing attention to threat. It was hypothesised that verbal worry would lead to greater attentional bias to threat than imagery-based worry.
Fifty high-worriers were randomly assigned to one of two groups, one in which they were instructed to worry in a verbal way and one in which they worried in an imagery-based way, before completing a dot probe task as a measure of attention to threat-related words.
Those who worried in verbal form demonstrated greater attentional bias to threat than did those who worried in imagery-based form. These findings could not be accounted for by group differences in personal relevance of or distress associated with worry topics, state mood following worry, levels of the relatedness of participants' worries to stimuli on the dot probe task, trait anxiety, general propensity to worry, nor adherence to the worry training.
The present study only included word stimuli in the dot probe task; inclusion of images would allow for firmly rejecting the hypothesis that the attention effects observed following verbal worry were merely a result of priming verbal threat representations. Also, future studies could include a further control group that does not engage in any form of worry to ascertain that verbal worry increased attentional bias rather than imagery decreasing pre-existing attentional bias.
Possible mechanisms underlying this effect of verbal worry on attention to threat are discussed, together with clinical implications of the current findings.
•Worry is predominantly a verbal-linguistic process with relatively little imagery.•High-worriers worried in verbal or imagery form before an emotional dot probe task.•Verbal worry is associated with attentional bias for threat words.•Imagery-based worry is not associated with an attentional bias for threat words.•The verbal nature of worry has a causal role in its maintenance.
Worry; Attention; Imagery; Verbal-linguistic processing; Dot probe
Whole genome sequencing (WGS) is being used for evaluation of individuals with undiagnosed disease of suspected genetic origin. Implementing WGS into clinical practice will place an increased burden upon care teams with regard to pre-test patient education and counseling about results. To quantitate the time needed for appropriate pre-test evaluation of participants in WGS testing, we documented the time spent by our clinical research group on various activities related to program preparation, participant screening, and consent prior to WGS. Participants were children or young adults with autism, intellectual or developmental disability, and/or congenital anomalies, who have remained undiagnosed despite previous evaluation, and their biologic parents. Results showed that significant time was spent in securing allocation of clinical research space to counsel participants and families, and in acquisition and review of participant’s medical records. Pre-enrollment chart review identified two individuals with existing diagnoses resulting in savings of $30,000 for the genome sequencing alone, as well as saving hours of personnel time for genome interpretation and communication of WGS results. New WGS programs should plan for costs associated with additional pre-test administrative planning and patient evaluation time that will be required to provide high quality care.
Electronic supplementary material
The online version of this article (doi:10.1007/s10897-014-9697-4) contains supplementary material, which is available to authorized users.
Whole genome sequencing; Time study; Electronic health record; Genetic counseling; Intellectual disability
The inclusion of genomic data in the electronic health record raises important ethical, legal, and social issues. In this article, we highlight these challenges and discuss potential solutions. We provide a brief background on the current state of electronic health records in the context of genomic medicine, discuss the importance of equitable access to genome-enabled electronic health records, and consider the potential use of electronic health records for improving genomic literacy in patients and providers. We highlight the importance of privacy, access, and security, and of determining which genomic information is included in the electronic health record. Finally, we discuss the challenges of reporting incidental findings, storing and reinterpreting genomic data, and nondocumentation and duty to warn family members at potential genetic risk.
clinical decision support, electronic health records; ethical, legal, and social implications; genomics; personalized medicine
Next Generation Sequencing studies generate a large quantity of genetic data in a relatively cost and time efficient manner and provide an unprecedented opportunity to identify candidate causative variants that lead to disease phenotypes. A challenge to these studies is the generation of sequencing artifacts by current technologies. To identify and characterize the properties that distinguish false positive variants from true variants, we sequenced a child and both parents (one trio) using DNA isolated from three sources (blood, buccal cells, and saliva). The trio strategy allowed us to identify variants in the proband that could not have been inherited from the parents (Mendelian errors) and would most likely indicate sequencing artifacts. Quality control measurements were examined and three measurements were found to identify the greatest number of Mendelian errors. These included read depth, genotype quality score, and alternate allele ratio. Filtering the variants on these measurements removed ~95% of the Mendelian errors while retaining 80% of the called variants. These filters were applied independently. After filtering, the concordance between identical samples isolated from different sources was 99.99% as compared to 87% before filtering. This high concordance suggests that different sources of DNA can be used in trio studies without affecting the ability to identify causative polymorphisms. To facilitate analysis of next generation sequencing data, we developed the Cincinnati Analytical Suite for Sequencing Informatics (CASSI) to store sequencing files, metadata (eg. relatedness information), file versioning, data filtering, variant annotation, and identify candidate causative polymorphisms that follow either de novo, rare recessive homozygous or compound heterozygous inheritance models. We conclude the data cleaning process improves the signal to noise ratio in terms of variants and facilitates the identification of candidate disease causative polymorphisms.
whole exome sequencing; variant filtering; next-generation sequencing; disease causative polymorphisms; Mendelian errors; Mendel errors; CASSI
Integrating genomic information into clinical care and the electronic health record can facilitate personalized medicine through genetically guided clinical decision support. Stakeholder involvement is critical to the success of these implementation efforts. Prior work on implementation of clinical information systems provides broad guidance to inform effective engagement strategies. We add to this evidence-based recommendations that are specific to issues at the intersection of genomics and the electronic health record. We describe stakeholder engagement strategies employed by the Electronic Medical Records and Genomics Network, a national consortium of US research institutions funded by the National Human Genome Research Institute to develop, disseminate, and apply approaches that combine genomic and electronic health record data. Through select examples drawn from sites of the Electronic Medical Records and Genomics Network, we illustrate a continuum of engagement strategies to inform genomic integration into commercial and homegrown electronic health records across a range of health-care settings. We frame engagement as activities to consult, involve, and partner with key stakeholder groups throughout specific phases of health information technology implementation. Our aim is to provide insights into engagement strategies to guide genomic integration based on our unique network experiences and lessons learned within the broader context of implementation research in biomedical informatics. On the basis of our collective experience, we describe key stakeholder practices, challenges, and considerations for successful genomic integration to support personalized medicine.
electronic health records; genomics; health information technology; personalized medicine; stakeholder engagement; translational medical research
In clinical exome and genome sequencing, there is potential for the recognition and reporting of incidental or secondary findings unrelated to the indication for ordering the sequencing but of medical value for patient care. The American College of Medical Genetics and Genomics (ACMG) recently published a policy statement on clinical sequencing, which emphasized the importance of disclosing the possibility of such results in pretest patient discussions, clinical testing, and reporting of results. The ACMG appointed a Working Group on Incidental Findings in Clinical Exome and Genome Sequencing to make recommendations about responsible management of incidental findings when patients undergo exome or genome sequencing. This Working Group conducted a year-long consensus process, including review by outside experts, and produced recommendations that have been approved by the ACMG Board. Specific and detailed recommendations, and the background and rationale for these recommendations, are described herein. We recommend that laboratories performing clinical sequencing seek and report mutations of the specified classes or types in the genes listed here. This evaluation and reporting should be performed for all clinical germline (constitutional) exome and genome sequencing, including the ‘normal’ of tumor-normal subtractive analyses in all subjects, irrespective of age, but excluding fetal samples. We recognize that there are insufficient data on clinical utility to fully support these recommendations and we encourage the creation of an ongoing process for updating these recommendations at least annually as further data are collected.
secondary findings; incidental findings; genome; genomic medicine; personalized medicine; whole-exome; whole-genome; sequencing
Applying an age cutoff to a Lynch syndrome screening program has considerable potential for decreasing total screening costs and increasing efficiency, but at a loss of effectiveness.
To determine the impact of applying an age cutoff to tumor-based Lynch syndrome (LS) screening, specifically focusing on changes in relative effectiveness, efficiency, and cost. The project was undertaken to answer questions about implementation of the LS screening program in an integrated health care delivery system.
Patients and Methods:
Clinical data extracted from an internal cancer registry, previous modeling efforts, published literature, and gray data were used to populate decision models designed to answer questions about the impact of age cutoffs in LS screening. Patients with colorectal cancer (CRC) were stratified at 10-year intervals from ages 50 to 80 years and compared with no age cutoff. Outcomes are reported for a cohort of 325 patients screened and includes total cost to screen, LS cases present in the cutoff category, number of LS cases expected to be identified by screening, cost per LS case detected, and total number and percentage of LS cases missed.
Applying an age cutoff to an LS screening program has considerable potential for decreasing total screening costs and increasing efficiency, but at a loss of effectiveness. Imposing an age cutoff of 50 years reduces the cost of the screening program to 16% of a program with no age cutoff, but at the expense of missing more than half of the cases. Failure to identify LS cases is magnified by a cascade effect in family members. The results of this analysis influenced the final policy in our system.
The Electronic Medical Records and Genomics (eMERGE) Network is a National Human Genome Research Institute (NHGRI)-funded consortium engaged in the development of methods and best-practices for utilizing the Electronic Medical Record (EMR) as a tool for genomic research. Now in its sixth year, its second funding cycle and comprising nine research groups and a coordinating center, the network has played a major role in validating the concept that clinical data derived from EMRs can be used successfully for genomic research. Current work is advancing knowledge in multiple disciplines at the intersection of genomics and healthcare informatics, particularly electronic phenotyping, genome-wide association studies, genomic medicine implementation and the ethical and regulatory issues associated with genomics research and returning results to study participants. Here we describe the evolution, accomplishments, opportunities and challenges of the network since its inception as a five-group consortium focused on genotype-phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting towards implementation of genomic medicine.
electronic medical records; personalized medicine; genome-wide association studies; genetics and genomics; collaborative research
Advances in genomics and related fields promise a new era of personalized medicine in the cancer care continuum. Nevertheless, there are fundamental challenges in integrating genomic medicine into cancer practice. We explore how multilevel research can contribute to implementation of genomic medicine. We first review the rapidly developing scientific discoveries in this field and the paucity of current applications that are ready for implementation in clinical and public health programs. We then define a multidisciplinary translational research agenda for successful integration of genomic medicine into policy and practice and consider challenges for successful implementation. We illustrate the agenda using the example of Lynch syndrome testing in newly diagnosed cases of colorectal cancer and cascade testing in relatives. We synthesize existing information in a framework for future multilevel research for integrating genomic medicine into the cancer care continuum.
Colonoscopy is one of the most effective methods of cancer prevention and detection, particularly for individuals with familial risk. Recruitment of family members to behavioral intervention trials remains uniquely challenging, owing to the intensive process required to identify and contact them. Recruiting at-risk family members involves contacting the original cancer cases and asking them to provide information about their at-risk relatives, who must then be contacted for study enrollment. Though this recruitment strategy is common in family trials, few studies have compared influences of patient and relative participation to nonparticipation. Furthermore, although use of cancer registries to identify initial cases has increased, to our knowledge no study has examined the relationship between registries and family recruitment outcomes.
This study assessed predictors of case participation and relative enrollment in a recruitment process that utilized state cancer registries. Participation characteristics were analyzed with separate multivariable logistic regressions in three stages: (1) cancer registry-contacted colorectal cancer (CRC) cases who agreed to study contact; (2) study-contacted CRC cases who provided at-risk relative information; and (3) at-risk relatives contacted for intervention participation.
Cancer registry source was predictive of participation for both CRC cases and relatives, though relative associations (odds ratios) varied across registries. Cases were less likely to participate if they were Hispanic or nonwhite, and were more likely to participate if they were female or younger than 50 at cancer diagnosis. At-risk relatives were more likely to participate if they were from Utah, if another family member was also participating in the study, or if they had previously had a colonoscopy. The number of eligible cases who had to be contacted to enroll one eligible relative varied widely by registry, from 7 to 81.
Family recruitment utilizing cancer registry-identified cancer cases is feasible, but highly dependent on both the strategies and protocols of those who are recruiting and on participant characteristics such as sex, race, or geography. Devising comprehensive recruitment protocols that specifically target those less likely to enroll may help future research meet recruitment goals.
Family Colorectal Cancer Awareness and Risk Education Project NCT01274143.
Cancer; Colorectal; Patient selection; Recruitment
The rapid advance of gene sequencing technologies has produced an unprecedented rate of discovery of genome variation in humans. A growing number of authoritative clinical repositories archive gene variants and disease phenotypes, yet there are currently many more gene variants that lack clear annotation or disease association. To date, there has been very limited coverage of gene-specific predictors in the literature. Here the evaluation is presented of “gene-specific” predictor models based on a naïve Bayesian classifier for 20 gene–disease datasets, containing 3986 variants with clinically characterized patient conditions. The utility of gene-specific prediction is then compared with “all-gene” generalized prediction and also with existing popular predictors. Gene-specific computational prediction models derived from clinically curated gene variant disease datasets often outperform established generalized algorithms for novel and uncertain gene variants.
Amino acid properties; gene variant classification; machine learning; phenotype prediction; bioinformatics; gene variants classification; gene disease database; developing/using computerized provider order entry; designing usable (responsive) resources and systems; methods for integration of information from disparate sources; high-performance and large-scale computing; distributed systems; agents; software engineering: architecture; data exchange; communication; integration across care settings (inter- and intra-enterprise); system implementation and management issues; languages; computational methods; statistical analysis of large datasets; advanced algorithms; identifying genome and protein structure and function; detecting disease outbreaks and biological threats; visualization of data and knowledge
Rationale: The differentiation of fibroblasts into myofibroblasts is a cardinal feature of idiopathic pulmonary fibrosis (IPF). The transcription factor Yin Yang 1 (YY1) plays a role in the proliferation and differentiation of diverse cell types, but its role in fibrotic lung diseases is not known.
Objectives: To elucidate the mechanism by which YY1 regulates fibroblast differentiation and lung fibrosis.
Methods: Lung fibroblasts were cultured with transforming growth factor (TGF)-β or tumor necrosis factor-α. Nuclear factor (NF)-κB, YY1, and α-smooth muscle actin (SMA) were determined in protein, mRNA, and promoter reporter level. Lung fibroblasts and lung fibrosis were assessed in a partial YY1-deficient mouse and a YY1f/f conditional knockout mouse after being exposed to silica or bleomycin.
Measurements and Main Results: TGF-β and tumor necrosis factor-α up-regulated YY1 expression in lung fibroblasts. TGF-β–induced YY1 expression was dramatically decreased by an inhibitor of NF-κB, which blocked I-κB degradation. YY1 is significantly overexpressed in both human IPF and murine models of lung fibrosis, including in the aggregated pulmonary fibroblasts of fibrotic foci. Furthermore, the mechanism of fibrogenesis is that YY1 can up-regulate α-SMA expression in pulmonary fibroblasts. YY1-deficient (YY1+/−) mice were significantly protected from lung fibrosis, which was associated with attenuated α-SMA and collagen expression. Finally, decreasing YY1 expression through instilled adenovirus-cre in floxed-YY1f/f mice reduced lung fibrosis.
Conclusions: YY1 is overexpressed in fibroblasts in both human IPF and murine models in a NF-κB–dependent manner, and YY1 regulates fibrogenesis at least in part by increasing α-SMA and collagen expression. Decreasing YY1 expression may provide a new therapeutic strategy for pulmonary fibrosis.
nuclear factor-κB; α-smooth muscle actin; idiopathic pulmonary fibrosis
Accurate interpretation of gene testing is a key component in customizing patient therapy. Where confirming evidence for a gene variant is lacking, computational prediction may be employed. A standardized framework, however, does not yet exist for quantitative evaluation of disease association for uncertain or novel gene variants in an objective manner. Here, complementary predictors for missense gene variants were incorporated into a weighted Consensus framework that includes calculated reference intervals from known disease outcomes. Data visualization for clinical reporting is also discussed.
The biological effects of acute particulate air pollution exposure in host innate immunity remain obscure and have relied largely on in vitro models. We hypothesized that single acute exposure to ambient or engineered particulate matter (PM) in the absence of other secondary stimuli would activate lung dendritic cells (DC) in vivo and provide information on the early immunological events of PM exposure and DC activation in a mouse model naïve to prior PM exposure. Activation of purified lung DC was studied following oropharyngeal instillation of ambient particulate matter (APM). We compared the effects of APM exposure with that of diesel-enriched PM (DEP), carbon black particles (CBP) and silver nanoparticles (AgP). We found that PM species induced variable cellular infiltration in the lungs and only APM exposure induced eosinophilic infiltration. Both APM and DEP activated pulmonary DC and promoted a Th2-type cytokine response from naïve CD4+ T cells ex vivo. Cultures of primary peribronchial lymph node cells from mice exposed to APM and DEP also displayed a Th2-type immune response ex vivo. We conclude that exposure of the lower airway to various PM species induces differential immunological responses and immunomodulation of DC subsets. Environmental APM and DEP activated DC in vivo and provoked a Th2 response ex vivo. By contrast, CBP and AgP induced altered lung tissue barrier integrity but failed to stimulate CD4+ T cells as effectively. Our work suggests that respirable pollutants activate the innate immune response with enhanced DC activation, pulmonary inflammation and Th2-immune responsiveness.
Innate immunity; Allergic immunity; Dendritic cell; Lung; Inflammation; Immunotoxicology; Toxicology; Particulate matter; Nanoparticles
Oxidative stress plays an important role in immune regulation and dendritic cell (DC) maturation. Recent studies indicate that allergens, including ragweed extract (RWE), possess prooxidant activities, but how RWE interacts with DCs is not well understood. Nuclear erythroid 2 p45-related factor 2 (Nrf2) is a key transcription factor that regulates constitutive and coordinated induction of a battery of antioxidant genes. We hypothesized that RWE would activate DCs and that this response would be augmented in the absence of Nrf2. We generated bone marrow–derived DCs (BM-DCs) and isolated lung DCs from Nrf2+/+ and Nrf2−/− mice and studied the effects of RWE on DCs in vitro. Under resting conditions, Nrf2−/− BM-DCs exhibited constitutively greater levels of inflammatory cytokines and costimulatory molecules than Nrf2+/+ BM-DCs. Exposure to RWE impaired endocytic activity, significantly induced oxidative stress, and enhanced the expression of CD80, CD86, and MHCII in Nrf2−/− BM-DCs when compared with Nrf2+/+ BM-DC, in association with reduced expression of Nrf2-regulated antioxidant genes. RWE significantly induced the secretion of inflammatory cytokines IL-6 and TNF-α in BM-DCs and lung DCs from Nrf2−/− mice than Nrf2+/+ mice and significantly inhibited the secretion of IL-12 in Nrf2+/+ BM-DCs and IL-18 in Nrf2+/+ and Nrf2−/− BM-DCs. The stimulatory effects of RWE on DC activation were inhibited to varying degrees by the antioxidant N-acetyl cysteine. Our findings indicate that a defect in Nrf2-mediated signaling mechanisms alters the response of DCs to a common environmental allergen, which may contribute to the susceptibility to allergic diseases.
Nrf2; dendritic cells; ragweed extract; antioxidant genes; oxidative stress
Individuals with Lynch syndrome, sometimes referred to as hereditary non-polyposis colorectal cancer (HNPCC), have an increased risk of developing colorectal cancer (CRC) as well as other cancers. The increased risk is due to inherited mutations in mismatch repair (MMR) genes, which reduce the ability of cells to repair DNA damage. Screening for Lynch syndrome in individuals newly diagnosed with colorectal cancer has been proposed as part of a strategy that combines tests and interventions to reduce the risk of colorectal cancer in the relatives of the colorectal cancer patients with Lynch Syndrome.
Oxidative stress is important in dendritic cell (DC) activation. Environmental particulate matter (PM) directs pro-oxidant activities that may alter DC function. Nuclear erythroid 2 p45-related factor 2 (Nrf2) is a redox-sensitive transcription factor that regulates expression of antioxidant and detoxification genes. Oxidative stress and defective antioxidant responses may contribute to the exacerbations of asthma. We hypothesized that PM would impart differential responses by Nrf2 wild-type DCs as compared with Nrf2−/− DCs. We found that the deletion of Nrf2 affected important constitutive functions of both bone marrow-derived and highly purified myeloid lung DCs such as the secretion of inflammatory cytokines and their ability to take up exogenous Ag. Stimulation of Nrf2−/− DCs with PM augmented oxidative stress and cytokine production as compared with resting or Nrf2+/+ DCs. This was associated with the enhanced induction of Nrf2-regulated antioxidant genes. In contrast to Nrf2+/+ DCs, coincubation of Nrf2−/− DCs with PM and the antioxidant N-acetyl cysteine attenuated PM-induced up-regulation of CD80 and CD86. Our studies indicate a previously underappreciated role of Nrf2 in innate immunity and suggest that deficiency in Nrf2-dependent pathways may be involved in susceptibility to the adverse health effects of air pollution in part by promoting Th2 cytokine responses in the absence of functional Nrf2. Moreover, our studies have uncovered a hierarchal response to oxidative stress in terms of costimulatory molecule expression and cytokine secretion in DCs and suggest an important role of heightened oxidative stress in proallergic Th2-mediated immune responses orchestrated by DCs.
Although reported gene variants in the RET oncogene have been directly associated with multiple endocrine neoplasia type 2 and hereditary medullary thyroid carcinoma, other mutations are classified as variants of uncertain significance (VUS) until the associated clinical phenotype is made clear. Currently, some 46 non-synonymous VUS entries exist in curated archives. In the absence of a gold standard method for predicting phenotype outcomes, this follow up study applies feature selected amino acid physical and chemical properties feeding a Bayes classifier to predict disease association of uncertain gene variants into categories of benign and pathogenic. Algorithm performance and VUS predictions were compared to established phylogenetic based mutation prediction algorithms. Curated outcomes and unpublished RET gene variants with known disease association were used to benchmark predictor performance. Reliable classification of RET uncertain gene variants will augment current clinical information of RET mutations and assist in improving prediction algorithms as knowledge increases.
Background & Aims
Colorectal cancer (CRC) risk estimates based on family history typically include only close relatives. We report familial relative risk in probands with various combinations, or constellations, of affected relatives, extending to third-degree.
A population-based resource that includes a computerized genealogy linked to statewide cancer records, was used to identify genetic relationships among CRC cases and their first-, second-, and third-degree relatives (FDRs, SDRs, and TDRs). Familial relative risks (FRRs) were estimated by comparing the observed number of affected individuals with a particular family history constellation to the expected number, based on cohort-specific CRC rates.
A total of 2,327,327 individuals included in ≥3 generation family histories were analyzed; 10,556 had a diagnosis of CRC. The FRR for CRC in individuals with ≥1 affected FDR=2.05 (95% CI 1.96–2.14), consistent with published estimates. In the absence of a positive first-degree family history, considering both affected SDRs and TDRs, only 1 constellation had an FRR estimate that was significantly > 1.0 (0 affected FDRs, 1 affected SDR, 2 affected TDRs; FRR=1.33, 95% CI 1.13–1.55). The FRR for individuals with 1 affected FDR, 1 affected SDR, and 0 affected TDRs=1.88 (95% CI 1.59–2.20), increasing to FRR=3.28 (95% CI 2.44–4.31) for probands with 1 affected FDR, 1 affected SDR, and ≥3 affected TDRs.
Increased numbers of affected FDRs influences risk much more than affected SDRs or TDRs. However, when combined with a positive first-degree family history, a positive second- and third-degree family history can significantly increase risk.
Dendritic cells (DC) are potent professional antigen-presenting cells that drive primary immune responses to infections or other agonists perceived as ‘dangerous’. Muc1 is the only cell surface mucin or MUC gene product that is expressed in DC. Unlike other members of this glycoprotein family, Muc1 possesses a unique cytosolic region capable of signal transduction and attenuating toll-like receptor (TLR) activation. The expression and function of Muc1 has been intensively investigated on epithelial and tumor cells, but relatively little is known about its function on DC. We hypothesized that Muc1 would influence in vitro generation and primary DC activation in response to the TLR4 and TLR5 ligands lipopolysaccharide and flagellin. Compared with Muc1+/+ DC, we found that Muc1−/− DC were constitutively activated, as determined by higher expression of co-stimulatory molecules (CD40, CD80 and CD86), greater secretion of immunoregulatory cytokines (TNF-α and VEGF), and better stimulation of allogeneic naïve CD4+ T cell proliferation. After activation by either LPS or flagellin and co-culture with allogeneic CD4+ T cells, Muc1−/− DC also induced greater secretion of TNF-α and IFN-γ compared to similarly activated Muc1+/+ DC. Taken together, our results indicate that deletion of Muc1 promotes a heightened functional response of DC in response to TLR4 and TLR5 signaling pathways, and suggests a previously under-appreciated role for Muc1 in regulating innate immune responses of DC.
Inflammation; Dendritic cells; Muc1; Toll-like receptor; Innate immunity; Immunomodulation; Host defence; Cytokines
Personalized medicine will require detailed clinical patient profiles, and a particular focus on capturing data that is useful in forecasting risk. A detailed family health history is considered a critical component of these profiles, insomuch that it has been coined as ‘the best genetic test available’. Despite this, tools aimed at capturing this information for use in electronic health records have been characterized as inadequate. In this manuscript we detail the creation of a patient-facing family health history tool known as OurFamilyHealth, whose long-term emphasis is to facilitate risk assessment and clinical decision support. We present the rationale for such a tool, describe its development and release as a component of Intermountain Healthcare’s patient portal, and detail early usage statistics surrounding the application. Data derived from the tool since its release are also compared against family history charting patterns in Intermountain’s electronic health records, revealing differences in data availability.