OBJECTIVES: Use electronic health records Autism Spectrum Disorder (ASD) to assess the comorbidity burden of ASD in children and young adults. STUDY DESIGN: A retrospective prevalence study was performed using a distributed query system across three general hospitals and one pediatric hospital. Over 14,000 individuals under age 35 with ASD were characterized by their co-morbidities and conversely, the prevalence of ASD within these comorbidities was measured. The comorbidity prevalence of the younger (Age<18 years) and older (Age 18-34 years) individuals with ASD was compared. RESULTS: 19.44% of ASD patients had epilepsy as compared to 2.19% in the overall hospital population (95% confidence interval for difference in percentages 13.58-14.69%), 2.43% of ASD with schizophrenia vs. 0.24% in the hospital population (95% CI 1.89-2.39%), inflammatory bowel disease (IBD) 0.83% vs. 0.54% (95% CI 0.13-0.43%), bowel disorders (without IBD) 11.74% vs. 4.5% (95% CI 5.72-6.68%), CNS/cranial anomalies 12.45% vs. 1.19% (95% CI 9.41-10.38%), diabetes mellitus type I (DM1) 0.79% vs. 0.34% (95% CI 0.3-0.6%), muscular dystrophy 0.47% vs 0.05% (95% CI 0.26-0.49%), sleep disorders 1.12% vs. 0.14% (95% CI 0.79-1.14%). Autoimmune disorders (excluding DM1 and IBD) were not significantly different at 0.67% vs. 0.68% (95% CI -0.14-0.13%). Three of the studied comorbidities increased significantly when comparing ages 0-17 vs 18-34 with p<0.001: Schizophrenia (1.43% vs. 8.76%), diabetes mellitus type I (0.67% vs. 2.08%), IBD (0.68% vs. 1.99%) whereas sleeping disorders, bowel disorders (without IBD) and epilepsy did not change significantly. CONCLUSIONS: The comorbidities of ASD encompass disease states that are significantly overrepresented in ASD with respect to even the patient populations of tertiary health centers. This burden of comorbidities goes well beyond those routinely managed in developmental medicine centers and requires broad multidisciplinary management that payors and providers will have to plan for.
For certain research questions related to long-term outcomes or to rare disorders, designing prospective studies is impractical or prohibitively expensive. Such studies could instead utilize clinical and magnetic resonance imaging data (MRI) collected as part of routine clinical care, stored in the electronic medical record (EMR). Using major depressive disorder (MDD) as a disease model, we examined the feasibility of studying brain morphology and associations with remission using clinical and MRI data exclusively drawn from the EMR. Advanced automated tools were used to select MDD patients and controls from the EMR who had brain MRI data, but no diagnosed brain pathology. MDD patients were further assessed for remission status by review of clinical charts. Twenty MDD patients (eight full-remitters, six partial-remitters, and six non-remitters), and 15 healthy control subjects met all study criteria for advanced morphometric analyses. Compared to controls, MDD patients had significantly smaller right rostral-anterior cingulate volume, and level of non-remission was associated with smaller left hippocampus and left rostral-middle frontal gyrus volume. The use of EMR data for psychiatric research may provide a timely and cost-effective approach with the potential to generate large study samples reflective of the real population with the illness studied.
Objectives. Treatment-resistant depression is a common clinical occurrence among patients with major depressive disorder (MDD), but its neurobiology is poorly understood. We used data collected as part of routine clinical care to study white matter integrity of the brain's limbic system and its association to treatment response. Methods. Electronic medical records of multiple large New England hospitals were screened for patients with an MDD billing diagnosis, and natural language processing was subsequently applied to find those with concurrent diffusion-weighted images, but without any diagnosed brain pathology. Treatment outcome was determined by review of clinical charts. MDD patients (n = 29 non-remitters, n = 26 partial-remitters, and n = 37 full-remitters), and healthy control subjects (n = 58) were analyzed for fractional anisotropy (FA) of the fornix and cingulum bundle. Results. Failure to achieve remission was associated with lower FA among MDD patients, statistically significant for the medial body of the fornix. Moreover, global and regional-selective age-related FA decline was most pronounced in patients with treatment-refractory, non-remitted depression. Conclusions. These findings suggest that specific brain microstructural white matter abnormalities underlie persistent, treatment-resistant depression. They also demonstrate the feasibility of investigating white matter integrity in psychiatric populations using legacy data.
Genome-wide screening is anticipated to accelerate the development of personalized medicine by identifying and exploiting new associations between genomic variants and drug responses. However, this goal could be undermined if care is not taken to minimize the impact of pharmacogenomic associations that turn out to have narrower implications than suggested by initial studies.
Purpose:With the advent of whole-genome sequencing made clinically available, the number of incidental findings is likely to rise. The false-positive incidental findings are of particular clinical concern. We provide estimates on the size of these false-positive findings and classify them into four broad categories.Methods:Whole-genome sequences (WGS) of nine individuals were scanned with several comprehensive public annotation databases and average estimates for the number of findings. These estimates were then evaluated in the perspective of various sources of false-positive annotation errors.Results:At present there are four main sources of false-positive incidental findings: erroneous annotations, sequencing error, incorrect penetrance estimates, and multiple hypothesis testing. Of these, the first two are likely to be addressed in the near term. Conservatively, current methods deliver hundreds of false-positive incidental findings per individual.Conclusion:The burden of false-positives in whole-genome sequence interpretation threatens current capabilities to deliver clinical-grade whole-genome clinical interpretation. A new generation of population studies and retooling of the clinical decision-support approach will be required to overcome this threat.Genet Med advance online publication 9 February 2012.
OBJECTIVE It has been suggested that there is a mechanism by which nonsteroidal anti-inflammatory drugs (NSAIDs) may interfere with antidepressant response, and poorer outcomes among NSAID-treated patients were reported in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. To attempt to confirm this association in an independent population-based treatment cohort and explore potential confounding variables, the authors examined use of NSAIDs and related medications among 1,528 outpatients in a New England health care system. METHOD Treatment outcomes were classified using a validated machine learning tool applied to electronic medical records. Logistic regression was used to examine the association between medication exposure and treatment outcomes, adjusted for potential confounding variables. To further elucidate confounding and treatment specificity of the observed effects, data from the STAR*D study were reanalyzed. RESULTS NSAID exposure was associated with a greater likelihood of depression classified as treatment resistant compared with depression classified as responsive to selective serotonin reuptake inhibitors (odds ratio=1.55, 95% CI=1.21-2.00). This association was apparent in the NSAIDs-only group but not in those using other agents with NSAID-like mechanisms (cyclooxygenase-2 inhibitors and salicylates). Inclusion of age, sex, ethnicity, and measures of comorbidity and health care utilization in regression models indicated confounding; association with outcome was no longer significant in fully adjusted models. Reanalysis of STAR*D results likewise identified an association in NSAIDs but not NSAID-like drugs, with more modest effects persisting after adjustment for potential confounding variables. CONCLUSIONS These results support an association between NSAID use and poorer antidepressant outcomes in major depressive disorder but indicate that some of the observed effect may be a result of confounding.
Adenosine-to-inosine (A-to-I) RNA editing is a neurodevelopmentally regulated epigenetic modification shown to modulate complex behavior in animals. Little is known about human A-to-I editing, but it is thought to constitute one of many molecular mechanisms connecting environmental stimuli and behavioral outputs. Thus, comprehensive exploration of A-to-I RNA editing in human brains may shed light on gene-environment interactions underlying complex behavior in health and disease. Synaptic function is a main target of A-to-I editing, which can selectively recode key amino acids in synaptic genes, directly altering synaptic strength and duration in response to environmental signals. Here, we performed a high-resolution survey of synaptic A-to-I RNA editing in a human population, and examined how it varies in autism, a neurodevelopmental disorder in which synaptic abnormalities are a common finding. Using ultra-deep (>1000 x ) sequencing, we quantified the levels of A-to-I editing of 10 synaptic genes in postmortem cerebella from 14 neurotypical and 11 autistic individuals. A high dynamic range of editing levels was detected across individuals and editing sites, from 99.6% to below detection limits. In most sites, the extreme ends of the population editing distributions were individuals with autism. Editing was correlated with isoform usage, clusters of correlated sites were identified, and differential editing patterns examined. Finally, a dysfunctional form of the editing enzyme adenosine deaminase acting on RNA B1 was found more commonly in postmortem cerebella from individuals with autism. These results provide a population-level, high-resolution view of A-to-I RNA editing in human cerebella and suggest that A-to-I editing of synaptic genes may be informative for assessing the epigenetic risk for autism.Molecular Psychiatry advance online publication, 7 August 2012; doi:10.1038/mp.2012.118.
Adenosine-to-inosine (A-to-I) RNA editing is a neurodevelopmentally regulated epigenetic modification shown to modulate complex behavior in animals. Little is known about human A-to-I editing, but it is thought to constitute one of many molecular mechanisms connecting environmental stimuli and behavioral outputs. Thus, comprehensive exploration of A-to-I RNA editing in human brains may shed light on gene-environment interactions underlying complex behavior in health and disease. Synaptic function is a main target of A-to-I editing, which can selectively recode key amino acids in synaptic genes, directly altering synaptic strength and duration in response to environmental signals. Here, we performed a high-resolution survey of synaptic A-to-I RNA editing in a human population, and examined how it varies in autism, a neurodevelopmental disorder in which synaptic abnormalities are a common finding. Using ultra-deep (>1000 × ) sequencing, we quantified the levels of A-to-I editing of 10 synaptic genes in postmortem cerebella from 14 neurotypical and 11 autistic individuals. A high dynamic range of editing levels was detected across individuals and editing sites, from 99.6% to below detection limits. In most sites, the extreme ends of the population editing distributions were individuals with autism. Editing was correlated with isoform usage, clusters of correlated sites were identified, and differential editing patterns examined. Finally, a dysfunctional form of the editing enzyme adenosine deaminase acting on RNA B1 was found more commonly in postmortem cerebella from individuals with autism. These results provide a population-level, high-resolution view of A-to-I RNA editing in human cerebella and suggest that A-to-I editing of synaptic genes may be informative for assessing the epigenetic risk for autism.Molecular Psychiatry advance online publication, 7 August 2012; doi:10.1038/mp.2012.118.
Aberrant DNA hypermethylation of tumor suppressor genes is thought to be an early event in tumorigenesis. Many studies have reported the methylation status of individual genes with known involvement in cancer, but an unbiased assessment of the biological function of the collective of hypermethylated genes has not been conducted so far. Based on the observation that a variety of human cancers recapitulate developmental gene expression patterns (that is activate genes normally expressed in early development and suppress late developmental genes), we hypothesized that the silencing of differentiation-associated genes in cancer could be attributed in part to DNA hypermethylation. To this end, we investigated the developmental expression patterns of genes with hypermethylated CpG islands in primary human lung carcinomas and lung cancer cell lines. We found that DNA hypermethylation primarily affects genes that are expressed in late stages of murine lung development. Gene ontology characterization of these genes shows that they are almost exclusively involved in morphogenetic differentiation processes. Our results indicate that DNA hypermethylation in cancer functions as a selective silencing mechanism of genes that are required for the maintenance of a differentiated state. The process of cellular de-differentiation that is evident on both the microscopic and transcriptional level in cancer might at least partly be mediated by these epigenetic events. Our observations provide a mechanistic explanation for induction of differentiation upon treatment with DNA methyltransferase inhibitors.
OBJECTIVE: To examine the association between exposure to newer antidepressants and risk of gastrointestinal (GI) and other bleeding complications among individuals with major depressive disorder (MDD). DESIGN: This study uses an incident user cohort design to compare associations between incidence of vascular/bleeding events and the relative affinity (low, moderate or high) of the antidepressant for the serotonin transporter during an exposure risk period for each patient. SETTING: New England healthcare system electronic medical record database. PARTICIPANTS: 36 389 individuals with a diagnosis of MDD and monotherapy with a selective serotonin reuptake inhibitor, serotonin-norepinephrine reuptake inhibitor or other new-generation antidepressant were identified from among 3.1 million patients in a New England healthcare system. PRIMARY AND SECONDARY OUTCOME MEASURES: Rates of bleeding or other vascular complications, including acute liver failure, acute renal failure, asthma, breast cancer and hip fractures. RESULTS: 601 GI bleeds were observed in the 21 462 subjects in the high-affinity group versus 333 among the 14 927 subjects in the lower affinity group (adjusted RR: 1.17, 95% CI 1.02 to 1.34). Similarly, 776 strokes were observed in the high-affinity group versus 434 in the lower affinity treatment group (adjusted RR: 1.18, 95% CI 1.06 to 1.32). No significant association with risk for a priori negative control outcomes, including acute liver failure, acute renal failure, asthma, breast cancer and hip fractures, was identified. CONCLUSIONS: Use of antidepressants with high affinity for the serotonin transporter may confer modestly elevated risk for GI and other bleeding complications. While multiple methodologic limitations must be considered, these results suggest that antidepressants with lower serotonin receptor affinity may be preferred in patients at greater risk for such complications.
We are entering an era in which the cost of clinical whole-genome and targeted sequencing tests is no longer prohibitive to their application. However, currently the infrastructure is not in place to support both the patient and the physicians that encounter the resultant data. Here, we ask five experts to give their opinions on whether clinical data should be treated differently from other medical data, given the potential use of these tests, and on the areas that must be developed to improve patient outcome.
BACKGROUND: The increasing incidence of Clostridium difficile (C. difficile) infection (CDI) among patients with inflammatory bowel disease is well recognised. However, most studies have focused on demonstrating that CDI is associated with adverse outcomes in IBD patients. Few have attempted to identify predictors of severe outcomes associated with CDI among IBD patients. AIM: To identify clinical and laboratory factors that predict severe outcomes associated with CDI in IBD patients. METHODS: From a multi-institution EMR database, we identified all hospitalised patients with at least one diagnosis code for C. difficile from among those with a diagnosis of Crohn's disease or ulcerative colitis. Our primary outcome was time to total colectomy or death with follow-up censored at 180 days after CDI. Cox proportional hazards models were used to identify predictors of the primary outcome from among demographic, disease-related, laboratory and medication variables. RESULTS: A total of 294 patients with CDI-IBD were included in our study. Of these, 58 patients (20%) met our primary outcome (45 deaths, 13 colectomy) at a median of 31 days. On multivariate analysis, serum albumin <3 g/dL (HR 5.75, 95% CI 1.34-24.56), haemoglobin below 9 g/dL (HR 5.29, 95% CI 1.58-17.69) and creatinine above 1.5 mg/dL (HR 1.98, 95% CI 1.04-3.79) were independent predictors of our primary outcome. Examining laboratory parameters as continuous variables or shortening our primary outcome to include events within 90 days yielded similar results. CONCLUSION: Serum albumin below 3 g/dL, haemoglobin below 9 g/dL and serum creatinine above 1.5 mg/dL were independent predictors of severe outcomes in hospitalised IBD patients with Clostridium difficile infection.
SUMMARY: Accurate annotations of genomic variants are necessary to achieve full-genome clinical interpretations that are scientifically sound and medically relevant. Many disease associations, especially those reported before the completion of the HGP, are limited in applicability because of potential inconsistencies with our current standards for genomic coordinates, nomenclature and gene structure. In an effort to validate and link variants from the medical genetics literature to an unambiguous reference for each variant, we developed a software pipeline and reviewed 68,641 single amino acid mutations from OMIM, HGMD, and dbSNP. The frequency of unresolved mutation annotations varied widely among the databases, ranging from 4% to 23%. A taxonomy of primary causes for unresolved mutations was produced. AVALIABILITY: This program is freely available from the web site (http://safegene.hms.harvard.edu/aa2nt/).
Platelet-derived growth factor receptors (PDGFRs) have been implicated in a wide array of human malignancies, including medulloblastoma (MB), the most common brain tumor of childhood. Although significant progress in MB biology and therapeutics has been achieved during the past decades, MB remains a horrible challenge to the physicians and researchers. Therefore, novel inhibitors targeting PDGFR signaling pathway may offer great promise for the treatment of MB. In the present study, we investigated the cytotoxicity and mechanisms of cambogin in Daoy MB cells. Our results show that cambogin triggers significant S phase cell cycle arrest and apoptosis via down regulation of cyclin A and E, and activation of caspases. More importantly, further mechanistic studies demonstrated that cambogin inhibits PDGFR signaling in Daoy and genetically defined mouse embryo fibroblast (MEF) cell lines. These results suggest that cambogin is preferentially cytotoxic to cells expressing PDGFR. Our findings may provide a novel approach by targeting PDGFR signaling against MB.
The lipid-lowering agent pravastatin and the antidepressant paroxetine are among the most widely prescribed drugs in the world. Unexpected interactions between them could have important public health implications. We mined the US Food and Drug Administration's (FDA's) Adverse Event Reporting System (AERS) for side-effect profiles involving glucose homeostasis and found a surprisingly strong signal for comedication with pravastatin and paroxetine. We retrospectively evaluated changes in blood glucose in 104 patients with diabetes and 135 without diabetes who had received comedication with these two drugs, using data in electronic medical record (EMR) systems of three geographically distinct sites. We assessed the mean random blood glucose levels before and after treatment with the drugs. We found that pravastatin and paroxetine, when administered together, had a synergistic effect on blood glucose. The average increase was 19 mg/dl (1.0 mmol/l) overall, and in those with diabetes it was 48 mg/dl (2.7 mmol/l). In contrast, neither drug administered singly was associated with such changes in glucose levels. An increase in glucose levels is not a general effect of combined therapy with selective serotonin reuptake inhibitors (SSRIs) and statins.