Person:

Ananthakrishnan, Ashwin

Objective: To optimally leverage the scalability and unique features of the electronic health records (EHR) for research that would ultimately improve patient care, we need to accurately identify patients and extract clinically meaningful measures. Using multiple sclerosis (MS) as a proof of principle, we showcased how to leverage routinely collected EHR data to identify patients with a complex neurological disorder and derive an important surrogate measure of disease severity heretofore only available in research settings. Methods: In a cross-sectional observational study, 5,495 MS patients were identified from the EHR systems of two major referral hospitals using an algorithm that includes codified and narrative information extracted using natural language processing. In the subset of patients who receive neurological care at a MS Center where disease measures have been collected, we used routinely collected EHR data to extract two aggregate indicators of MS severity of clinical relevance multiple sclerosis severity score (MSSS) and brain parenchymal fraction (BPF, a measure of whole brain volume). Results: The EHR algorithm that identifies MS patients has an area under the curve of 0.958, 83% sensitivity, 92% positive predictive value, and 89% negative predictive value when a 95% specificity threshold is used. The correlation between EHR-derived and true MSSS has a mean R2 = 0.38±0.05, and that between EHR-derived and true BPF has a mean R2 = 0.22±0.08. To illustrate its clinical relevance, derived MSSS captures the expected difference in disease severity between relapsing-remitting and progressive MS patients after adjusting for sex, age of symptom onset and disease duration (p = 1.56×10−12). Conclusion: Incorporation of sophisticated codified and narrative EHR data accurately identifies MS patients and provides estimation of a well-accepted indicator of MS severity that is widely used in research settings but not part of the routine medical records. Similar approaches could be applied to other complex neurological disorders.

Background: Early life exposures may modify risk of inflammatory bowel diseases (IBD; Crohn’s disease (CD), ulcerative colitis (UC)). However, the relationship between early life exposures and natural history of IBD has not been previously examined. Methods: This single center study included patients with CD or UC recruited in a prospective IBD registry. Enrolled patients completed a detailed environmental questionnaire that assessed various early life environmental exposures. Our primary outcome was requirement for disease-related surgery in CD and UC. Logistic regression models defined independent effect of early life exposures, adjusting for potential confounders. Results: Our study included 333 CD and 270 UC patients. Just over half were female with a median age at diagnosis of 25 years. One-third of the cohort had history of bowel surgery (31%) and nearly half had used at least one biologic agent (47%). Among those with CD, being breastfed was associated with reduced risk of CD-related surgery (34% vs. 55%), while childhood cigarette smoke exposure was associated with increased risk. On multivariate analysis, history of being breastfed (odds ratio (OR) 0.21, 95% confidence interval [CI] 0.09–0.46) and cigarette smoke exposure as a child (OR 2.17, 95% CI 1.10–4.29) remained independently associated with surgery. None of the early life variables influenced disease phenotype or outcome in UC. Conclusion: A history of being breastfed was associated with a decreased risk while childhood cigarette smoke exposure was associated with an increased risk of surgery in patients with CD. Further investigation to examine biological mechanisms is warranted. Electronic supplementary material The online version of this article (doi:10.1186/s12876-014-0216-8) contains supplementary material, which is available to authorized users.

Objective: To examine the association between physical activity and risk of ulcerative colitis and Crohn’s disease. Design: Prospective cohort study. Setting: Nurses’ Health Study and Nurses’ Health Study II. Participants: 194 711 women enrolled in the Nurses’ Health Study and Nurses’ Health Study II who provided data on physical activity and other risk factors every two to four years since 1984 in the Nurses’ Health Study and 1989 in the Nurses’ Health Study II and followed up through 2010. Main outcome measure Incident ulcerative colitis and Crohn’s disease. Results: During 3 421 972 person years of follow-up, we documented 284 cases of Crohn’s disease and 363 cases of ulcerative colitis. The risk of Crohn’s disease was inversely associated with physical activity (P for trend 0.02). Compared with women in the lowest fifth of physical activity, the multivariate adjusted hazard ratio of Crohn’s disease among women in the highest fifth of physical activity was 0.64 (95% confidence interval 0.44 to 0.94). Active women with at least 27 metabolic equivalent task (MET) hours per week of physical activity had a 44% reduction (hazard ratio 0.56, 95% confidence interval 0.37 to 0.84) in risk of developing Crohn’s disease compared with sedentary women with <3 MET h/wk. Physical activity was not associated with risk of ulcerative colitis (P for trend 0.46). The absolute risk of ulcerative colitis and Crohn’s disease among women in the highest fifth of physical activity was 8 and 6 events per 100 000 person years compared with 11 and 16 events per 100 000 person years among women in the lowest fifth of physical activity, respectively. Age, smoking, body mass index, and cohort did not significantly modify the association between physical activity and risk of ulcerative colitis or Crohn’s disease (all P for interaction >0.35). Conclusion: In two large prospective cohorts of US women, physical activity was inversely associated with risk of Crohn’s disease but not of ulcerative colitis.

Crohn’s disease (CD) and ulcerative colitis (UC), the two common forms of inflammatory bowel disease (IBD), affect over 2.5 million people of European ancestry with rising prevalence in other populations1. Genome-wide association studies (GWAS) and subsequent meta-analyses of CD and UC2,3 as separate phenotypes implicated previously unsuspected mechanisms, such as autophagy4, in pathogenesis and showed that some IBD loci are shared with other inflammatory diseases5. Here we expand knowledge of relevant pathways by undertaking a meta-analysis of CD and UC genome-wide association scans, with validation of significant findings in more than 75,000 cases and controls. We identify 71 new associations, for a total of 163 IBD loci that meet genome-wide significance thresholds. Most loci contribute to both phenotypes, and both directional and balancing selection effects are evident. Many IBD loci are also implicated in other immune-mediated disorders, most notably with ankylosing spondylitis and psoriasis. We also observe striking overlap between susceptibility loci for IBD and mycobacterial infection. Gene co-expression network analysis emphasizes this relationship, with pathways shared between host responses to mycobacteria and those predisposing to IBD.

Background & Aims Microbial dysbiosis and aberrant host–microbe interactions in the gut are believed to contribute to the development and progression of Crohn’s disease (CD). Microbiome studies in CD typically have focused on microbiota in feces or superficial mucosal layers of the colon because accessing DNA from deeper layers of the bowel is challenging. In this study, we analyzed the deep tissue microbiome in patients who underwent surgical resection of the small intestine. Methods: Paraffin blocks were obtained from 12 CD patients undergoing ileocecal resection, and healthy ileum samples (inflammatory bowel disease–free controls) were obtained from 12 patients undergoing surgery for right-sided colon cancer. Diseased and healthy-appearing ileum was identified using microscopy, and paraffin blocks were macrodissected using a core needle to specifically isolate DNA. Illumina Whole Genome Sequencing was used for microbial sequence identification and subsequent taxonomic classification using the PathSeq tool. Results: We observed significant differences between the microbiome of CD samples vs inflammatory bowel disease–free controls, including depletion of Bacteroidetes and Clostridia. Notably, microbial composition at the phyla level did not differ markedly between healthy and diseased areas of CD patients. However, we observed enrichment of potentially pathogenic organisms at the species level. Conclusions: Our study showed dysbiosis within deeper layers of the ileum of CD patients, specifically enrichment of enterotoxigenic Staphylococcus aureus and an environmental Mycobacterium species not described previously. Future studies with larger cohort sizes are warranted to confirm these findings. Studies would benefit from effective microbial DNA extraction methods from paraffin sections and host nucleic acid depletion approaches to increase microbial read coverage.

Background: Clostridium difficile infection (CDI) is the most common healthcare associated infection and is highly prevalent in Europe and North America. Limited data is available on the prevalence of CDI in Asia. However, secular increases in prevalence of risk factors for CDI suggest that it may be emerging as a major cause of morbidity, highlighting the urgent need for a systematic study of the prevalence of CDI in Asia. Methods: We systematically searched PubMed/Medline and Embase for publications from Asia between 2000–16 examining prevalence of CDI. A random-effects meta-analysis was performed to calculate the pooled prevalence of CDI in Asia and to identify subgroups and regions at high risk. Results: Our meta-analysis included 51 studies from throughout Asia including 37,663 patients at risk among whom confirmed CDI was found in 4,343 patients. The pooled proportion of confirmed CDI among all patients with diarrhea was 14.8% with a higher prevalence in East Asia (19.5%), compared with South Asia (10.5%) or the Middle East (11.1%). There were an estimated 5.3 episodes of CDI per 10,000 patient days, similar to rates reported from Europe and North America. Infections due to hypervirulent strains were rare. CDI-related mortality was 8.9%. Conclusions: In a meta-analysis of 51 studies, we observed similar rates of CDI in Asia in comparison to Europe and North America. Increased awareness and improved surveillance of Clostridium difficile is essential to reduce incidence and morbidity.

Background: Androgens, which are known to be altered by exogenous hormone use, have recently been linked to alterations of the gut microbiome and mucosal immune function. No study has evaluated the association between circulating levels of androgens and risk of Crohn's disease (CD) and ulcerative colitis (UC). Methods: We conducted a nested case–control study of women enrolled in the Nurses' Health Study and Nurses' Health Study II who provided a blood specimen. Cases of CD and UC were each matched to 2 controls. Prediagnosis plasma levels of dehydroepiandrosterone sulfate, testosterone, and sex hormone–binding globulin were measured. We examined the association of each analyte with risk of CD or UC using conditional logistic regression models. Results: Compared with women in the lowest quintile of testosterone, the multivariable-adjusted odds ratios for CD were 0.86 (95% confidence interval, 0.39–1.90) for women in the second quintile, 0.49 (95% confidence interval, 0.21–1.15) for the third quartile, 0.22 (0.08–0.65) for the fourth quintile, and 0.39 (95% confidence interval, 0.16–0.99) for the highest quintile (Plinear trend = 0.004). In contrast, we did not observe a consistent association between prediagnostic testosterone and risk of UC (Plinear trend = 0.84). We also did not observe any association between plasma levels of sex hormone–binding globulin or dehydroepiandrosterone sulfate and risk of UC or CD (all Plinear trends > 0.10). Conclusions: Among women, prediagnostic circulating testosterone is associated with a lower risk of CD but not UC. Further studies to understand the biological mechanisms by which endogenous androgens may mediate the etiopathogenesis of CD are warranted.

Protein-truncating variants protective against human disease provide in vivo validation of therapeutic targets. Here we used targeted sequencing to conduct a search for protein-truncating variants conferring protection against inflammatory bowel disease exploiting knowledge of common variants associated with the same disease. Through replication genotyping and imputation we found that a predicted protein-truncating variant (rs36095412, p.R179X, genotyped in 11,148 ulcerative colitis patients and 295,446 controls, MAF=up to 0.78%) in RNF186, a single-exon ring finger E3 ligase with strong colonic expression, protects against ulcerative colitis (overall P=6.89 × 10−7, odds ratio=0.30). We further demonstrate that the truncated protein exhibits reduced expression and altered subcellular localization, suggesting the protective mechanism may reside in the loss of an interaction or function via mislocalization and/or loss of an essential transmembrane domain.

Electronic medical records are emerging as a major source of data for clinical and translational research studies, although phenotypes of interest need to be accurately defined first. This article provides an overview of how to develop a phenotype algorithm from electronic medical records, incorporating modern informatics and biostatistics methods.

Background: Typically, algorithms to classify phenotypes using electronic medical record (EMR) data were developed to perform well in a specific patient population. There is increasing interest in analyses which can allow study of a specific outcome across different diseases. Such a study in the EMR would require an algorithm that can be applied across different patient populations. Our objectives were: (1) to develop an algorithm that would enable the study of coronary artery disease (CAD) across diverse patient populations; (2) to study the impact of adding narrative data extracted using natural language processing (NLP) in the algorithm. Additionally, we demonstrate how to implement CAD algorithm to compare risk across 3 chronic diseases in a preliminary study. Methods and Results: We studied 3 established EMR based patient cohorts: diabetes mellitus (DM, n = 65,099), inflammatory bowel disease (IBD, n = 10,974), and rheumatoid arthritis (RA, n = 4,453) from two large academic centers. We developed a CAD algorithm using NLP in addition to structured data (e.g. ICD9 codes) in the RA cohort and validated it in the DM and IBD cohorts. The CAD algorithm using NLP in addition to structured data achieved specificity >95% with a positive predictive value (PPV) 90% in the training (RA) and validation sets (IBD and DM). The addition of NLP data improved the sensitivity for all cohorts, classifying an additional 17% of CAD subjects in IBD and 10% in DM while maintaining PPV of 90%. The algorithm classified 16,488 DM (26.1%), 457 IBD (4.2%), and 245 RA (5.0%) with CAD. In a cross-sectional analysis, CAD risk was 63% lower in RA and 68% lower in IBD compared to DM (p<0.0001) after adjusting for traditional cardiovascular risk factors. Conclusions: We developed and validated a CAD algorithm that performed well across diverse patient populations. The addition of NLP into the CAD algorithm improved the sensitivity of the algorithm, particularly in cohorts where the prevalence of CAD was low. Preliminary data suggest that CAD risk was significantly lower in RA and IBD compared to DM.