Deep learning prediction of hospital readmissions for asthma and COPD.

QUESTION: Severe asthma and COPD exacerbations requiring hospitalization are linked to increased disease morbidity and healthcare costs. We sought to identify Electronic Health Record (EHR) features of severe asthma and COPD exacerbations and evaluate the performance of four machine learning (ML) and one deep learning (DL) model in predicting readmissions using EHR data. STUDY DESIGN AND METHODS: Observational study between September 30, 2012, and December 31, 2017, of patients hospitalized with asthma and COPD exacerbations. RESULTS: This study included 5,794 patients, 1,893 with asthma and 3,901 with COPD. Patients with asthma were predominantly female (n = 1288 [68%]), 35% were Black (n = 669), and 25% (n = 479) were Hispanic. Black (44 vs. 33%, p = 0.01) and Hispanic patients (30 vs. 24%, p = 0.02) were more likely to be readmitted for asthma. Similarly, patients with COPD readmissions included a large percentage of Blacks (18 vs. 10%, p < 0.01) and Hispanics (8 vs. 5%, p < 0.01). To identify patients at high risk of readmission index hospitalization data of a subset of 2,682 patients, 777 with asthma and 1,905 with COPD, was analyzed with four ML models, and one DL model. We found that multilayer perceptron, the DL method, had the best sensitivity and specificity compared to the four ML methods implemented in the same dataset. INTERPRETATION: Multilayer perceptron, a deep learning method, had the best performance in predicting asthma and COPD readmissions, demonstrating that EHR and deep learning integration can improve high-risk patient detection.

Differences in Mortality Among Patients With Asthma and COPD Hospitalized With COVID-19.

BACKGROUND: It remains unclear whether patients with asthma and/or chronic obstructive pulmonary disease (COPD) are at increased risk for severe coronavirus disease 2019 (COVID-19). OBJECTIVE: Compare in-hospital COVID-19 outcomes among patients with asthma, COPD, and no airway disease. METHODS: A retrospective cohort study was conducted on 8,395 patients admitted with COVID-19 between March 2020 and April 2021. Airway disease diagnoses were defined using International Classification of Diseases, 10th Revision codes. Mortality and sequential organ failure assessment (SOFA) scores were compared among groups. Logistic regression analysis was used to identify and adjust for confounding clinical features associated with mortality. RESULTS: The median SOFA score in patients without airway disease was 0.32 and mortality was 11%. In comparison, asthma patients had lower SOFA scores (median 0.15; P < .01) and decreased mortality, even after adjusting for age, diabetes, and other confounders (odds ratio 0.65; P = .01). Patients with COPD had higher SOFA scores (median 0.86; P < .01) and increased adjusted odds of mortality (odds ratio 1.40; P < .01). Blood eosinophil count of 200 cells/µL or greater, a marker of type 2 inflammation, was associated with lower mortality across all groups. Importantly, patients with asthma showed improved outcomes even after adjusting for eosinophilia, indicating that noneosinophilic asthma was associated with protection as well. CONCLUSIONS: COVID-19 severity was increased in patients with COPD and decreased in those with asthma, eosinophilia, and noneosinophilic asthma, independent of clinical confounders. These findings suggest that COVID-19 severity may be influenced by intrinsic immunological factors in patients with airway diseases, such as type 2 inflammation.

User centered clinical decision support to implement initiation of buprenorphine for opioid use disorder in the emergency department: EMBED pragmatic cluster randomized controlled trial.

OBJECTIVE: To determine the effect of a user centered clinical decision support tool versus usual care on rates of initiation of buprenorphine in the routine emergency care of individuals with opioid use disorder. DESIGN: Pragmatic cluster randomized controlled trial (EMBED). SETTING: 18 emergency department clusters across five healthcare systems in five states representing the north east, south east, and western regions of the US, ranging from community hospitals to tertiary care centers, using either the Epic or Cerner electronic health record platform. PARTICIPANTS: 599 attending emergency physicians caring for 5047 adult patients presenting with opioid use disorder. INTERVENTION: A user centered, physician facing clinical decision support system seamlessly integrated into user workflows in the electronic health record to support initiating buprenorphine in the emergency department by helping clinicians to diagnose opioid use disorder, assess the severity of withdrawal, motivate patients to accept treatment, and complete electronic health record tasks by automating clinical and after visit documentation, order entry, prescribing, and referral. MAIN OUTCOME MEASURES: Rate of initiation of buprenorphine (administration or prescription of buprenorphine) in the emergency department among patients with opioid use disorder. Secondary implementation outcomes were measured with the RE-AIM (reach, effectiveness, adoption, implementation, and maintenance) framework. RESULTS: 1 413 693 visits to the emergency department (775 873 in the intervention arm and 637 820 in the usual care arm) from November 2019 to May 2021 were assessed for eligibility, resulting in 5047 patients with opioid use disorder (2787 intervention arm, 2260 usual care arm) under the care of 599 attending physicians (340 intervention arm, 259 usual care arm) for analysis. Buprenorphine was initiated in 347 (12.5%) patients in the intervention arm and in 271 (12.0%) patients in the usual care arm (adjusted generalized estimating equations odds ratio 1.22, 95% confidence interval 0.61 to 2.43, P=0.58). Buprenorphine was initiated at least once by 151 (44.4%) physicians in the intervention arm and by 88 (34.0%) in the usual care arm (1.83, 1.16 to 2.89, P=0.01). CONCLUSIONS: User centered clinical decision support did not increase patient level rates of initiating buprenorphine in the emergency department. Although streamlining and automating electronic health record workflows can potentially increase adoption of complex, unfamiliar evidence based practices, more interventions are needed to look at other barriers to the treatment of addiction and increase the rate of initiating buprenorphine in the emergency department in patients with opioid use disorder. TRIAL REGISTRATION: ClinicalTrials.gov NCT03658642.

If you personalize it, will they use it?: Self-reported and observed use of a tailored, internet-based pain self-management program.

Little is known about how individuals with chronic pain use tailored internet-based interventions. This study is the first to compare self-reported skill module use to observed module access and to examine each of these in relationship to tailored recommendations to access specific content. Participants (N = 58) enrolled in a 10-week trial of the Pain EASE program, a tailored internet-based intervention that includes 10 pain self-management skill modules. Participants completed a "Self-Assessment," which was used to provide a "Personalized Plan" that encouraged accessing specific modules. Participants self-reported module use during weekly data collection telephone calls. Program log data were extracted to capture "observed" module use during the trial period. Findings indicated significantly greater self-reported use of the Pain EASE modules compared to observed access with log data. Further, log data revealed that participants accessed less than half of the modules recommended to them via tailoring.

A fast likelihood approach for estimation of large phylogenies from continuous trait data.

Despite the recent availability of large-scale genomic data for many individuals, few methods for phylogenetic inference are both computationally efficient and highly accurate for trees with hundreds of taxa. Model-based methods such as those developed in the maximum likelihood and Bayesian frameworks are especially time-consuming, as they involve both computationally intensive calculations on fixed phylogenies and searches through the space of possible phylogenies, and they are known to scale poorly with the addition of taxa. Here, we propose a fast approximation to the maximum likelihood estimator that directly uses continuous trait data, such as allele frequency data. The approximation works by first computing the maximum likelihood estimates of some internal branch lengths, and then inferring the tree-topology using these estimates. Our approach is more computationally efficient than existing methods for such data while still achieving comparable accuracy. This method is innovative in its use of the mathematical properties of tree-topologies for inference, and thus serves as a useful addition to the collection of methods available for estimating phylogenies from continuous trait data.

Predictors of engagement in an internet-based cognitive behavioral therapy program for veterans with chronic low back pain.

Internet-based interventions for chronic pain have demonstrated efficacy and may address access barriers to care. Participant characteristics have been shown to affect engagement with these programs; however, limited information is available about the relationship between participant characteristics and engagement with internet-based programs for self-management of chronic pain. The current study examined relationships between demographic and clinical characteristics and engagement with the Pain EASE program, a self-directed, internet-based cognitive behavioral therapy intervention for veterans with chronic low back pain (cLBP). Veterans with cLBP were enrolled in a 10 week trial of the Pain EASE program. Engagement measures included the number of logins, access to coping skill modules, and completed study staff-initiated weekly check-in calls. Regression analyses were conducted to identify significant predictors of engagement from hypothesized predictors (e.g., race/ethnicity, age, depressive symptom severity, and pain interference). Participants (N = 58) were 93% male, 60.3% identified as White, and had a mean age of 54.5 years. Participants logged into the program a median of 3.5 times, accessed a median of 2 skill modules, and attended a median of 6 check-in calls. Quantile regression revealed that, at the 50th percentile, non-White-identified participants accessed fewer modules than White-identified participants (p = .019). Increased age was associated with increased module use (p = .001). No clinical characteristics were significantly associated with engagement measures. White-identified race/ethnicity and increased age were associated with greater engagement with the Pain EASE program. Results highlight the importance of defining and increasing engagement in internet-delivered pain care.

A Randomized Trial of a Multifactorial Strategy to Prevent Serious Fall Injuries.

BACKGROUND: Injuries from falls are major contributors to complications and death in older adults. Despite evidence from efficacy trials that many falls can be prevented, rates of falls resulting in injury have not declined. METHODS: We conducted a pragmatic, cluster-randomized trial to evaluate the effectiveness of a multifactorial intervention that included risk assessment and individualized plans, administered by specially trained nurses, to prevent fall injuries. A total of 86 primary care practices across 10 health care systems were randomly assigned to the intervention or to enhanced usual care (the control) (43 practices each). The participants were community-dwelling adults, 70 years of age or older, who were at increased risk for fall injuries. The primary outcome, assessed in a time-to-event analysis, was the first serious fall injury, adjudicated with the use of participant report, electronic health records, and claims data. We hypothesized that the event rate would be lower by 20% in the intervention group than in the control group. RESULTS: The demographic and baseline characteristics of the participants were similar in the intervention group (2802 participants) and the control group (2649 participants); the mean age was 80 years, and 62.0% of the participants were women. The rate of a first adjudicated serious fall injury did not differ significantly between the groups, as assessed in a time-to-first-event analysis (events per 100 person-years of follow-up, 4.9 in the intervention group and 5.3 in the control group; hazard ratio, 0.92; 95% confidence interval [CI], 0.80 to 1.06; P = 0.25). The rate of a first participant-reported fall injury was 25.6 events per 100 person-years of follow-up in the intervention group and 28.6 events per 100 person-years of follow-up in the control group (hazard ratio, 0.90; 95% CI, 0.83 to 0.99; P = 0.004). The rates of hospitalization or death were similar in the two groups. CONCLUSIONS: A multifactorial intervention, administered by nurses, did not result in a significantly lower rate of a first adjudicated serious fall injury than enhanced usual care. (Funded by the Patient-Centered Outcomes Research Institute and others; STRIDE ClinicalTrials.gov number, NCT02475850.).

Interrupted Time Series of User-centered Clinical Decision Support Implementation for Emergency Department-initiated Buprenorphine for Opioid Use Disorder.

OBJECTIVES: Adoption of emergency department (ED) initiation of buprenorphine (BUP) for opioid use disorder (OUD) into routine emergency care has been slow, partly due to clinicians' unfamiliarity with this practice and perceptions that it is complicated and time-consuming. To address these barriers and guide emergency clinicians through the process of BUP initiation, we implemented a user-centered computerized clinical decision support system (CDS). This study was conducted to assess the feasibility of implementation and to evaluate the preliminary efficacy of the intervention to increase the rate of ED-initiated BUP. METHODS: An interrupted time series study was conducted in an urban, academic ED from April 2018 to February 2019 (preimplementation phase), March 2019 to August 2019 (implementation phase), and September 2019 to December 2019 (maintenance phase) to study the effect of the intervention on adult ED patients identified by a validated electronic health record (EHR)-based computable phenotype consisting of structured data consistent with potential cases of OUD who would benefit from BUP treatment. The intervention offers flexible CDS for identification of OUD, assessment of opioid withdrawal, and motivation of readiness to start treatment and automates EHR activities related to ED initiation of BUP (including documentation, orders, prescribing, and referral). The primary outcome was the rate of ED-initiated BUP. Secondary outcomes were launch of the intervention, prescription for naloxone at ED discharge, and referral for ongoing addiction treatment. RESULTS: Of the 141,041 unique patients presenting to the ED over the preimplementation and implementation phases (i.e., the phases used in primary analysis), 906 (574 preimplementation and 332 implementation) met OUD phenotype and inclusion criteria. The rate of BUP initiation increased from 3.5% (20/574) in the preimplementation phase to 6.6% (22/332) in the implementation phase (p = 0.03). After the temporal trend of the number of physician's with X-waiver training and other covariates were adjusted for, the relative risk of BUP initiation rate was 2.73 (95% confidence interval [CI] = 0.62 to 12.0, p = 0.18). Similarly, the number of unique attendings who initiated BUP increased modestly 7/53 (13.0%) to 13/57 (22.8%, p = 0.10) after offering just-in-time training during the implementation period. The rate of naloxone prescribed at discharge also increased (6.5% preimplementation and 11.5% implementation; p < 0.01). The intervention received a system usability scale score of 82.0 (95% CI = 76.7 to 87.2). CONCLUSION: Implementation of user-centered CDS at a single ED was feasible, acceptable, and associated with increased rates of ED-initiated BUP and naloxone prescribing in patients with OUD and a doubling of the number of unique physicians adopting the practice. We have implemented this intervention across several health systems in an ongoing trial to assess its effectiveness, scalability, and generalizability.

Progress Report on EMBED: A Pragmatic Trial of User-Centered Clinical Decision Support to Implement EMergency Department-Initiated BuprenorphinE for Opioid Use Disorder.

Buprenorphine (BUP) can safely and effectively reduce craving, overdose, and mortality rates in people with opioid use disorder (OUD). However, adoption of ED-initiation of BUP has been slow partly due to physician perception this practice is too complex and disruptive. We report progress of the ongoing EMBED (EMergency department-initiated BuprenorphinE for opioid use Disorder) project. This project is a five-year collaboration across five healthcare systems with the goal to develop, integrate, study, and disseminate user-centered Clinical Decision Support (CDS) to promote the adoption of Emergency Department (ED)-initiation of buprenorphine/naloxone (BUP) into routine emergency care. Soon to enter its third year, the project has already completed multiple milestones to achieve its goals including (1) user-centered design of the CDS prototype, (2) integration of the CDS into an automated electronic health record (EHR) workflow, (3) data coordination including derivation and validation of an EHR-based computable phenotype, (4) meeting all ethical and regulatory requirements to achieve a waiver of informed consent, (5) pilot testing of the intervention at a single site, and (6) launching a parallel group-randomized 18-month pragmatic trial in 20 EDs across 5 healthcare systems. Pilot testing of the intervention in a single ED was associated with increased rates of ED-initiated BUP and naloxone prescribing and a doubling of the number of unique physicians adopting the practice. The ongoing multi-center pragmatic trial will assess the intervention's effectiveness, scalability, and generalizability with a goal to shift the emergency care paradigm for OUD towards early identification and treatment. TRIAL REGISTRATION: Clinicaltrials.gov # NCT03658642.

FrogAncestryCalc: A standalone batch likelihood computation tool for ancestry inference panels catalogued in FROG-kb.

The web-based application, FROG-kb (the Forensic Resource/Reference on Genetics-knowledge base, https://frog.med.yale.edu) supports the use of Single Nucleotide Polymorphisms (SNPs) for individual identification and ancestry inference in a forensic setting. The primary functionality provided by FROG-kb on the web is computation of relative likelihoods of populations being the origin of an individual, utilizing the underlying reference population allele frequency data curated and organized in ALFRED, the ALlele FREquency Database (https://alfred.med.yale.edu/). Here we present a downloadable stand-alone tool, FrogAncestryCalc that can simultaneously compute population likelihoods for multiple individuals for a selected panel of SNPs. The program calculates for a given Ancestry Inference (AI) panel the probability of each individual's genotype profile arising in each of the reference populations. Five of the AI panels catalogued in FROG-kb are implemented in this version of FrogAncestryCalc.

Internet-Based Pain Self-Management for Veterans: Feasibility and Preliminary Efficacy of the Pain EASE Program.

OBJECTIVE: To develop and test the feasibility and preliminary efficacy of a cognitive behavioral therapy-based, internet-delivered self-management program for chronic low back pain (cLBP) in veterans. METHODS: Phase I included program development, involving expert panel and participant feedback. Phase II was a single-arm feasibility and preliminary efficacy study of the Pain e-health for Activity, Skills, and Education (Pain EASE) program. Feasibility (ie, website use, treatment credibility, satisfaction) was measured using descriptive methods. Mixed models were used to assess mean within-subject changes from baseline to 10 weeks post-baseline in pain interference (primary outcome, West Haven-Yale Multidimensional Pain Inventory, scale of 0 to 6), pain intensity, mood, fatigue, sleep, and depression. RESULTS: Phase I participants (n = 15) suggested modifications including style changes, content reduction, additional "Test Your Knowledge" quizzes, and cognitive behavioral therapy skill practice monitoring form revisions for enhanced usability. In Phase II, participants (n = 58) were mostly male (93%) and White (60%), and had an average age of 55 years (standard deviation [SD] = 12) and moderate pain (mean score 5.9/10); 41 (71%) completed the post-baseline assessment. Participants (N = 58) logged on 6.1 (SD = 8.6) times over 10 weeks, and 85% reported being very or moderately satisfied with Pain EASE. Pain interference improved from a mean of 3.8 at baseline to 3.3 at 10 weeks (difference 0.5 [95% confidence interval 0.1 to 0.9], P = 0.008). Within-subject improvement also occurred for some secondary outcomes, including mood and depression symptoms. DISCUSSION: Veterans with cLBP may benefit from technology-delivered interventions, which may also reduce pain interference. Overall, veterans found that Pain EASE, an internet-based self-management program, is feasible and satisfactory for cLBP.

Population relationships based on 170 ancestry SNPs from the combined Kidd and Seldin panels.

The benefits of ancestry informative SNP (AISNP) panels can best accrue and be properly evaluated only as sufficient reference population data become readily accessible. Ideally the set of reference populations should approximate the genetic diversity of human populations worldwide. The Kidd and Seldin AISNP sets are two panels that have separately accumulated thus far the largest and most diverse collections of data on human reference populations from the major continental regions. A recent tally in the ALFRED allele frequency database finds 164 reference populations available for all the 55 Kidd AISNPs and 132 reference populations for all the 128 Seldin AISNPs. Although much more of the genetic diversity in human populations around the world still needs to be documented, 81 populations have genotype data available for all 170 AISNPs in the union of the Kidd and Seldin panels. In this report we examine admixture and principal component analyses on these 81 worldwide populations and some regional subsets of these reference populations to determine how well the combined panel illuminates population relationships. Analyses of this dataset that focused on Native American populations revealed very strong cluster patterns associated with many of the individual populations studied.

Genetic relationships of European, Mediterranean, and SW Asian populations using a panel of 55 AISNPs.

The set of 55 ancestry informative SNPs (AISNPs) originally developed by the Kidd Lab has been studied on a large number of populations and continues to be applied to new population samples. The existing reference database of population samples allows the relationships of new population samples to be inferred on a global level. Analyses show that these autosomal markers constitute one of the better panels of AISNPs. Continuing to build this reference database enhances its value. Because more than half of the 25 ethnic groups recently studied with these AISNPs are from Southwest Asia and the Mediterranean region, we present here various analyses focused on populations from these regions along with selected reference populations from nearby regions where genotype data are available. Many of these ethnic groups have not been previously studied for forensic markers. Data on populations from other world regions have also been added to the database but are not included in these focused analyses. The new population samples added to ALFRED and FROG-kb increase the total to 164 population samples that have been studied for all 55 AISNPs.

Improving ancestry distinctions among Southwest Asian populations.

The Kidd Lab panel of 55 AISNPs can provide up to 10 statistically relevant biogeographic groupings of a global set of populations. A second-tier panel would be useful for increasing the accuracy for further differentiation of populations within a specific global grouping. Because recent advances in massively parallel sequencing (MPS) methods allow the genotyping of many more SNPs, we are now identifying additional SNPs to provide refined discrimination among regional subsets of populations; Southwest Asia and the nearby Mediterranean region (SWA) is our current target for such a "second tier" panel. We selected the potentially best SNPs from various sources: our own laboratory database (>4600 SNPs), AISNP panels (Kidd 55 and Seldin 128 SNP panels), and published papers reporting European and SW Asian populations. Rosenberg's Informativeness, Fst, and allele frequency heatmap matrices are used to determine the best SNPs for the region. A total of 2568 individuals, from 39 different populations ranging from North-East Africa through the SW Asia and Europe to the Ural Mountains, were included in the refinement processes and analyses. Heatmap, PCA, Structure (K = 4), and ancestry inference for selected individuals with an in-lab version of FROG-kb analyses indicate that these 86 AISNPs provide the basis for building an improved, optimized panel of AISNPs that collectively provide additional information on differences among populations in that part of the world. Testing this panel with additional populations from the area and with new SNPs and/or microhaplotypes is expected to improve the panel.

Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE): A Cluster-Randomized Pragmatic Trial of a Multifactorial Fall Injury Prevention Strategy: Design and Methods.

Background: Fall injuries are a major cause of morbidity and mortality among older adults. We describe the design of a pragmatic trial to compare the effectiveness of an evidence-based, patient-centered multifactorial fall injury prevention strategy to an enhanced usual care. Methods: Strategies to Reduce Injuries and Develop Confidence in Elders (STRIDE) is a 40-month cluster-randomized, parallel-group, superiority, pragmatic trial being conducted at 86 primary care practices in 10 health care systems across United States. The 86 practices were randomized to intervention or control group using covariate-based constrained randomization, stratified by health care system. Participants are community-living persons, ≥70 years, at increased risk for serious fall injuries. The intervention is a comanagement model in which a nurse Falls Care Manager performs multifactorial risk assessments, develops individualized care plans, which include surveillance, follow-up evaluation, and intervention strategies. Control group receives enhanced usual care, with clinicians and patients receiving evidence-based information on falls prevention. Primary outcome is serious fall injuries, operationalized as those leading to medical attention (nonvertebral fractures, joint dislocation, head injury, lacerations, and other major sequelae). Secondary outcomes include all fall injuries, all falls, and well-being (concern for falling; anxiety and depressive symptoms; physical function and disability). Target sample size was 5,322 participants to provide 90% power to detect 20% reduction in primary outcome rate relative to control. Results: Trial enrolled 5,451 subjects in 20 months. Intervention and follow-up are ongoing. Conclusions: The findings of the STRIDE study will have important clinical and policy implications for the prevention of fall injuries in older adults.

The redesigned Forensic Research/Reference on Genetics-knowledge base, FROG-kb.

The Forensic Resource/Reference on Genetics-knowledge base (FROG-kb) web site was introduced in 2011 and in the five years since the previous publication ongoing research into how the database can better serve forensics has resulted in extensive redesign of the database interface and functionality. Originally designed as a prototype to support forensic use of single nucleotide polymorphisms (SNPs), FROG-kb provides a freely accessible web interface that facilitates forensic practice and can be useful for teaching and research. Based on knowledge gained through its use, the web interface has been redesigned for easier navigation through the multiple components. The site also has functional enhancements, extensive new documentation, and new reference panels of SNPs with new curated data. FROG-kb focuses on single nucleotide polymorphisms (SNPs) and provides reference population data for several published panels of individual identification SNPs (IISNPs) and several published panels of ancestry inference SNPs (AISNPs). For each of the various marker panels with reference population data, FROG-kb calculates random match probabilities (RMP) and relative likelihoods of ancestry for a user-entered genotype profile (either completely or partially specified). Example genotype profiles are available and the User's Manual presents interpretation guidelines for the calculations. The extensive documentation along with ongoing updates makes FROG-kb a comprehensive tool in facilitating use of SNPs in forensic practice and education. An overview of the new FROG-kb with examples and material explaining the results of its use are presented here.

Increasing the reference populations for the 55 AISNP panel: the need and benefits.

Ancestry inference for an individual can only be as good as the reference populations with allele frequency data on the SNPs being used. If the most relevant ancestral population(s) does not have data available for the SNPs studied, then analyses based on DNA evidence may indicate a quite distantly related population, albeit one among the more closely related of the existing reference populations. We have added reference population allele frequencies for 14 additional population samples (with >1100 individuals studied) to the 125 population samples previously published for the Kidd Lab 55 AISNP panel. Allele frequencies are now publicly available for all 55 SNPs in ALFRED and FROG-kb for a total of 139 population samples. This Kidd Lab panel of 55 ancestry informative SNPs has been incorporated in commercial kits by both ThermoFisher Scientific and Illumina for massively parallel sequencing. Researchers employing those kits will find the enhanced set of reference populations useful.

Evaluating a subset of ancestry informative SNPs for discriminating among Southwest Asian and circum-Mediterranean populations.

Many different published sets of single nucleotide polymorphisms (SNPs) and/or insertion-deletion polymorphisms (InDels) can serve as ancestry informative markers (AIMs) to distinguish among continental regions of the world. For a focus on Southwest Asian ancestry we chose to start with the Kidd Lab panel of 55 ancestry-informative SNPs (AISNPs) because it already provided good global reference data (FROG-kb: frog.med.yale.edu) in a set of 73 population samples distinguishing at least 8 biogeographic clusters of populations. This panel serves as a good first tier ancestry panel. We are now interested in identifying region-specific second tier panels for more refined distinction among populations within each of the global regions. We have begun studying the global region centered on Southwest Asia and the region encompassing the Mediterranean Sea. We have incorporated 10 populations from North Africa, Turkey and Iran and included 31 of the original 73 populations and eleven 1000 Genomes Phase3 populations for a total of 3129 individuals from 52 populations, all typed for the 55 AISNPs. We have then identified the subset of the 55 AISNPs that are most informative for this region of the world using Heatmap, Fst, and Informativeness analyses to eliminate those SNPs essentially redundant or providing no information among populations in this region, reducing the number of SNPs to 32. STRUCTURE and PCA analyses show the remaining 32 SNPs identify the North African cluster and appropriately include the Turkish and Iranian samples with the Southwest Asian cluster. These markers provide the basis for building an improved, optimized panel of AISNPs that provides additional information on differences among populations in this part of the world. The data have also allowed an examination of the accuracy of the ancestry inference based on 32 SNPs for the newly studied populations from this region. The likelihood ratio approach to ancestry inference embodied in FROG-kb provides highly significant population assignments within one order of magnitude for each individual in the Turkish, Iranian, and Tunisian populations.

52 additional reference population samples for the 55 AISNP panel.

Ancestry inference for a person using a panel of SNPs depends on the variation of frequencies of those SNPs around the world and the amount of reference data available for calculation/comparison. The Kidd Lab panel of 55 AISNPs has been incorporated in commercial kits by both Life Technologies and Illumina for massively parallel sequencing. Therefore, a larger set of reference populations will be useful for researchers using those kits. We have added reference population allele frequencies for 52 population samples to the 73 previously entered so that there are now allele frequencies publicly available in ALFRED and FROG-kb for a total of 125 population samples.

Application of six IrisPlex SNPs and comparison of two eye color prediction systems in diverse Eurasia populations.

DNA-based prediction for externally visible characteristics such as eye color is already a useful tool in forensic criminal investigations. The IrisPlex system, consisting of six single nucleotide polymorphisms (SNPs) and a prediction model, was developed based on individuals from several European populations. Other recent studies have developed a different prediction model, also based on European populations. In this study, we compared two prediction models using the data for the six IrisPlex SNPs genotyped on 905 individuals from 12 different Eurasian populations. All SNPs showed significant differences in allele frequencies among three groups of populations: European, genetically intermediate (Khanty, Uygur, and Yakut), and East Asian. The two prediction models, the FROG-kb calculation based on the formula of Walsh et al. (2011) and the Snipper calculation from Ruiz et al. (2013), gave identical predictions of brown eye color for the four East Asian populations with complete data but did not give concordant predictions for many individuals in the seven intermediate and European populations. Inconsistencies were mainly conclusive prediction by one model but not the other. Of the 714 individuals with complete 6-locus genotypes, the two models gave 22 % inconsistent predictions. Eliminating the 306 individuals in the Korean and three Chinese populations, in which the predictions were always consistent for brown eye color, the inconsistencies (among the remaining 408 individuals) were 38.7 %. We conclude that more attention should be paid to predictive uncertainty/error. Implementation of both prediction models in future forensic casework is one immediate way to highlight uncertainty.