Using LASSO regression to detect predictive aggregate effects in genetic studies

We use least absolute shrinkage and selection operator (LASSO) regression to select genetic markers and phenotypic features that are most informative with respect to a trait of interest. We compare several strategies for applying LASSO methods in risk prediction models, using the Genetic Analysis Workshop 17 exome simulation data consisting of 697 individuals with information on genotypic and phenotypic features (smoking, age, sex) in 5-fold cross-validated fashion. The cross-validated averages of the area under the receiver operating curve range from 0.45 to 0.63 for different strategies using only genotypic markers. The same values are improved to 0.69–0.87 when both genotypic and phenotypic information are used. The ability of the LASSO method to find true causal markers is limited, but the method was able to discover several common variants (e.g., FLT1) under certain conditions

2019 American College of Rheumatology/Arthritis Foundation Guideline for the Management of Osteoarthritis of the Hand, Hip, and Knee

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153772/1/acr24131.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153772/2/acr24131_am.pd

Integrative Analysis Strategies for Discovering Genetic Associations with Common Diseases

Genetic association studies have proven to be successful at identifying reliable associations with complex diseases. However, the majority of these results are uninformative with respect to any functional basis, and more research is necessary appreciate the mechanisms by which these associations are related to pathogenic molecular alterations. In this project, we propose a number of computational approaches to address current challenges in genome-wide association studies: detection of gene-gene interactions, utilization of high performance computing resources, development of genomic risk prediction tools, and investigation into miRNA-associated variations that may lead to problematic modulations in transcriptional activity. First, we present an adaptive evolutionary optimization algorithm that utilizes local linkage disequilibrium patterns to improve the search for gene-gene interactions associated with a phenotype of interest. Our method was applied to several simulated disease models and to a real genome-wide association study. The results indicate that our method has improved power and computational efficiency for uncovering gene-gene interactions relative to one of the most powerful competing methods. This optimization strategy was extended into a parallel algorithm that uses state of the art computing methods involving graphics processing units to explore genome-wide association study data sets with maximal computational efficiency and minimal cost. Next, we present an improved penalized lasso regression strategy to build more accurate predictions of disease risk based on genomic and phenotypic information for case control studies. Using this approach on a simulated data set from the 1000 Genomes project, we were able to model disease risk using common and rare genetic variation in combination with quantitative trait information. Lastly, we present a framework for the determination of genomic variation associated with miRNA dysregulation. We applied our analysis method to several genome-wide association studies of common diseases to determine candidate targets for disease-associated dysfunctions in miRNA-related gene expression changes. The research in this thesis represents a set of computational tools and integrative analysis strategies that can be used to provide a detailed description of the genetic risk associated with a potentially complex inherited phenotype. Code developed in this project will be made available to the research community for further development and application to other genome-wide association studies

FoxM1 Regulates Mammary Luminal Cell Fate

Elevated expression of FoxM1 in breast cancer correlates with an undifferentiated tumor phenotype and a negative clinical outcome. However, a role for FoxM1 in regulating mammary differentiation was not known. Here, we identify another function of FoxM1, the ability to act as a transcriptional repressor, which plays an important role in regulating the differentiation of luminal epithelial progenitors. Regeneration of mammary glands with elevated levels of FoxM1 leads to aberrant ductal morphology and expansion of the luminal progenitor pool. Conversely, knockdown of FoxM1 results in a shift toward the differentiated state. FoxM1 mediates these effects by repressing the key regulator of luminal differentiation, GATA-3. Through association with DNMT3b, FoxM1 promotes methylation of the GATA-3 promoter in an Rb-dependent manner. This study identifies FoxM1 as a critical regulator of mammary differentiation with significant implications for the development of aggressive breast cancers

Free Flap Reconstruction Monitoring Techniques and Frequency in the Era of Restricted Resident Work Hours

Importance: Free flap reconstruction of the head and neck is routinely performed with success rates around 94% to 99% at most institutions. Despite experience and meticulous technique, there is a small but recognized risk of partial or total flap loss in the postoperative setting. Historically, most microvascular surgeons involve resident house staff in flap monitoring protocols, and programs relied heavily on in-house resident physicians to assure timely intervention for compromised flaps. In 2003, the Accreditation Council for Graduate Medical Education mandated the reduction in the hours a resident could work within a given week. At many institutions this new era of restricted resident duty hours reshaped the protocols used for flap monitoring to adapt to a system with reduced resident labor. Objectives: To characterize various techniques and frequencies of free flap monitoring by nurses and resident physicians; and to determine if adapted resident monitoring frequency is associated with flap compromise and outcome. Design, Setting, and Participants: This multi-institutional retrospective review included patients undergoing free flap reconstruction to the head and/or neck between January 2005 and January 2015. Consecutive patients were included from different academic institutions or tertiary referral centers to reflect evolving practices. Main Outcomes and Measures: Technique, frequency, and personnel for flap monitoring; flap complications; and flap success. Results: Overall, 1085 patients (343 women [32%] and 742 men [78%]) from 9 institutions were included. Most patients were placed in the intensive care unit postoperatively (n = 790 [73%]), while the remaining were placed in intermediate care (n = 201 [19%]) or in the surgical ward (n = 94 [7%]). Nurses monitored flaps every hour (q1h) for all patients. Frequency of resident monitoring varied, with 635 patients monitored every 4 hours (q4h), 146 monitored every 8 hours (q8h), and 304 monitored every 12 hours (q12h). Monitoring techniques included physical examination (n = 949 [87%]), handheld external Doppler sonography (n = 739 [68%]), implanted Doppler sonography (n = 333 [31%]), and needle stick (n = 349 [32%]); 105 patients (10%) demonstrated flap compromise, prompting return to the operating room in 96 patients. Of these 96 patients, 46 had complete flap salvage, 22 had partial loss, and 37 had complete loss. The frequency of resident flap checks did not affect the total flap loss rate (q4h, 25 patients [4%]; q8h, 8 patients [6%]; and q12h, 8 patients [3%]). Flap salvage rates for compromised flaps were not statistically different. Conclusions and Relevance: Academic centers rely primarily on q1h flap checks by intensive care unit nurses using physical examination and Doppler sonography. Reduced resident monitoring frequency did not alter flap salvage nor flap outcome. These findings suggest that institutions may successfully monitor free flaps with decreased resident burden

2019 American College of Rheumatology/Arthritis Foundation Guideline for the Management of Osteoarthritis of the Hand, Hip, and Knee.

ObjectiveTo develop an evidence-based guideline for the comprehensive management of osteoarthritis (OA) as a collaboration between the American College of Rheumatology (ACR) and the Arthritis Foundation, updating the 2012 ACR recommendations for the management of hand, hip, and knee OA.MethodsWe identified clinically relevant population, intervention, comparator, outcomes questions and critical outcomes in OA. A Literature Review Team performed a systematic literature review to summarize evidence supporting the benefits and harms of available educational, behavioral, psychosocial, physical, mind-body, and pharmacologic therapies for OA. Grading of Recommendations Assessment, Development and Evaluation methodology was used to rate the quality of the evidence. A Voting Panel, including rheumatologists, an internist, physical and occupational therapists, and patients, achieved consensus on the recommendations.ResultsBased on the available evidence, either strong or conditional recommendations were made for or against the approaches evaluated. Strong recommendations were made for exercise, weight loss in patients with knee and/or hip OA who are overweight or obese, self-efficacy and self-management programs, tai chi, cane use, hand orthoses for first carpometacarpal (CMC) joint OA, tibiofemoral bracing for tibiofemoral knee OA, topical nonsteroidal antiinflammatory drugs (NSAIDs) for knee OA, oral NSAIDs, and intraarticular glucocorticoid injections for knee OA. Conditional recommendations were made for balance exercises, yoga, cognitive behavioral therapy, kinesiotaping for first CMC OA, orthoses for hand joints other than the first CMC joint, patellofemoral bracing for patellofemoral knee OA, acupuncture, thermal modalities, radiofrequency ablation for knee OA, topical NSAIDs, intraarticular steroid injections and chondroitin sulfate for hand OA, topical capsaicin for knee OA, acetaminophen, duloxetine, and tramadol.ConclusionThis guideline provides direction for clinicians and patients making treatment decisions for the management of OA. Clinicians and patients should engage in shared decision-making that accounts for patients' values, preferences, and comorbidities. These recommendations should not be used to limit or deny access to therapies