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Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group.

October 18, 2018 dna 0
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Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group.

Genet Med. 2018 06;20(6):655-663

Authors: Orlando LA, Sperber NR, Voils C, Nichols M, Myers RA, Wu RR, Rakhra-Burris T, Levy KD, Levy M, Pollin TI, Guan Y, Horowitz CR, Ramos M, Kimmel SE, McDonough CW, Madden EB, Damschroder LJ

Abstract
PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network’s efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

PMID: 28914267 [PubMed – indexed for MEDLINE]

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Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group.

October 17, 2018 dna 0
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Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network’s Common Measures Working Group.

Genet Med. 2018 06;20(6):655-663

Authors: Orlando LA, Sperber NR, Voils C, Nichols M, Myers RA, Wu RR, Rakhra-Burris T, Levy KD, Levy M, Pollin TI, Guan Y, Horowitz CR, Ramos M, Kimmel SE, McDonough CW, Madden EB, Damschroder LJ

Abstract
PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network’s efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

PMID: 28914267 [PubMed – indexed for MEDLINE]

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SNP rs11185644 of RXRA gene is identified for dose-response variability to vitamin D3 supplementation: a randomized clinical trial.

October 16, 2018 dna 0
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SNP rs11185644 of RXRA gene is identified for dose-response variability to vitamin D3 supplementation: a randomized clinical trial.

Sci Rep. 2017 01 12;7:40593

Authors: Zhang M, Zhao LJ, Zhou Y, Badr R, Watson P, Ye A, Zhou B, Zhang J, Deng HW, Recker RR, Lappe JM

Abstract
The level of serum 25-Hydroxyvitamin D [25(OH)D] has high heritability, suggesting that genes may contribute to variations in serum 25(OH)D level and vitamin D dose-response. As vitamin D deficiency has been linked to numerous diseases, understanding how genetic variation contributes to vitamin D dose-response is important for personalized vitamin D treatment and cost-effective disease prevention. To identify genetic variants responsible for vitamin D status and dose-response, we performed two vitamin D3 and calcium clinical supplementation trials in 2,207 postmenopausal Caucasian women. We examined the association of 291 SNPs with baseline serum 25(OH)D levels and 25(OH)D dose-response. Five SNPs, rs10500804 (P = 4.93 × 10-7), rs2060793 (P = 6.63 × 10-7), rs10741657 (P = 1.49 × 10-6), rs10766197 (P = 1.05 × 10-5) and rs11023380 (P = 7.67 × 10-5) in the CYP2R1 gene, as well as 6 SNPs, rs4588 (P = 7.86 × 10-7), rs2298850 (P = 1.94 × 10-6), rs1155563 (P = 6.39 × 10-6), rs705119 (P = 2.80 × 10-5), rs705120 (P = 1.08 × 10-4) and rs222040 (P = 1.59 × 10-4) in the GC gene were associated with baseline serum 25(OH)D levels. SNP rs11185644 near the RXRA was significantly associated with 25(OH)D dose-response (P = 1.01 × 10-4). Our data suggest that polymorphisms in the CYP2R1 and GC gene may contribute to variation in baseline serum 25(OH)D concentration, and that polymorphism rs11185644 may contribute to variation in 25(OH)D dose-response in healthy postmenopausal Caucasian women.

PMID: 28079136 [PubMed – indexed for MEDLINE]

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Comparative Genomics Reveals Accelerated Evolution in Conserved Pathways during the Diversification of Anole Lizards.

October 16, 2018 dna 0
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Comparative Genomics Reveals Accelerated Evolution in Conserved Pathways during the Diversification of Anole Lizards.

Genome Biol Evol. 2018 02 01;10(2):489-506

Authors: Tollis M, Hutchins ED, Stapley J, Rupp SM, Eckalbar WL, Maayan I, Lasku E, Infante CR, Dennis SR, Robertson JA, May CM, Crusoe MR, Bermingham E, DeNardo DF, Hsieh ST, Kulathinal RJ, McMillan WO, Menke DB, Pratt SC, Rawls JA, Sanjur O, Wilson-Rawls J, Wilson Sayres MA, Fisher RE, Kusumi K

Abstract
Squamates include all lizards and snakes, and display some of the most diverse and extreme morphological adaptations among vertebrates. However, compared with birds and mammals, relatively few resources exist for comparative genomic analyses of squamates, hampering efforts to understand the molecular bases of phenotypic diversification in such a speciose clade. In particular, the ∼400 species of anole lizard represent an extensive squamate radiation. Here, we sequence and assemble the draft genomes of three anole species-Anolis frenatus, Anolis auratus, and Anolis apletophallus-for comparison with the available reference genome of Anolis carolinensis. Comparative analyses reveal a rapid background rate of molecular evolution consistent with a model of punctuated equilibrium, and strong purifying selection on functional genomic elements in anoles. We find evidence for accelerated evolution in genes involved in behavior, sensory perception, and reproduction, as well as in genes regulating limb bud development and hindlimb specification. Morphometric analyses of anole fore and hindlimbs corroborated these findings. We detect signatures of positive selection across several genes related to the development and regulation of the forebrain, hormones, and the iguanian lizard dewlap, suggesting molecular changes underlying behavioral adaptations known to reinforce species boundaries were a key component in the diversification of anole lizards.

PMID: 29360978 [PubMed – indexed for MEDLINE]

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From hype to reality: data science enabling personalized medicine.

October 16, 2018 dna 0
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From hype to reality: data science enabling personalized medicine.

BMC Med. 2018 08 27;16(1):150

Authors: Fröhlich H, Balling R, Beerenwinkel N, Kohlbacher O, Kumar S, Lengauer T, Maathuis MH, Moreau Y, Murphy SA, Przytycka TM, Rebhan M, Röst H, Schuppert A, Schwab M, Spang R, Stekhoven D, Sun J, Weber A, Ziemek D, Zupan B

Abstract
BACKGROUND: Personalized, precision, P4, or stratified medicine is understood as a medical approach in which patients are stratified based on their disease subtype, risk, prognosis, or treatment response using specialized diagnostic tests. The key idea is to base medical decisions on individual patient characteristics, including molecular and behavioral biomarkers, rather than on population averages. Personalized medicine is deeply connected to and dependent on data science, specifically machine learning (often named Artificial Intelligence in the mainstream media). While during recent years there has been a lot of enthusiasm about the potential of ‘big data’ and machine learning-based solutions, there exist only few examples that impact current clinical practice. The lack of impact on clinical practice can largely be attributed to insufficient performance of predictive models, difficulties to interpret complex model predictions, and lack of validation via prospective clinical trials that demonstrate a clear benefit compared to the standard of care. In this paper, we review the potential of state-of-the-art data science approaches for personalized medicine, discuss open challenges, and highlight directions that may help to overcome them in the future.
CONCLUSIONS: There is a need for an interdisciplinary effort, including data scientists, physicians, patient advocates, regulatory agencies, and health insurance organizations. Partially unrealistic expectations and concerns about data science-based solutions need to be better managed. In parallel, computational methods must advance more to provide direct benefit to clinical practice.

PMID: 30145981 [PubMed – indexed for MEDLINE]

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A comprehensive custom panel design for routine hereditary cancer testing: preserving control, improving diagnostics and revealing a complex variation landscape.

October 16, 2018 dna 0
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A comprehensive custom panel design for routine hereditary cancer testing: preserving control, improving diagnostics and revealing a complex variation landscape.

Sci Rep. 2017 01 04;7:39348

Authors: Castellanos E, Gel B, Rosas I, Tornero E, Santín S, Pluvinet R, Velasco J, Sumoy L, Del Valle J, Perucho M, Blanco I, Navarro M, Brunet J, Pineda M, Feliubadaló L, Capellá G, Lázaro C, Serra E

Abstract
We wanted to implement an NGS strategy to globally analyze hereditary cancer with diagnostic quality while retaining the same degree of understanding and control we had in pre-NGS strategies. To do this, we developed the I2HCP panel, a custom bait library covering 122 hereditary cancer genes. We improved bait design, tested different NGS platforms and created a clinically driven custom data analysis pipeline. The I2HCP panel was developed using a training set of hereditary colorectal cancer, hereditary breast and ovarian cancer and neurofibromatosis patients and reached an accuracy, analytical sensitivity and specificity greater than 99%, which was maintained in a validation set. I2HCP changed our diagnostic approach, involving clinicians and a genetic diagnostics team from panel design to reporting. The new strategy improved diagnostic sensitivity, solved uncertain clinical diagnoses and identified mutations in new genes. We assessed the genetic variation in the complete set of hereditary cancer genes, revealing a complex variation landscape that coexists with the disease-causing mutation. We developed, validated and implemented a custom NGS-based strategy for hereditary cancer diagnostics that improved our previous workflows. Additionally, the existence of a rich genetic variation in hereditary cancer genes favors the use of this panel to investigate their role in cancer risk.

PMID: 28051113 [PubMed – indexed for MEDLINE]

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Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis.

October 16, 2018 dna 0
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Human genetic and metabolite variation reveals that methylthioadenosine is a prognostic biomarker and an inflammatory regulator in sepsis.

Sci Adv. 2017 Mar;3(3):e1602096

Authors: Wang L, Ko ER, Gilchrist JJ, Pittman KJ, Rautanen A, Pirinen M, Thompson JW, Dubois LG, Langley RJ, Jaslow SL, Salinas RE, Rouse DC, Moseley MA, Mwarumba S, Njuguna P, Mturi N, Wellcome Trust Case Control Consortium 2, Kenyan Bacteraemia Study Group, Williams TN, Scott JA, Hill AV, Woods CW, Ginsburg GS, Tsalik EL, Ko DC

Abstract
Sepsis is a deleterious inflammatory response to infection with high mortality. Reliable sepsis biomarkers could improve diagnosis, prognosis, and treatment. Integration of human genetics, patient metabolite and cytokine measurements, and testing in a mouse model demonstrate that the methionine salvage pathway is a regulator of sepsis that can accurately predict prognosis in patients. Pathway-based genome-wide association analysis of nontyphoidal Salmonella bacteremia showed a strong enrichment for single-nucleotide polymorphisms near the components of the methionine salvage pathway. Measurement of the pathway’s substrate, methylthioadenosine (MTA), in two cohorts of sepsis patients demonstrated increased plasma MTA in nonsurvivors. Plasma MTA was correlated with levels of inflammatory cytokines, indicating that elevated MTA marks a subset of patients with excessive inflammation. A machine-learning model combining MTA and other variables yielded approximately 80% accuracy (area under the curve) in predicting death. Furthermore, mice infected with Salmonella had prolonged survival when MTA was administered before infection, suggesting that manipulating MTA levels could regulate the severity of the inflammatory response. Our results demonstrate how combining genetic data, biomolecule measurements, and animal models can shape our understanding of disease and lead to new biomarkers for patient stratification and potential therapeutic targeting.

PMID: 28345042 [PubMed – indexed for MEDLINE]

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A system for detecting high impact-low frequency mutations in primary tumors and metastases.

October 16, 2018 dna 0
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A system for detecting high impact-low frequency mutations in primary tumors and metastases.

Oncogene. 2018 01 11;37(2):185-196

Authors: Anjanappa M, Hao Y, Simpson ER, Bhat-Nakshatri P, Nelson JB, Tersey SA, Mirmira RG, Cohen-Gadol AA, Saadatzadeh MR, Li L, Fang F, Nephew KP, Miller KD, Liu Y, Nakshatri H

Abstract
Tumor complexity and intratumor heterogeneity contribute to subclonal diversity. Despite advances in next-generation sequencing (NGS) and bioinformatics, detecting rare mutations in primary tumors and metastases contributing to subclonal diversity is a challenge for precision genomics. Here, in order to identify rare mutations, we adapted a recently described epithelial reprograming assay for short-term propagation of epithelial cells from primary and metastatic tumors. Using this approach, we expanded minor clones and obtained epithelial cell-specific DNA/RNA for quantitative NGS analysis. Comparative Ampliseq Comprehensive Cancer Panel sequence analyses were performed on DNA from unprocessed breast tumor and tumor cells propagated from the same tumor. We identified previously uncharacterized mutations present only in the cultured tumor cells, a subset of which has been reported in brain metastatic but not primary breast tumors. In addition, whole-genome sequencing identified mutations enriched in liver metastases of various cancers, including Notch pathway mutations/chromosomal inversions in 5/5 liver metastases, irrespective of cancer types. Mutations/rearrangements in FHIT, involved in purine metabolism, were detected in 4/5 liver metastases, and the same four liver metastases shared mutations in 32 genes, including mutations of different HLA-DR family members affecting OX40 signaling pathway, which could impact the immune response to metastatic cells. Pathway analyses of all mutated genes in liver metastases showed aberrant tumor necrosis factor and transforming growth factor signaling in metastatic cells. Epigenetic regulators including KMT2C/MLL3 and ARID1B, which are mutated in >50% of hepatocellular carcinomas, were also mutated in liver metastases. Thus, irrespective of cancer types, organ-specific metastases may share common genomic aberrations. Since recent studies show independent evolution of primary tumors and metastases and in most cases mutation burden is higher in metastases than primary tumors, the method described here may allow early detection of subclonal somatic alterations associated with metastatic progression and potentially identify therapeutically actionable, metastasis-specific genomic aberrations.

PMID: 28892047 [PubMed – indexed for MEDLINE]