Getting personal with epigenetics:towards individual-specific epigenomic imputation with machine learning

Epigenetic modifications are dynamic mechanisms involved in the regulation of gene expression. Unlike the DNA sequence, epigenetic patterns vary not only between individuals, but also between different cell types within an individual. Environmental factors, somatic mutations and ageing contribute to epigenetic changes that may constitute early hallmarks or causal factors of disease. Epigenetic modifications are reversible and thus promising therapeutic targets for precision medicine. However, mapping efforts to determine an individual's cell-type-specific epigenome are constrained by experimental costs and tissue accessibility. To address these challenges, we developed eDICE, an attention-based deep learning model that is trained to impute missing epigenomic tracks by conditioning on observed tracks. Using a recently published set of epigenomes from four individual donors, we show that transfer learning across individuals allows eDICE to successfully predict individual-specific epigenetic variation even in tissues that are unmapped in a given donor. These results highlight the potential of machine learning-based imputation methods to advance personalized epigenomics.</p

Non-medical prescribing versus medical prescribing for acute and chronic disease management in primary and secondary care. [Protocol]

This is the protocol for a review and there is no abstract. The objectives are as follows: To assess the clinical, economic and humanistic health outcomes of non-medical prescribing for managing acute and chronic health conditions in primary and secondary care settings compared with medical prescribing

Integration of multiple epigenomic marks improves prediction of variant impact in saturation mutagenesis reporter assay

The integrative analysis of highâ throughput reporter assays, machine learning, and profiles of epigenomic chromatin state in a broad array of cells and tissues has the potential to significantly improve our understanding of noncoding regulatory element function and its contribution to human disease. Here, we report results from the CAGI 5 regulation saturation challenge where participants were asked to predict the impact of nucleotide substitution at every base pair within five diseaseâ associated human enhancers and nine diseaseâ associated promoters. A library of mutations covering all bases was generated by saturation mutagenesis and altered activity was assessed in a massively parallel reporter assay (MPRA) in relevant cell lines. Reporter expression was measured relative to plasmid DNA to determine the impact of variants. The challenge was to predict the functional effects of variants on reporter expression. Comparative analysis of the full range of submitted prediction results identifies the most successful models of transcription factor binding sites, machine learning algorithms, and ways to choose among or incorporate diverse datatypes and cellâ types for training computational models. These results have the potential to improve the design of future studies on more diverse sets of regulatory elements and aid the interpretation of diseaseâ associated genetic variation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/151884/1/humu23797_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/151884/2/humu23797.pd

Prostate Cancer Susceptibility Loci Identified on Chromosome 12 in African Americans

Prostate cancer (PCa) is a complex disease that disproportionately affects African Americans and other individuals of African descent. A number of regions across the genome have been associated to PCa, most of them with moderate effects. A few studies have reported chromosomal changes on 12p and 12q that occur during the onset and development of PCa but to date no consistent association of the disease with chromosome 12 polymorphic variation has been identified. In order to unravel genetic risk factors that underlie PCa health disparities we investigated chromosome 12 using ancestry informative markers (AIMs), which allow us to distinguish genomic regions of European or West African origin, and tested them for association with PCa. Additional SNPs were genotyped in those areas where significant signals of association were detected. The strongest signal was discovered at the SNP rs12827748, located upstream of the PAWR gene, a tumor suppressor, which is amply expressed in the prostate. The most frequent allele in Europeans was the risk allele among African Americans. We also examined vitamin D related genes, VDR and CYP27B1, and found a significant association of PCa with the TaqI polymorphism (rs731236) in the former. Although our results warrant further investigation we have uncovered a genetic susceptibility factor for PCa in a likely candidate by means of an approach that takes advantage of the differential contribution of parental groups to an admixed population

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research

The ENCODE Imputation Challenge: a critical assessment of methods for cross-cell type imputation of epigenomic profiles

A promising alternative to comprehensively performing genomics experiments is to, instead, perform a subset of experiments and use computational methods to impute the remainder. However, identifying the best imputation methods and what measures meaningfully evaluate performance are open questions. We address these questions by comprehensively analyzing 23 methods from the ENCODE Imputation Challenge. We find that imputation evaluations are challenging and confounded by distributional shifts from differences in data collection and processing over time, the amount of available data, and redundancy among performance measures. Our analyses suggest simple steps for overcoming these issues and promising directions for more robust research

Non-medical prescribing versus medical prescribing for acute and chronic disease management in primary and secondary care.

The aim of this Cochrane review was to find out if prescribing by health professionals other than doctors delivers comparable outcomes to prescribing by doctors. Cochrane researchers collected and analysed all relevant studies to answer this question and found 46 studies. Key messages With appropriate training and support, nurses and pharmacists are able to prescribe medicines as part of managing a range of conditions to achieve comparable health management outcomes to doctors. The majority of studies focus on chronic disease management in higher-income counties where there is generally a moderate-certainty of evidence supporting similar outcomes for the markers of disease in high blood pressure, diabetes, and high cholesterol. Further high-quality studies are needed in poorer countries and to better quantify differences in prescribing outcomes for adverse events, and to determine health economic outcomes. Further studies could also focus more specifically on the prescribing component of care. What was studied in the review? A number of countries allow health professionals other than doctors to prescribe medicines. This shift in roles is thought to provide improved and timely access to medicines for consumers where there are shortages of doctors or the health system is facing pressures in coping with the burden of disease. In addition, this task shift has been supported by a number of governments as a way to more appropriately use the skills of health professionals, such as nurses and pharmacists, in the care of patients. We compared the outcomes of any healthcare workers who were prescribing with a high degree of autonomy with medical prescribers in the hospital or community setting in low-, middle- and high-income countries. What are the main results of the review? This review found 45 studies where nurses and pharmacists with high levels of prescribing autonomy were compared with usual care medical prescribers. A further study compared nurse prescribing with guideline support with usual nurse prescribing care. No studies were found with other health professionals or lay prescribers. Four nurse prescribing studies were undertaken in the low- and middle-income settings of Colombia, South Africa, Uganda, and Thailand. The remainder of studies were undertaken in high-income Western countries. Forty-two studies were based in a community setting, two studies were located in hospitals, one study in the workplace, and one study in an aged care facility. Prescribing was but one part of many health-related interventions, particularly in the management of chronic disease. The review found that the outcomes for non-medical prescribers were comparable to medical prescribers for: high blood pressure (moderate-certainty of evidence); diabetes control (high-certainty of evidence); high cholesterol (moderate-certainty of evidence); adverse events (low-certainty of evidence); patients adhering to their medication regimeans (moderate-certainty of evidence); patient satisfaction with care (moderate-certainty of evidence); and health-related quality of life (moderate-certainty of evidence). Pharmacists and nurses with varying levels of undergraduate, postgraduate, and specific on-the-job training related to the disease or condition were able to deliver comparable prescribing outcomes to doctors. Non-medical prescribers frequently had medical support available to facilitate a collaborative practice model