Incorporation Of Genetic Information Research Articles

Artificial Intelligence for Image-Based Breast Cancer Risk Prediction Using Attention.

Accurate prediction of individual breast cancer risk paves the way for personalised prevention and early detection. The incorporation of genetic information and breast density has been shown to improve predictions for existing models, but detailed image-based features are yet to be included despite correlating with risk. Complex information can be extracted from mammograms using deep-learning algorithms, however, this is a challenging area of research, partly due to the lack of data within the field, and partly due to the computational burden. We propose an attention-based Multiple Instance Learning (MIL) model that can make accurate, short-term risk predictions from mammograms taken prior to the detection of cancer at full resolution. Current screen-detected cancers are mixed in with priors during model development to promote the detection of features associated with risk specifically and features associated with cancer formation, in addition to alleviating data scarcity issues. MAI-risk achieves an AUC of 0.747 [0.711, 0.783] in cancer-free screening mammograms of women who went on to develop a screen-detected or interval cancer between 5 and 55 months, outperforming both IBIS (AUC 0.594 [0.557, 0.633]) and VAS (AUC 0.649 [0.614, 0.683]) alone when accounting for established clinical risk factors.

Identification of 969 protein quantitative trait loci in an African American population with kidney disease attributed to hypertension

Investigations into the causal underpinnings of disease processes can be aided by the incorporation of genetic information. Genetic studies require populations varied in both ancestry and prevalent disease in order to optimize discovery and ensure generalizability of findings to the global population. Here, we report the genetic determinants of the serum proteome in 466 African Americans with chronic kidney disease attributed to hypertension from the richly phenotyped African American Study of Kidney Disease and Hypertension (AASK) study. Using the largest aptamer-based protein profiling platform to date (6,790 proteins or protein complexes), we identified 969 genetic associations with 900 unique proteins; including 52 novel cis (local) associations and 379 novel trans (distant) associations. The genetic effects of previously published cis-protein quantitative trait loci (pQTLs) were found to be highly reproducible, and we found evidence that our novel genetic signals colocalize with gene expression and disease processes. Many trans- pQTLs were found to reflect associations mediated by the circulating cis protein, and the common trans-pQTLs are enriched for processes involving extracellular vesicles, highlighting a plausible mechanism for distal regulation of the levels of secreted proteins. Thus, our study generates a valuable resource of genetic associations linking variants to protein levels and disease in an understudied patient population to inform future studies of drug targets and physiology.

Genetic structure of a remnant Acropora cervicornis population

Amongst the global decline of coral reefs, hope spots such as Cordelia Bank in Honduras, have been identified. This site contains dense, remnant thickets of the endangered species Acropora cervicornis, which local managers and conservation organizations view as a potential source population for coral restoration projects. The aim of this study was to determine the genetic diversity of colonies across three banks within the protected area. We identified low genetic diversity (FST = 0.02) across the three banks, and genetic similarity of colonies ranged from 91.3 to 95.8% between the banks. Clonality rates were approximately 30% across the three banks, however, each genotype identified was unique to each bank. Despite the low genetic diversity, subtle genetic differences within and among banks were demonstrated, and these dense thickets were shown not to be comprised of a single or a few genotypes. The presence of multiple genotypes suggests A. cervicornis colonies from these banks could be used to maintain and enhance genetic diversity in restoration projects. Management of hope spots, such as Cordelia Bank, and the incorporation of genetic information into restoration projects to ensure genetic diversity within out-planted populations, will be critical in the ongoing challenge of conserving and preserving coral reefs.

Effect of Incorporating Genetic Testing Results into Nutrition Counseling and Care on Health Outcomes: An Evidence Analysis Center Systematic Review—Part II

In recent years, literature examining implementation of nutritional genomics into clinical practice has increased, including publication of several randomized controlled trials (RCTs). This systematic review addressed the following question: In children and adults, what is the effect of incorporating results of genetic testing into nutrition counseling and care compared with an alternative intervention or control group, on nutrition-related health outcomes? A literature search of MEDLINE, Embase, PsycINFO, CINAHL, and other databases was conducted for peer-reviewed RCTs published from January 2008 until December 2018. An international workgroup consisting of registered dietitian nutritionists, systematic review methodologists, and evidence analysts screened and reviewed articles, summarized data, conducted meta-analyses, and graded conclusion statements. The second in a two-part series, this article specifically summarizes evidence from RCTs that examined health outcomes (ie, quality of life, disease incidence and prevention of disease progression, or mortality), intermediate health outcomes (ie, anthropometric measures, body composition, or relevant laboratory measures routinely collected in practice), and adverse events as reported by study authors. Analysis of 11 articles from nine RCTs resulted in 16 graded conclusion statements. Among participants with nonalcoholic fatty liver disease, a diet tailored to genotype resulted in a greater reduction of percent body fat compared with a customary diet for nonalcoholic fatty liver disease. However, meta-analyses for the outcomes of total cholesterol, low-density lipoprotein cholesterol, body mass index, and weight yielded null results. Heterogeneity between studies and low certainty of evidence precluded development of strong conclusions about the incorporation of genetic information into nutrition practice. Although there are still relatively few well-designed RCTs to inform integration of genetic information into the Nutrition Care Process, the field of nutritional genomics is evolving rapidly, and gaps in the literature identified by this systematic review can inform future studies.

Follicular Lymphoma: Diagnostic and Prognostic Considerations in Initial Treatment Approach.

Follicular lymphoma is a diverse disease, with a diverse variable biology, clinical presentation, and prognosis. The identification of factors that can predict the specific outcome of follicular lymphoma patients remains an area of need. Here, we review the significant advances made in follicular lymphoma prognosis in the last two decades, particularly with the advent of new genetic models. Tumor burden remains an important predictor of prognosis and is still a standard upon which treatment initiation decisions are made. Clinical prognostic indices, including the follicular lymphoma international prognostic index (FLIPI) and FLIPI-2, are validated to predict overall survival and progression-free survival, respectively. However, clinical decisions are rarely made based on these and other indices. Recently described molecular abnormalities in follicular lymphoma include those involving epigenetic regulation, cell-surface receptor signaling, and those controlling the interactions of the follicular lymphoma cell with the microenvironment. Clinicogenetic indices, such as the m7-FLIPI, take into account molecular information and provide a more accurate prognostic prediction than clinical indices. Significant advances have been made in the development of predictive models of risk in follicular lymphoma, in particular with the incorporation of genetic information to predict risk. New models are capable of identifying groups of patients at highest risk of progression. However, it is not yet possible to predict the specific clinical course of a particular patient based on baseline factors. Continued research is needed to identify patients at highest risk of failing initial therapy and the therapeutic approaches to improve their outcomes.

Leveraging Human Genetics to Guide Cancer Drug Development.

The high attrition rate of cancer drug development programs is a barrier to realizing the promise of precision oncology. We have examined whether the genetic insights from genome-wide association studies of cancer can guide drug development and repurposing in oncology. Across 37 cancers, we identified 955 genetic risk variants from the National Human Genome Research Institute-European Bioinformatics Institute genome-wide association study catalog. We linked these variants to target genes using strategies that were based on linkage disequilibrium, DNA three-dimensional structure, and integration of predicted gene function and expression. With the use of the Informa Pharmaprojects database, we identified genes that are targets of unique drugs and assessed the level of enrichment that would be afforded by incorporation of genetic information in preclinical and phase II studies. For targets not under development, we implemented machine learning approaches to assess druggability. For all preclinical targets incorporating genetic information, a 2.00-fold enrichment of a drug being successfully approved could be achieved (95% CI, 1.14- to 3.48-fold; P = .02). For phase II targets, a 2.75-fold enrichment could be achieved (95% CI, 1.42- to 5.35-fold; P < .001). Application of genetic information suggests potential repurposing of 15 approved nononcology drugs. The findings illustrate the value of using insights from the genetics of inherited cancer susceptibility discovery projects as part of a data-driven strategy to inform drug discovery. Support for cancer germline genetic information for prospective targets is available online from the Institute of Cancer Research.

A comprehensive genetic approach for improving prediction of skin cancer risk in humans.

Prediction of genetic risk for disease is needed for preventive and personalized medicine. Genome-wide association studies have found unprecedented numbers of variants associated with complex human traits and diseases. However, these variants explain only a small proportion of genetic risk. Mounting evidence suggests that many traits, relevant to public health, are affected by large numbers of small-effect genes and that prediction of genetic risk to those traits and diseases could be improved by incorporating large numbers of markers into whole-genome prediction (WGP) models. We developed a WGP model incorporating thousands of markers for prediction of skin cancer risk in humans. We also considered other ways of incorporating genetic information into prediction models, such as family history or ancestry (using principal components, PCs, of informative markers). Prediction accuracy was evaluated using the area under the receiver operating characteristic curve (AUC) estimated in a cross-validation. Incorporation of genetic information (i.e., familial relationships, PCs, or WGP) yielded a significant increase in prediction accuracy: from an AUC of 0.53 for a baseline model that accounted for nongenetic covariates to AUCs of 0.58 (pedigree), 0.62 (PCs), and 0.64 (WGP). In summary, prediction of skin cancer risk could be improved by considering genetic information and using a large number of single-nucleotide polymorphisms (SNPs) in a WGP model, which allows for the detection of patterns of genetic risk that are above and beyond those that can be captured using family history. We discuss avenues for improving prediction accuracy and speculate on the possible use of WGP to prospectively identify individuals at high risk.

Variantes genéticas, riesgo cardiovascular y estudios de asociación de genoma completo

Genome-wide association studies have shown an association between single nucleotide polymorphisms (SNPs) and coronary artery disease and myocardial infarction in new chromosomal regions: 1p13.1, 2q36.3, 9p21 and 10q11.21. The SNPs from the 9p21 region constitute a risk haplotype due to the strong linkage disequilibrium in this area. These SNPs have been extensively replicated in several European and Asian populations, and are associated with other pathologies such as abdominal aortic and intracranial aneurysms, and with intermediate phenotypes such as arterial stiffness and coronary calcium. The risk haplotype of 9p21 is located in a region without annotated genes, near CDKN2A and CDKN2B, known tumor suppressor genes encoding for inhibitors of cell cycle kinases. In the remaining regions the SNPs are located in genes with known roles in atherosclerosis as well as others with new roles. It has been shown that the incorporation of genetic information in the form of SNPs slightly improves the prediction of long-term cardiovascular risk estimated by the Framingham function, allowing the reclassification of individuals into more precise categories. Gene expression studies have found that expression levels of CDKN2A/CDKN2B/ANRIL are co-regulated and associated with the risk haplotype and atherosclerosis severity. Full English text available from: www.revespcardiol.org

Genetic Variants, Cardiovascular Risk and Genome-Wide Association Studies

Genome-wide association studies have shown an association between single nucleotide polymorphisms (SNPs) and coronary artery disease and myocardial infarction in new chromosomal regions: 1p13.1, 2q36.3, 9p21 and 10q11.21. The SNPs from the 9p21 region constitute a risk haplotype due to the strong linkage disequilibrium in this area. These SNPs have been extensively replicated in several European and Asian populations, and are associated with other pathologies such as abdominal aortic and intracranial aneurysms, and with intermediate phenotypes such as arterial stiffness and coronary calcium. The risk haplotype of 9p21 is located in a region without annotated genes, near CDKN2A and CDKN2B, known tumor suppressor genes encoding for inhibitors of cell cycle kinases. In the remaining regions the SNPs are located in genes with known roles in atherosclerosis as well as others with new roles. It has been shown that the incorporation of genetic information in the form of SNPs slightly improves the prediction of long-term cardiovascular risk estimated by the Framingham function, allowing the reclassification of individuals into more precise categories. Gene expression studies have found that expression levels of CDKN2A/CDKN2B/ANRIL are co-regulated and associated with the risk haplotype and atherosclerosis severity.

Personalized Medicine and the Ocular Surface

again I am having thoughts flying home from the ASCPT convention. The most dominant theme I heard this year was “personalized medicine,” 4 in which pharmacotherapy is individualized based upon the individual’s genetic and other characteristics. There are several examples of personalized medicine already in use in systemic medicine. Trastuzumab is indicated for the treatment of patients with metastatic breast cancer whose tumors overexpress the HER2 protein (Herceptin ® package insert, Genentech, South San Francisco, CA). A genetic test is performed on each patient’s tumor, and trastuzumab is administered only to patients with the HER2 protein overexpression. Warfarin, a drug used for its anticoagulant effects since 1954, has always been challenging to titrate, given its relatively low therapeutic index. Recently, it has been shown that better prediction of optimal dose was attained with additional incorporation of genetic information on CYP2C9, which metabolizes the more active form (S-) of warfarin, and VKORC1, the enzyme responsible for vitamin K metabolism and the target for warfarin action, rather than clinical data (eg, age and weight) alone. The FDA recently modified the package insert for warfarin to include evaluation of both CYP2C9 and VKORC1 genetic information in the “Dosage and Administration” section. 5

Genomic Analysis of Left Ventricular Remodeling

The left ventricle (LV) of the heart remodels in response to hemodynamic load through the processes of physiological or pathophysiological hypertrophy.1–3 Despite extensive study of the molecular basis of cardiac hypertrophy and LV remodeling,1,4 the mainstay of medical treatment of maladaptive remodeling remains based on therapies initially devised for treating hypertension. The limited progress in the development of specific therapies for LV remodeling has led some to refer to “the impossible task of developing a new treatment for heart failure” and is the reason why, in part, device therapies have received such recent attention.5–8 To gain a better understanding of the biology of maladaptive LV remodeling, with a view to identifying therapeutic targets, new paradigms and experimental approaches are needed, and genomics provides one such methodology. Genomics is the study of genome-scale data sets, at the DNA or RNA level, and when combined with studies of physiological traits or disease phenotypes, genomics can be used to infer molecular insights. Unlike single-gene studies, which are the favored hypothesis-driven design,4 genomic approaches examine variation in up to gigabases of sequences to find statistical associations between transcripts and traits in a hypothesis-free system. These hypothesis-free studies have often been criticized as unfocused, but following the successes of genome-wide association studies (GWAS) and the recent achievements of integrated genetic and genomic analyses, a new era of genomic experimentation presents itself.9–14 It is notable that GWAS and integrated genomic studies in humans often identify regions associated with disease rather than specific genes and that effect sizes are small; nevertheless, these data remain highly informative.15–17 In this article, we review the genomic analysis of LV remodeling in the context of the recent past, the state of the art, and the imminent use of next-generation sequencing. A glossary of terms is …

From genome to wheat: Emerging opportunities for modelling wheat growth and development

Ecophysiological models of crop growth and development sometimes show unrealistic responses that are attributable to our incomplete understanding of the processes the models attempt to describe. Rapid advances in plant genetics, genomics and biochemistry offer important opportunities for improving representations of key processes of growth and development. Research on incorporation of genetic information in models supports this potential, especially in modelling cultivar performance across environments. This paper reviews progress in using information from genetics, genomics and allied fields in modelling and examines approaches suitable for modelling wheat ( Triticum aestivum L. and T. durum Desf.). Efforts to model wheat crops should first focus on the relatively well-understood genetic systems affecting phenology and plant height. A simple gene-based approach using linear equations to estimate cultivar-specific parameters has the advantage that it can easily be implemented in existing wheat models. One requirement is to integrate data on the genetic makeup of wheat cultivars with results from field trials that can be used to estimate genetic effects and evaluate model performance. Concomitantly, modellers should exploit findings from genomics and allied fields on wheat and other plant species in order to improve sub-models of individual processes, using more complex representations of gene action. Advances in these more mechanistic representations require much more detailed and quantitative studies on how gene action varies with specific environmental signals such as temperature and photoperiod.

The Cobweb of Life Revealed by Genome-Scale Estimates of Horizontal Gene Transfer

With the availability of increasing amounts of genomic sequences, it is becoming clear that genomes experience horizontal transfer and incorporation of genetic information. However, to what extent such horizontal gene transfer (HGT) affects the core genealogical history of organisms remains controversial. Based on initial analyses of complete genomic sequences, HGT has been suggested to be so widespread that it might be the “essence of phylogeny” and might leave the treelike form of genealogy in doubt. On the other hand, possible biased estimation of HGT extent and the findings of coherent phylogenetic patterns indicate that phylogeny of life is well represented by tree graphs. Here, we reexamine this question by assessing the extent of HGT among core orthologous genes using a novel statistical method based on statistical comparisons of tree topology. We apply the method to 40 microbial genomes in the Clusters of Orthologous Groups database over a curated set of 297 orthologous gene clusters, and we detect significant HGT events in 33 out of 297 clusters over a wide range of functional categories. Estimates of positions of HGT events suggest a low mean genome-specific rate of HGT (2.0%) among the orthologous genes, which is in general agreement with other quantitative of HGT. We propose that HGT events, even when relatively common, still leave the treelike history of phylogenies intact, much like cobwebs hanging from tree branches.

Genetic Testing Considerations for Oral Medicine

The availability and integration of genetic information into our understanding of normal and abnormal growth and development are driving important changes in health care. These changes have fostered the hope that the availability of genetic information will promote a better understanding of disease etiology and permit early, even pre-symptomatic diagnosis and preventative intervention to avoid disease onset. Expectations for this proactive health care approach are fueled by the technological and scientific advances that have fundamentally changed how we perceive human diseases. Among the clinical applications of this information, genetic testing applications are likely to expand significantly and may broadly impact the clinical practice of dentistry. In this changing environment, it is vital that dental care providers, policymakers, and consumers become aware of important issues related to genetic testing and the incorporation of genetic information into the diagnosis and treatment of common diseases that involve the oral cavity. We must also guard against unrealistic expectations and calls for genetic tests that are not valid. To realize the promise of this new molecular genetics, we must understand the possibilities and responsibly incorporate newly emergent technologies into the evolving discipline of dentistry. This paper overviews many of the important issues that need to be considered in the application of genetic testing to oral medicine.

Genetic susceptibility for breast cancer—Risk assessment and counseling

The incorporation of genetic information into clinical oncology practice is a process in evolution, necessitating consideration of cancer risk assessment, ethical and social implications of testing and efficacy of treatment, and prevention interventions. Although most cancers do have a hereditary component, recognizing individuals who are at unusually high risk is important for planning their surveillance practices and considering options for risk management over a lifetime, and because of implications for their family members. Genetic information has enormous potential to inform and transform cancer risk identification, risk reduction, and treatment practices. In this review, we summarize basic information about breast cancer genetics, examine accumulating data about the prevalence and penetrance of deleterious mutations and management options for BRCA1 and BRCA2 mutation carriers, and discuss some of the counseling issues that may occur as physicians and patients explore this exploding area of oncology. The rapid incorporation of careful genetic testing into oncology practice is an important step toward more precise risk management. Currently, the time necessary for careful discussion of the complex issues raised by genetic testing for inherited breast/ ovarian cancer susceptibility may necessitate referral to geneticists or genetic counselors for truly informed consent to be obtained. However, identification of women for whom testing is appropriate and management of cancer risk with women after testing, are critical new functions for oncologists. They are only the beginning of exciting new opportunities in cancer risk and prevention.