Large-scale reference data sets of human genetic variation are critical for the medical and functional interpretation of DNA sequence changes. Here we describe the aggregation and analysis of high-quality exome (protein-coding region) DNA sequence data for 60,706 individuals of diverse ancestries generated as part of the Exome Aggregation Consortium (ExAC). This catalogue of human genetic diversity contains an average of one variant every eight bases of the exome, and provides direct evidence for the presence of widespread mutational recurrence. We have used this catalogue to calculate objective metrics of pathogenicity for sequence variants, and to identify genes subject to strong selection against various classes of mutation; identifying 3,230 genes with near-complete depletion of predicted protein-truncating variants, with 72% of these genes having no currently established human disease phenotype. Finally, we demonstrate that these data can be used for the efficient filtering of candidate disease-causing variants, and for the discovery of human 'knockout' variants in protein-coding genes.

/pdf/analysis-of-protein-coding-genetic-variation-in-60-706-43wjw7d23z.pdf

Analysis of protein-coding genetic variation in 60,706 humans

BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

Network Medicine: A Network-Based Approach to Human Disease

The paper is concerned with spatial clustering of economic activity and its relation to the spatiality of knowledge creation in interactive learning processes. It questions the view that tacit knowledge transfer is confined to local milieus whereas codified knowledge may roam the globe almost frictionlessly. The paper highlights the conditions under which both tacit and codified knowledge can be exchanged locally and globally. A distinction is made between, on the one hand, the learning processes taking place among actors embedded in a community by just being there dubbed buzz and, on the other, the knowledge attained by investing in building channels of communication called pipelines to selected providers located outside the local milieu. It is argued that the co-existence of high levels of buzz and many pipelines may provide firms located in outward-looking and lively clusters with a string of particular advantages not available to outsiders. Finally, some policy implications, stemming from this argumen...

/pdf/clusters-and-knowledge-local-buzz-global-pipelines-and-the-29bsuyvekg.pdf

Clusters and knowledge: local buzz, global pipelines and the process of knowledge creation

Medical genetics was revolutionized during the 1980s by the application of genetic mapping to locate the genes responsible for simple Mendelian diseases. Most diseases and traits, however, do not follow simple inheritance patterns. Genetics have thus begun taking up the even greater challenge of the genetic dissection of complex traits. Four major approaches have been developed: linkage analysis, allele-sharing methods, association studies, and polygenic analysis of experimental crosses. This article synthesizes the current state of the genetic dissection of complex traits--describing the methods, limitations, and recent applications to biological problems.

https://focus.psychiatryonline.org/doi/pdf/10.1176/foc.4.3.442

Genetic dissection of complex traits

A network of disorders and disease genes linked by known disorder-gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.

/pdf/the-human-disease-network-mm8yuib85g.pdf

The human disease network

A network of disorders and disease genes linked by known disorder–gene associations offers a platform to explore in a single graph-theoretic framework all known phenotype and disease gene associations, indicating the common genetic origin of many diseases. Genes associated with similar disorders show both higher likelihood of physical interactions between their products and higher expression profiling similarity for their transcripts, supporting the existence of distinct disease-specific functional modules. We find that essential human genes are likely to encode hub proteins and are expressed widely in most tissues. This suggests that disease genes also would play a central role in the human interactome. In contrast, we find that the vast majority of disease genes are nonessential and show no tendency to encode hub proteins, and their expression pattern indicates that they are localized in the functional periphery of the network. A selection-based model explains the observed difference between essential and disease genes and also suggests that diseases caused by somatic mutations should not be peripheral, a prediction we confirm for cancer genes.

human disease network

Previous studies have demonstrated familial clustering of prostate cancer. To define the nature of this familial aggregation and to assess whether Mendelian inheritance can explain prostate cancer clustering, proportional hazards and segregation analyses were performed on 691 families ascertained through a single prostate cancer proband. The proportional hazards analyses revealed that two factors, early age at onset of disease in the proband and multiple affected family members, were important determinants of risk of prostate cancer in these families. Furthermore, segregation analyses revealed that this clustering can be best explained by autosomal dominant inheritance of a rare (q = 0.0030) high-risk allele leading to an early onset of prostate cancer. The estimated cumulative risk of prostate cancer for carriers revealed that the allele was highly penetrant: by age 85, 88% of carriers compared to only 5% of noncarriers are projected to be affected with prostate cancer. The best fitting autosomal dominant model further suggested that this inherited form of prostate cancer accounts for a significant proportion of early onset disease but overall is responsible for a small proportion of prostate cancer occurrence (9% by age 85). These data provide evidence that prostate cancer is inherited in Mendelian fashion in a subset of families and provide a foundation for gene mapping studies of heritable prostate cancer. Characterization of genes involved in inherited prostate cancer could provide important insight into the development of this disease in general.

https://www.pnas.org/content/pnas/89/8/3367.full.pdf

Mendelian inheritance of familial prostate cancer.

A case-control study was performed to estimate the relative risk of developing prostate cancer for men with a positive family history. Extensive cancer pedigrees were obtained on 691 men with prostate cancer and 640 spouse controls.



Fifteen percent of the cases but only 8% of the controls had a father or brother affected with prostate cancer (P < .001). Men with a father or brother affected were twice as likely to develop prostate cancer as men with no relatives affected. In addition, there was a trend of increasing risk with increasing number of affected family members such that men with two or three first degree relatives affected had a five and 11–fold increased risk of developing prostate cancer.



Recognizing that 9–10% of U.S. men will develop prostate cancer in their lifetime, men with a family history of prostate cancer should be advised of their significantly increased prostate cancer risk and should undergo appropriate screening measures for this disease.

Barton Childs

Papers

The human disease network

human disease network

Mendelian inheritance of familial prostate cancer.

Family history and the risk of prostate cancer.

Hereditary Prostate Cancer: Epidemiologic and Clinical Features