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      The need for uncertainty quantification in machine-assisted medical decision making

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      Nature Machine Intelligence
      Springer Nature

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          The mystery of missing heritability: Genetic interactions create phantom heritability.

          Human genetics has been haunted by the mystery of "missing heritability" of common traits. Although studies have discovered >1,200 variants associated with common diseases and traits, these variants typically appear to explain only a minority of the heritability. The proportion of heritability explained by a set of variants is the ratio of (i) the heritability due to these variants (numerator), estimated directly from their observed effects, to (ii) the total heritability (denominator), inferred indirectly from population data. The prevailing view has been that the explanation for missing heritability lies in the numerator--that is, in as-yet undiscovered variants. While many variants surely remain to be found, we show here that a substantial portion of missing heritability could arise from overestimation of the denominator, creating "phantom heritability." Specifically, (i) estimates of total heritability implicitly assume the trait involves no genetic interactions (epistasis) among loci; (ii) this assumption is not justified, because models with interactions are also consistent with observable data; and (iii) under such models, the total heritability may be much smaller and thus the proportion of heritability explained much larger. For example, 80% of the currently missing heritability for Crohn's disease could be due to genetic interactions, if the disease involves interaction among three pathways. In short, missing heritability need not directly correspond to missing variants, because current estimates of total heritability may be significantly inflated by genetic interactions. Finally, we describe a method for estimating heritability from isolated populations that is not inflated by genetic interactions.
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            Verification and Validation in Scientific Computing

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              Is Open Access

              Interplay between Epigenetics and Genetics in Cancer

              Genomic instability, which occurs through both genetic mechanisms (underlying inheritable phenotypic variations caused by DNA sequence-dependent alterations, such as mutation, deletion, insertion, inversion, translocation, and chromosomal aneuploidy) and epigenomic aberrations (underlying inheritable phenotypic variations caused by DNA sequence-independent alterations caused by a change of chromatin structure, such as DNA methylation and histone modifications), is known to promote tumorigenesis and tumor progression. Mechanisms involve both genomic instability and epigenomic aberrations that lose or gain the function of genes that impinge on tumor suppression/prevention or oncogenesis. Growing evidence points to an epigenome-wide disruption that involves large-scale DNA hypomethylation but specific hypermethylation of tumor suppressor genes, large blocks of aberrant histone modifications, and abnormal miRNA expression profile. Emerging molecular details regarding the modulation of these epigenetic events in cancer are used to illustrate the alterations of epigenetic molecules, and their consequent malfunctions could contribute to cancer biology. More recently, intriguing evidence supporting that genetic and epigenetic mechanisms are not separate events in cancer has been emerging; they intertwine and take advantage of each other during tumorigenesis. In addition, we discuss the collusion between epigenetics and genetics mediated by heterochromatin protein 1, a major component of heterochromatin, in order to maintain genome integrity.
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                Author and article information

                Journal
                Nature Machine Intelligence
                Nat Mach Intell
                Springer Nature
                2522-5839
                January 2019
                January 7 2019
                January 2019
                : 1
                : 1
                : 20-23
                Article
                10.1038/s42256-018-0004-1
                eb25080c-4bb8-4649-b55c-4d0320e4cdfc
                © 2019

                http://www.springer.com/tdm

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