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Abstract Background Esophageal squamous cell carcinomas (ESCC) is the fourth most lethal cancer in China. Previous studies reveal several highly conserved mutational processes in ESCC. However, it remains unclear what are the true regulators of the mutational processes. Results We analyzed the somatic mutational signatures in 302 paired whole-exome sequencing data of ESCC in a Chinese population for potential regulators of the mutational processes. We identified three conserved subtypes based on the mutational signatures with significantly different clinical outcomes. Our results show that patients of different subpopulations of Chinese differ significantly in the activity of the “NpCpG” signature (FDR = 0.00188). In addition, we report ZNF750 and CDC27, of which the somatic statuses and the genetic burdens consistently influence the activities of specific mutational signatures in ESCC: the somatic ZNF750 status is associated with the AID/APOBEC-related mutational process (FDR = 0.0637); the somatic CDC27 copy-number is associated with the “NpCpG” (FDR = 0.00615) and the AID/APOBEC-related mutational processes (FDR = 8.69 × 10− 4). The burdens of germline variants in the two genes also significantly influence the activities of the same somatic mutational signatures (FDR

The increasing prevalence of diagnosed breast cancer cases emphasizes the urgent demand for developing new prognostic breast cancer biomarkers. Copy number alteration (CNA) burden measured as the percentage of the genome affected by CNAs has emerged as a potential candidate to this aim. Using somatic CNA data obtained from METABRIC (Molecular Taxonomy of Breast Cancer International Consortium), we implemented Kaplan-Meier estimators and Cox proportional hazards models to examine the association of CNA burden with patient’s overall survival (OS) and disease specific survival (DSS). We also evaluated the association by considering patients’ age and tumor subtypes using stratified Cox models. We delineated the distribution of CNA burden in sample genomes and highlighted chromosomes 1, 8, and 16 as the carriers of the highest CNA burden. We identified a strong association between CNA burden and age as well as CNA burden and breast cancer PAM50 subtypes. We found that controlling the effects of both age (bound by 45-year) and PAM50 subtypes on patient survival using stratified Cox models, would still result in significant association between CNA burden and patients overall survival in both Discovery and Validation data. The same trend was observed in disease specific survival when only PAM50 subtypes were controlled in the stratified Cox models. Our analysis showed that there is a significant association between CNA burden and breast cancer survival. This result is also validated by using TCGA (The Cancer Genome Atlas) data. CNA burden of breast cancer patients has a considerable potential to be used as a novel prognostic biomarker.

Myosin motors are the fundamental force-generating elements of muscle contraction. Variation in the human β-cardiac myosin heavy chain gene (MYH7) can lead to hypertrophic cardiomyopathy (HCM), a heritable disease characterized by cardiac hypertrophy, heart failure, and sudden cardiac death. How specific myosin variants alter motor function or clinical expression of disease remains incompletely understood. Here, we combine structural models of myosin from multiple stages of its chemomechanical cycle, exome sequencing data from two population cohorts of 60,706 and 42,930 individuals, and genetic and phenotypic data from 2,913 patients with HCM to identify regions of disease enrichment within β-cardiac myosin. We first developed computational models of the human β-cardiac myosin protein before and after the myosin power stroke. Then, using a spatial scan statistic modified to analyze genetic variation in protein 3D space, we found significant enrichment of disease-associated variants in the converter, a kinetic domain that transduces force from the catalytic domain to the lever arm to accomplish the power stroke. Focusing our analysis on surface-exposed residues, we identified a larger region significantly enriched for disease-associated variants that contains both the converter domain and residues on a single flat surface on the myosin head described as the myosin mesa. Notably, patients with HCM with variants in the enriched regions have earlier disease onset than patients who have HCM with variants elsewhere. Our study provides a model for integrating protein structure, large-scale genetic sequencing, and detailed phenotypic data to reveal insight into time-shifted protein structures and genetic disease. [ABSTRACT FROM AUTHOR]

Background: The list of genomic loci associated with multiple sclerosis (MS) susceptibility outside the major histocompatibility complex (MHC) in patients of Northern European (NE) ancestry has increased to 103. Despite the extraordinarily high MS prevalence in the isolated Sardinian population, the contribution of genetic risk factors to MS in Sardinia is largely not understood. Objective: The objective of this paper is to examine the relevance of non-MHC MS susceptibility variants in Sardinia. Methods: We examined a log-additive MS-specific genetic burden score (MSGB) using 110 NE-derived risk alleles in a dataset of 75 Sardinian cases, 346 Sardinian controls and 177 cases and 1967 controls from the United States (US). Results: Sardinian cases demonstrate a heavier non-MHC MSGB load than Sardinian controls and US cases (p = 2E-06, p = 1E-06, respectively). Furthermore, Sardinian controls carry a heavier burden than US controls (p = 2E-14). Our results confirm the limited ability of the 110-SNP MSGB to predict disease status in Sardinia (AUROC = 0.629). Conclusions: Risk alleles discovered in samples of NE ancestry are relevant to MS in Sardinia. Our results suggest a general enrichment of MS susceptibility alleles in Sardinians, encouraging the pursuit of further studies of MS in this population. [ABSTRACT FROM AUTHOR]

Abstract: We discuss categories of genetic diversity in humans. Neutral diversity, population differences in frequencies of genetic markers that we think are invisible to natural selection, provides a passive record of population history but is otherwise of little interest in human biology. Genetic variation related to disease can be separated into mutational noise and variation due to selection, either ongoing selection else effects of a past environment. We distinguish consequences of genetic diversity for fitness, relevant to evolution, and consequences for well-being, relevant to medicine and public health. We call genetic variation that causes impairment of health or well-being of individual humans “apparent genetic burden” and variation that has effects on fitness but not well-being “unapparent genetic burden”. We use “burden” to distinguish these notions from the classical concept of “genetic load” that refers to effects on population fitness, a concept formulated by Morton et al. [Morton, N.E., Crow, J.F., Muller, H.J., 1956. An estimate of the mutational damage in man from data on consanguineous marriages. Proc. Natl. Acad. Sci. U.S.A. 42, 855–863]. We distinguish adapted genes and adapted genotypes: an adapted gene is a gene that increases fitness of its bearer either in heterozygous or homozygous state or both, while an adapted genotype is a genotype that increases fitness of its bearer but is not transmitted intact to future generations. Balanced polymorphisms in which the heterozygote is superior in fitness may generate most adapted genotypes. In the face of major rapid environmental change adapted genotypes appear first but over time they are replaced by adapted genes. The presence of adapted genotypes is a good indication of recent environmental change: for example, there are apparently many polymorphisms in domestic animals of this nature, responses to domestication, and many fewer in wild animals (and in humans). [Copyright &y& Elsevier]

While previous results of genetic association studies for common, complex diseases (eg., coronary artery disease, CAD) have been disappointing, examination of multiple related genes within a physiologic pathway may provide improved resolution. This paper describes a method of calculating a genetic risk score (GRS) for a clinical endpoint by integrating data from many candidate genes and multiple intermediate phenotypes (IPs). First, the association of all single nucleotide polymorphisms (SNPs) to an IP is determined and regressionβ-coefficients are used to calculate an IP-specific GRS for each individual, repeating this analysis for every IP. Next, the IPs are assessed by a second regression as predictors of the clinical endpoint. Each IP's individual GRS is then weighted by the regressionβ-coefficients from the second step, creating a single, composite GRS. As an example, 3,172 patients undergoing coronary angiography were evaluated for 3 SNPs from the cholesterol metabolism pathway. Although these data provide only a preliminary example, the GRS method detected significant differences in CAD by GRS group, whereas separate genotypes did not. These results illustrate the potential of the GRS methodology for multigenic risk evaluation and suggest that such approaches deserve further examination in common, complex diseases such as CAD. [ABSTRACT FROM AUTHOR]