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BACKGROUND - A 27-year-old woman was seen for long QT syndrome. She was found to be a carrier of 2 variants, KCNQ1 Val162Met and KCNH2 Ser55Leu, and both were classified as "pathogenic" by a diagnostic laboratory, in part because of sequence proximity to other known pathogenic variants.
OBJECTIVE - The purpose of this study was to assess the relationship between both the KCNQ1 and KCNH2 variants and clinical significance using protein structure, in vitro functional assays, and familial segregation.
METHODS - We used co-segregation analysis of family, patch clamp in vitro electrophysiology, and structural analysis using recently released cryo-electron microscopy structures of both channels.
RESULTS - The structural analysis indicates that KCNQ1 Val162Met is oriented away from functionally important regions while Ser55Leu is positioned at domains critical for KCNH2 fast inactivation. Clinical phenotyping and electrophysiology study further support the conclusion that KCNH2 Ser55Leu is correctly classified as pathogenic but KCNQ1 Val162Met is benign.
CONCLUSION - Proximity in sequence space does not always translate accurately to proximity in 3-dimensional space. Emerging structural methods will add value to pathogenicity prediction.
Copyright © 2018 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.

A major challenge in evaluating the contribution of rare variants to complex disease is identifying enough copies of the rare alleles to permit informative statistical analysis. To investigate the contribution of rare variants to the risk of type 2 diabetes (T2D) and related traits, we performed deep whole-genome analysis of 1,034 members of 20 large Mexican-American families with high prevalence of T2D. If rare variants of large effect accounted for much of the diabetes risk in these families, our experiment was powered to detect association. Using gene expression data on 21,677 transcripts for 643 pedigree members, we identified evidence for large-effect rare-variant -expression quantitative trait loci that could not be detected in population studies, validating our approach. However, we did not identify any rare variants of large effect associated with T2D, or the related traits of fasting glucose and insulin, suggesting that large-effect rare variants account for only a modest fraction of the genetic risk of these traits in this sample of families. Reliable identification of large-effect rare variants will require larger samples of extended pedigrees or different study designs that further enrich for such variants.

Over the past 20 years, a large body of experimental and epidemiologic evidence has linked sleep duration and quality to glucose homeostasis, although the mechanistic pathways remain unclear. The aim of the current study was to determine whether genetic variation influencing both sleep and glucose regulation could underlie their functional relationship. We hypothesized that the genetic regulation of electroencephalographic (EEG) activity during non-rapid eye movement sleep, a highly heritable trait with fingerprint reproducibility, is correlated with the genetic control of metabolic traits including insulin sensitivity and β-cell function. We tested our hypotheses through univariate and bivariate heritability analyses in a three-generation pedigree with in-depth phenotyping of both sleep EEG and metabolic traits in 48 family members. Our analyses accounted for age, sex, adiposity, and the use of psychoactive medications. In univariate analyses, we found significant heritability for measures of fasting insulin sensitivity and β-cell function, for time spent in slow-wave sleep, and for EEG spectral power in the delta, theta, and sigma ranges. Bivariate heritability analyses provided the first evidence for a shared genetic control of brain activity during deep sleep and fasting insulin secretion rate.
© 2017 by the American Diabetes Association.

BACKGROUND AND PURPOSE - Apoptosis-inducing factor mitochondrion-associated-1 (AIFM1) in mitochondria has captured a great deal of attention due to its well-described function in apoptosis. Mutations in AIFM1 have resulted in multiple clinical phenotypes, including X-linked Charcot-Marie-Tooth disease type 4. These syndromes usually involve multiple locations within the nervous system and/or multiple organs. This study describes a novel missense mutation in AIFM1 and its associated peripheral nerve disease.
METHODS - Patients with AIFM1 mutation were characterized clinically, electrophysiologically, genetically and by magnetic resonance imaging. The fibroblasts were isolated from the patients to study mitochondrial OXPHOS complexes.
RESULTS - We identified a family with a novel missense mutation (Phe210Leu) in AIFM1 who developed an isolated late-onset axonal polyneuropathy in which the central nervous system and other organs were spared. Interestingly, this Phe210Leu mutation resulted in abnormal assembly of mitochondrial complex I and III, and failed to disrupt AIFM1 binding with mitochondrial intermembrane space import and assembly protein 40 (MIA40) in the patients' cells. Deficiency of either AIFM1 or MIA40 is known to impair the assembly of mitochondrial complex I and IV. However, levels of both AIFM1 and MIA40 were unchanged.
CONCLUSIONS - Phe210Leu mutation in AIFM1 induces an axonal polyneuropathy that might be contributed by the misassembly of mitochondrial complex I and III. This misassembly appears to be independent of the traditional mechanism via AIFM1/MIA40 deficiency.
© 2017 EAN.

Purpose - To identify the causes of autosomal dominant retinitis pigmentosa (adRP) in a cohort of families without mutations in known adRP genes and consequently to characterize a novel dominant-acting missense mutation in SAG.
Methods - Patients underwent ophthalmologic testing and were screened for mutations using targeted-capture and whole-exome next-generation sequencing. Confirmation and additional screening were done by Sanger sequencing. Haplotypes segregating with the mutation were determined using short tandem repeat and single nucleotide variant polymorphisms. Genealogies were established by interviews of family members.
Results - Eight families in a cohort of 300 adRP families, and four additional families, were found to have a novel heterozygous mutation in the SAG gene, c.440G>T; p.Cys147Phe. Patients exhibited symptoms of retinitis pigmentosa and none showed symptoms characteristic of Oguchi disease. All families are of Hispanic descent and most were ascertained in Texas or California. A single haplotype including the SAG mutation was identified in all families. The mutation dramatically alters a conserved amino acid, is extremely rare in global databases, and was not found in 4000+ exomes from Hispanic controls. Molecular modeling based on the crystal structure of bovine arrestin-1 predicts protein misfolding/instability.
Conclusions - This is the first dominant-acting mutation identified in SAG, a founder mutation possibly originating in Mexico several centuries ago. The phenotype is clearly adRP and is distinct from the previously reported phenotypes of recessive null mutations, that is, Oguchi disease and recessive RP. The mutation accounts for 3% of the 300 families in the adRP Cohort and 36% of Hispanic families in this cohort.

A cell's phenotype is the observable actualization of complex interactions between its genome, epigenome, and local environment. While traditional views in cancer have held that cellular and tumor phenotypes are largely functions of genomic instability, increasing attention has recently been given to epigenetic and microenvironmental influences. Such non-genetic factors allow cancer cells to experience intrinsic diversity and plasticity, and at the tumor level can result in phenotypic heterogeneity and treatment evasion. In 2006, Takahashi and Yamanaka exploited the epigenome's plasticity by "reprogramming" differentiated cells into a pluripotent state by inducing expression of a cocktail of four transcription factors. Recent advances in cancer biology have shown not only that cellular reprogramming is possible for malignant cells, but it may provide a foundation for future therapies. Nevertheless, cell reprogramming experiments are frequently plagued by low efficiency, activation of aberrant transcriptional programs, instability, and often rely on expertise gathered from systems which may not translate directly to cancer. Here, we review a theoretical framework tracing back to Waddington's epigenetic landscape which may be used to derive quantitative and qualitative understanding of cellular reprogramming. Implications for tumor heterogeneity, evolution and adaptation are discussed in the context of designing new treatments to re-sensitize recalcitrant tumors. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.
Copyright © 2017. Published by Elsevier B.V.

Many large genome-wide association studies (GWAS) have identified common blood pressure (BP) variants. However, most of the identified BP variants do not overlap with the linkage evidence observed from family studies. We thus hypothesize that multiple rare variants contribute to the observed linkage evidence. We performed linkage analysis using 517 individuals in 130 European families from the Cleveland Family Study (CFS) who have been genotyped on the Illumina OmniExpress Exome array. The largest linkage peak was observed on chromosome 16p13 (MLOD = 2.81) for systolic blood pressure (SBP). Follow-up conditional linkage and association analyses in the linkage region identified multiple rare, coding variants in RBFOX1 associated with reduced SBP. In a 17-member CFS family, carriers of the missense variant rs149974858 are normotensive despite being obese (average BMI = 60 kg/m2). Gene-based association test of rare variants using SKAT-O showed significant association with SBP (p-value = 0.00403) and DBP (p-value = 0.0258) in the CFS participants and the association was replicated in large independent replication studies (N = 57,234, p-value = 0.013 for SBP, 0.0023 for PP). RBFOX1 is expressed in brain tissues, the atrial appendage and left ventricle in the heart, and in skeletal muscle tissues, organs/tissues which are potentially related to blood pressure. Our study showed that associations of rare variants could be efficiently detected using family information.

With a combined carrier frequency of 1:200, heteroplasmic mitochondrial DNA (mtDNA) mutations cause human disease in ∼1:5000 of the population. Rapid shifts in the level of heteroplasmy seen within a single generation contribute to the wide range in the severity of clinical phenotypes seen in families transmitting mtDNA disease, consistent with a genetic bottleneck during transmission. Although preliminary evidence from human pedigrees points towards a random drift process underlying the shifting heteroplasmy, some reports describe differences in segregation pattern between different mtDNA mutations. However, based on limited observations and with no direct comparisons, it is not clear whether these observations simply reflect pedigree ascertainment and publication bias. To address this issue, we studied 577 mother-child pairs transmitting the m.11778G>A, m.3460G>A, m.8344A>G, m.8993T>G/C and m.3243A>G mtDNA mutations. Our analysis controlled for inter-assay differences, inter-laboratory variation and ascertainment bias. We found no evidence of selection during transmission but show that different mtDNA mutations segregate at different rates in human pedigrees. m.8993T>G/C segregated significantly faster than m.11778G>A, m.8344A>G and m.3243A>G, consistent with a tighter mtDNA genetic bottleneck in m.8993T>G/C pedigrees. Our observations support the existence of different genetic bottlenecks primarily determined by the underlying mtDNA mutation, explaining the different inheritance patterns observed in human pedigrees transmitting pathogenic mtDNA mutations.
© The Author 2016. Published by Oxford University Press.

BACKGROUND - Plasma lipid levels are highly heritable traits, but known genetic loci can only explain a small portion of their heritability.
METHODS AND RESULTS - In this study, we analyzed the role of parental levels of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TGs) in explaining the values of the corresponding traits in adult offspring. We also evaluated the contribution of nongenetic factors that influence lipid traits (age, body mass index, smoking, medications, and menopause) alone and in combination with variability at the genetic loci known to associate with TC, LDL-C, HDL-C, and TG levels. We performed comparisons among different sex-specific regression models in 416 families from the Framingham Heart Study and 304 from the SardiNIA cohort. Models including parental lipid levels explain significantly more of the trait variation than models without these measures, explaining up to ≈39% of the total trait variation. Of this variation, the parent-of-origin effect explains as much as ≈15% and it does so in a sex-specific way. This observation is not owing to shared environment, given that spouse-pair correlations were negligible (<1.5% explained variation in all cases) and is distinct from previous genetic and acquired factors that are known to influence serum lipid levels.
CONCLUSIONS - These findings support the concept that unknown genetic and epigenetic contributors are responsible for most of the heritable component of the plasma lipid phenotype, and that, at present, the clinical utility of knowing age-matched parental lipid levels in assessing risk of dyslipidemia supersedes individual locus effects. Our results support the clinical utility of knowing parental lipid levels in assessing future risk of dyslipidemia.
© 2015 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Sequencing family DNA samples provides an attractive alternative to population based designs to identify rare variants associated with human disease due to the enrichment of causal variants in pedigrees. Previous studies showed that genotype calling accuracy can be improved by modeling family relatedness compared to standard calling algorithms. Current family-based variant calling methods use sequencing data on single variants and ignore the identity-by-descent (IBD) sharing along the genome. In this study we describe a new computational framework to accurately estimate the IBD sharing from the sequencing data, and to utilize the inferred IBD among family members to jointly call genotypes in pedigrees. Through simulations and application to real data, we showed that IBD can be reliably estimated across the genome, even at very low coverage (e.g. 2X), and genotype accuracy can be dramatically improved. Moreover, the improvement is more pronounced for variants with low frequencies, especially at low to intermediate coverage (e.g. 10X to 20X), making our approach effective in studying rare variants in cost-effective whole genome sequencing in pedigrees. We hope that our tool is useful to the research community for identifying rare variants for human disease through family-based sequencing.