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INTRODUCTION - HLA class II allele, DRB1*03:01, is the most common genetic risk factor for autoimmune hepatitis (AIH), but other unrecognized HLA related risks exist.
METHODS - We compared the HLA class I (A, B, C) and class II (DR, DQ, DP) typing between patients with well-characterized AIH and healthy controls by high resolution sequencing of the HLA region. Seventy-three patients with AIH and 87 healthy controls were included. Association between HLA alleles and AIH was considered singly and in clusters and adjusted for age, gender, and DRB1*03:01.
RESULTS - DRB1*03:01 was singly associated with AIH among whites (odds ratio [OR]: 3.09, P = 0.002) and carriers of DRB1*03:01 also carried DQA*05:01 and DQB1*02:01. Significant HLA class I alleles were associated with AIH including those belonging to the A03 (OR: 0.4, P = 0.01) and B44 supertype (OR: 0.44, P = 0.03). Further refinement of HLA-A by binding pocket structure revealed that the sequence Y(F/T)AVMENV(H/Q)Y, corresponding to HLA-A alleles A*03:01-02; *31:01; *32:02, was protective for AIH (OR: 0.3, P = 0.002). A protective association also existed for alleles belonging to the HLA-B binding pocket structure Y(H/Y)TVKEISNY (OR: 0.35, P = 0.01), corresponding to HLA-B alleles: B*40:01-02; *41:02; *44:02-03; *45:01; *49:01; *50:01-02. Associations with specific class I alleles belonging to the 8.1 ancestral haplotype (HLA-A*01:01, HLA-B*08:01, HLA-C*07:01) were not significant when considered jointly with DRB1*03:01 and reported protective class I alleles.
DISCUSSION - Our study identified novel supertypes and HLA-A and B peptide binding structures protective against AIH. Further risk assessment of class I molecules remains important in AIH as they are key mediators of adaptive immunity.
Importance - Atrial fibrillation (AF) is the most common arrhythmia affecting 1% of the population. Young individuals with AF have a strong genetic association with the disease, but the mechanisms remain incompletely understood.
Objective - To perform large-scale whole-genome sequencing to identify genetic variants related to AF.
Design, Setting, and Participants - The National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine Program includes longitudinal and cohort studies that underwent high-depth whole-genome sequencing between 2014 and 2017 in 18 526 individuals from the United States, Mexico, Puerto Rico, Costa Rica, Barbados, and Samoa. This case-control study included 2781 patients with early-onset AF from 9 studies and identified 4959 controls of European ancestry from the remaining participants. Results were replicated in the UK Biobank (346 546 participants) and the MyCode Study (42 782 participants).
Exposures - Loss-of-function (LOF) variants in genes at AF loci and common genetic variation across the whole genome.
Main Outcomes and Measures - Early-onset AF (defined as AF onset in persons <66 years of age). Due to multiple testing, the significance threshold for the rare variant analysis was P = 4.55 × 10-3.
Results - Among 2781 participants with early-onset AF (the case group), 72.1% were men, and the mean (SD) age of AF onset was 48.7 (10.2) years. Participants underwent whole-genome sequencing at a mean depth of 37.8 fold and mean genome coverage of 99.1%. At least 1 LOF variant in TTN, the gene encoding the sarcomeric protein titin, was present in 2.1% of case participants compared with 1.1% in control participants (odds ratio [OR], 1.76 [95% CI, 1.04-2.97]). The proportion of individuals with early-onset AF who carried a LOF variant in TTN increased with an earlier age of AF onset (P value for trend, 4.92 × 10-4), and 6.5% of individuals with AF onset prior to age 30 carried a TTN LOF variant (OR, 5.94 [95% CI, 2.64-13.35]; P = 1.65 × 10-5). The association between TTN LOF variants and AF was replicated in an independent study of 1582 patients with early-onset AF (cases) and 41 200 control participants (OR, 2.16 [95% CI, 1.19-3.92]; P = .01).
Conclusions and Relevance - In a case-control study, there was a statistically significant association between an LOF variant in the TTN gene and early-onset AF, with the variant present in a small percentage of participants with early-onset AF (the case group). Further research is necessary to understand whether this is a causal relationship.
Using an integrated approach to characterize the pancreatic tissue and isolated islets from a 33-year-old with 17 years of type 1 diabetes (T1D), we found that donor islets contained β cells without insulitis and lacked glucose-stimulated insulin secretion despite a normal insulin response to cAMP-evoked stimulation. With these unexpected findings for T1D, we sequenced the donor DNA and found a pathogenic heterozygous variant in the gene encoding hepatocyte nuclear factor-1α (HNF1A). In one of the first studies of human pancreatic islets with a disease-causing HNF1A variant associated with the most common form of monogenic diabetes, we found that HNF1A dysfunction leads to insulin-insufficient diabetes reminiscent of T1D by impacting the regulatory processes critical for glucose-stimulated insulin secretion and suggest a rationale for a therapeutic alternative to current treatment.
Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
BACKGROUND - High throughput sequencing technology enables the both the human genome and transcriptome to be screened at the single nucleotide resolution. Tools have been developed to infer single nucleotide variants (SNVs) from both DNA and RNA sequencing data. To evaluate how much difference can be expected between DNA and RNA sequencing data, and among tissue sources, we designed a study to examine the single nucleotide difference among five sources of high throughput sequencing data generated from the same individual, including exome sequencing from blood, tumor and adjacent normal tissue, and RNAseq from tumor and adjacent normal tissue.
RESULTS - Through careful quality control and analysis of the SNVs, we found little difference between DNA-DNA pairs (1%-2%). However, between DNA-RNA pairs, SNV differences ranged anywhere from 10% to 20%.
CONCLUSIONS - Only a small portion of these differences can be explained by RNA editing. Instead, the majority of the DNA-RNA differences should be attributed to technical errors from sequencing and post-processing of RNAseq data. Our analysis results suggest that SNV detection using RNAseq is subject to high false positive rates.
Tuberous sclerosis complex (TSC) is a pediatric disorder of dysregulated growth and differentiation caused by loss of function mutations in either the TSC1 or TSC2 genes, which regulate mTOR kinase activity. To study aberrations of early development in TSC, we generated induced pluripotent stem cells using dermal fibroblasts obtained from patients with TSC. During validation, we found that stem cells generated from TSC patients had a very high rate of integration of the reprogramming plasmid containing a shRNA against TP53. We also found that loss of one allele of TSC2 in human fibroblasts is sufficient to increase p53 levels and impair stem cell reprogramming. Increased p53 was also observed in TSC2 heterozygous and homozygous mutant human stem cells, suggesting that the interactions between TSC2 and p53 are consistent across cell types and gene dosage. These results support important contributions of TSC2 heterozygous and homozygous mutant cells to the pathogenesis of TSC and the important role of p53 during reprogramming.
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We report a case of severe type I hyperlipoproteinemia caused by autoimmunity against lipoprotein lipase (LPL) in the context of presymptomatic Sjögren's syndrome. A 7-year-old mixed race (Caucasian/African American) girl was admitted to the intensive care unit at Vanderbilt Children's Hospital with acute pancreatitis and shock. She was previously healthy aside from asthma and history of Hashimoto's thyroiditis. Admission triglycerides (TGs) were 2191 mg/dL but returned to normal during the hospital stay and in the absence of food intake. At discharge, she was placed on a low-fat, low-sugar diet. She did not respond to fibrates, prescription fish oil, metformin, or orlistat, and during the following 2 years, she was hospitalized several times with recurrent pancreatitis. Except for a heterozygous mutation in the promoter region of LPL, predicted to have no clinical significance, she had no further mutations in genes known to affect TG metabolism and to cause inherited type I hyperlipoproteinemia, such as APOA5, APOC2, GPIHBP1, or LMF1. When her TG levels normalized after incidental use of prednisone, an autoimmune mechanism was suspected. Immunoblot analyses showed the presence of autoantibodies to LPL in the patient's plasma. Autoantibodies to LPL decreased by 37% while patient was on prednisone, and by 68% as she subsequently transitioned to hydroxychloroquine monotherapy. While on hydroxychloroquine, she underwent a supervised high-fat meal challenge and showed normal ability to metabolize TG. For the past 3 years and 6 months, she has had TG consistently <250 mg/dL, and no symptoms of, or readmissions for, pancreatitis.
Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.
Mitochondrial dysfunction is elevated in very early stages of Alzheimer's disease and exacerbates oxidative stress, which contributes to disease pathology. Mitochondria were isolated from 4-month-old wild-type mice, transgenic mice carrying the APP and PSEN1 mutations, mice with decreased brain and mitochondrial ascorbate (vitamin C) via heterozygous knockout of the sodium dependent vitamin C transporter (SVCT2) and transgenic APP/PSEN1 mice with heterozygous SVCT2 expression. Mitochondrial isolates from SVCT2 mice were observed to consume less oxygen using high-resolution respirometry, and also exhibited decreased mitochondrial membrane potential compared to wild type isolates. Conversely, isolates from young (4 months) APP/PSEN1 mice consumed more oxygen, and exhibited an increase in mitochondrial membrane potential, but had a significantly lower ATP/ADP ratio compared to wild type isolates. Greater levels of reactive oxygen species were also produced in mitochondria isolated from both APP/PSEN1 and SVCT2 mice compared to wild type isolates. Acute administration of ascorbate to mitochondria isolated from wild-type mice increased oxygen consumption compared with untreated mitochondria suggesting ascorbate may support energy production. This study suggests that both presence of amyloid and ascorbate deficiency can contribute to mitochondrial dysfunction, even at an early, prodromal stage of Alzheimer's disease, although occurring via different pathways. Ascorbate may, therefore, provide a useful preventative strategy against neurodegenerative disease, particularly in populations most at risk for Alzheimer's disease in which stores are often depleted through mitochondrial dysfunction and elevated oxidative stress.
Copyright © 2017 Elsevier Inc. All rights reserved.
Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. VIDEO ABSTRACT.
Copyright © 2017 Elsevier Inc. All rights reserved.
Power/sample size (power) analysis estimates the likelihood of successfully finding the statistical significance in a data set. There has been a growing recognition of the importance of power analysis in the proper design of experiments. Power analysis is complex, yet necessary for the success of large studies. It is important to design a study that produces statistically accurate and reliable results. Power computation methods have been well established for both microarray-based gene expression studies and genotyping microarray-based genome-wide association studies. High-throughput sequencing (HTS) has greatly enhanced our ability to conduct biomedical studies at the highest possible resolution (per nucleotide). However, the complexity of power computations is much greater for sequencing data than for the simpler genotyping array data. Research on methods of power computations for HTS-based studies has been recently conducted but is not yet well known or widely used. In this article, we describe the power computation methods that are currently available for a range of HTS-based studies, including DNA sequencing, RNA-sequencing, microbiome sequencing and chromatin immunoprecipitation sequencing. Most importantly, we review the methods of power analysis for several types of sequencing data and guide the reader to the relevant methods for each data type.