Jason D. Merker

Measurement and clinical monitoring of human lymphocyte clonality by massively parallel VDJ pyrosequencing

Massively parallel sequencing of rearranged immune receptor genes permits detection and tracking of specific immune cell populations in normal and pathological contexts. Like a reporter who serially unearths fragments of a story until a plausible picture of the latest scandal emerges, scientists have over time gathered pieces of the vast amount of information inherent in the highly recombined genes of the human immune system—probing their complexity, seeking a disease diagnosis, or hunting for evidence of remission. Back in 1987, Susumu Tonegawa won the Nobel Prize in Physiology or Medicine for discovering the genetics behind the diversity of human antibodies—a process called V-D-J recombination. Now, more than 20 years later, scientists at Stanford University and 454 Life Sciences have used powerful next-generation DNA sequencing technology to comprehensively characterize the products of V-D-J recombination in both cancer patients and healthy volunteers. Indeed, this ability to exhaustively profile the human immune response will help to untangle some of biomedicine’s most knotty problems—cancer, autoimmune disease, and vaccine development. B and T lymphocytes, cells of the adaptive immune system, build the blueprints for myriad antigen-recognizing proteins—immunoglobulins (Ig) and T cell receptors—by recombination within variable (V), diversity (D), and joining (J) gene segments to rearrange the intervening highly variable DNA sequences that can specify numerous antigen recognition domains. All of this reassortment creates a repertoire of receptors that recognizes scads of molecules from foreign invaders (antigens), a process that spurs the immune system to respond to the threat. When an immune cell sporting a particular antigen receptor finds and binds its matching antigen, the cell divides repeatedly, giving rise to many genetically identical lymphocytes that target a particular antigen for elimination. In contrast to this vibrant diversity of healthy immune systems, those of people with B lymphocyte– or T lymphocyte–based cancers (lymphomas or leukemias) generate cells that express a single dominant (clonal) receptor. In the new work, Boyd et al. performed massively parallel DNA sequencing of rearranged IgH gene loci in blood and tissue samples from cancer patients and healthy people to examine the diversity of their B cells, the immune cells that make antibodies. To this end, they amplified the rearranged IgH B cell DNA with a series of primers and the polymerase chain reaction to generate bar-coded, amplified DNA mixtures. These samples were then sequenced and the information was analyzed to determine which DNA segments had been joined to generate the blueprints for the IgH immune molecules. The experimental design used by Boyd et al. employs a high-throughput deep sequencing machine and can accommodate up to 150 samples at a time, providing an intricate snapshot of the immune repertoire. From healthy individuals, the authors were able to estimate the normal complexity of the B cell repertoire. With samples from the cancer patients, they obtained disease-specific signatures of clonal B cell proliferation events. For example, in a lymph node sample from one patient, deep sequencing detected two distinct V-D-J rearrangements. This finding indicates that there were two separate clonal B cell populations in this specimen and, therefore, two different B cell lymphomas. Such signatures could be obtained at the time of disease diagnosis and then monitored on an ongoing basis and thereby used to assess the effects of anticancer therapies that target these clonal populations or for early detection of disease relapse. Characterization of immune cell populations by deep sequencing also may illuminate fundamental aspects of infectious and autoimmune diseases as well as the body’s response to vaccination, gene and cell therapies, and other surgical procedures. The complex repertoire of immune receptors generated by B and T cells enables recognition of diverse threats to the host organism. Here, we show that massively parallel DNA sequencing of rearranged immune receptor loci can provide direct detection and tracking of immune diversity and expanded clonal lymphocyte populations in physiological and pathological contexts. DNA was isolated from blood and tissue samples, a series of redundant primers was used to amplify diverse DNA rearrangements, and the resulting mixtures of bar-coded amplicons were sequenced with long-read ultradeep sequencing. Individual DNA molecules were then characterized on the basis of DNA segments that had been joined to make a functional (or nonfunctional) immune effector. Current experimental designs can accommodate up to 150 samples in a single sequence run, with the depth of sequencing sufficient to identify stable and dynamic aspects of the immune repertoire in both normal and diseased circumstances. These data provide a high-resolution picture of immune spectra in normal individuals and in patients with hematological malignancies, illuminating, in the latter case, both the initial behavior of clonal tumor populations and the later suppression or reemergence of such populations after treatment.

Assuring the quality of next-generation sequencing in clinical laboratory practice

Amy S Gargis, Centers for Disease Control and Prevention Lisa Kalman, Centers for Disease Control and Prevention Meredith W Berry, SeqWright Inc David P Bick, Medical College of Wisconsin David P Dimmock, Medical College of Wisconsin Tina Hambuch, Illumina Clinical Services Fei Lu, SeqWright Inc Elaine Lyon, University of Utah Karl V Voelkerding, University of Utah Barbara Zehnbauer, Emory University

Clinical Interpretation and Implications of Whole-Genome Sequencing

IMPORTANCE Whole-genome sequencing (WGS) is increasingly applied in clinical medicine and is expected to uncover clinically significant findings regardless of sequencing indication. OBJECTIVES To examine coverage and concordance of clinically relevant genetic variation provided by WGS technologies; to quantitate inherited disease risk and pharmacogenomic findings in WGS data and resources required for their discovery and interpretation; and to evaluate clinical action prompted by WGS findings. DESIGN, SETTING, AND PARTICIPANTS An exploratory study of 12 adult participants recruited at Stanford University Medical Center who underwent WGS between November 2011 and March 2012. A multidisciplinary team reviewed all potentially reportable genetic findings. Five physicians proposed initial clinical follow-up based on the genetic findings. MAIN OUTCOMES AND MEASURES Genome coverage and sequencing platform concordance in different categories of genetic disease risk, person-hours spent curating candidate disease-risk variants, interpretation agreement between trained curators and disease genetics databases, burden of inherited disease risk and pharmacogenomic findings, and burden and interrater agreement of proposed clinical follow-up. RESULTS Depending on sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for single nucleotide variant discovery. Genotype concordance was high for previously described single nucleotide genetic variants (99%-100%) but low for small insertion/deletion variants (53%-59%). Curation of 90 to 127 genetic variants in each participant required a median of 54 minutes (range, 5-223 minutes) per genetic variant, resulted in moderate classification agreement between professionals (Gross κ, 0.52; 95% CI, 0.40-0.64), and reclassified 69% of genetic variants cataloged as disease causing in mutation databases to variants of uncertain or lesser significance. Two to 6 personal disease-risk findings were discovered in each participant, including 1 frameshift deletion in the BRCA1 gene implicated in hereditary breast and ovarian cancer. Physician review of sequencing findings prompted consideration of a median of 1 to 3 initial diagnostic tests and referrals per participant, with fair interrater agreement about the suitability of WGS findings for clinical follow-up (Fleiss κ, 0.24; P < 001). CONCLUSIONS AND RELEVANCE In this exploratory study of 12 volunteer adults, the use of WGS was associated with incomplete coverage of inherited disease genes, low reproducibility of detection of genetic variation with the highest potential clinical effects, and uncertainty about clinically reportable findings. In certain cases, WGS will identify clinically actionable genetic variants warranting early medical intervention. These issues should be considered when determining the role of WGS in clinical medicine.

Novel mutations in the inhibitory adaptor protein LNK drive JAK-STAT signaling in patients with myeloproliferative neoplasms

Dysregulated Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling due to activation of tyrosine kinases is a common feature of myeloid malignancies. Here we report the first human disease-related mutations in the adaptor protein LNK, a negative regulator of JAK-STAT signaling, in 2 patients with JAK2 V617F-negative myeloproliferative neoplasms (MPNs). One patient exhibited a 5 base-pair deletion and missense mutation leading to a premature stop codon and loss of the pleckstrin homology (PH) and Src homology 2 (SH2) domains. A second patient had a missense mutation (E208Q) in the PH domain. BaF3-MPL cells transduced with these LNK mutants displayed augmented and sustained thrombopoietin-dependent growth and signaling. Primary samples from MPN patients bearing LNK mutations exhibited aberrant JAK-STAT activation, and cytokine-responsive CD34(+) early progenitors were abnormally abundant in both patients. These findings indicate that JAK-STAT activation due to loss of LNK negative feedback regulation is a novel mechanism of MPN pathogenesis.

Individual Variation in the Germline Ig Gene Repertoire Inferred from Variable Region Gene Rearrangements

Individual variation in the Ig germline gene repertoire leads to individual differences in the combinatorial diversity of the Ab repertoire, but the study of such variation has been problematic. The application of high-throughput DNA sequencing to the study of rearranged Ig genes now makes this possible. The sequencing of thousands of VDJ rearrangements from an individual, either from genomic DNA or expressed mRNA, should allow their germline IGHV, IGHD, and IGHJ repertoires to be inferred. In addition, where previously mere glimpses of diversity could be gained from sequencing studies, new large data sets should allow the rearrangement frequency of different genes and alleles to be seen with clarity. We analyzed the DNA of 108,210 human IgH chain rearrangements from 12 individuals and determined their individual IGH genotypes. The number of reportedly functional IGHV genes and allelic variants ranged from 45 to 60, principally because of variable levels of gene heterozygosity, and included 14 previously unreported IGHV polymorphisms. New polymorphisms of the IGHD3-16 and IGHJ6 genes were also seen. At heterozygous loci, remarkably different rearrangement frequencies were seen for the various IGHV alleles, and these frequencies were consistent between individuals. The specific alleles that make up an individuals Ig genotype may therefore be critical in shaping the combinatorial repertoire. The extent of genotypic variation between individuals is highlighted by an individual with aplastic anemia who appears to lack six contiguous IGHD genes on both chromosomes. These deletions significantly alter the potential expressed IGH repertoire, and possibly immune function, in this individual.

Microarray Detection of Human Parainfluenzavirus 4 Infection Associated with Respiratory Failure in an Immunocompetent Adult

Abstract A pan-viral DNA microarray, the Virochip (University of California, San Francisco), was used to detect human parainfluenzavirus 4 (HPIV-4) infection in an immunocompetent adult presenting with a life-threatening acute respiratory illness. The virus was identified in an endotracheal aspirate specimen, and the microarray results were confirmed by specific polymerase chain reaction and serological analysis for HPIV-4. Conventional clinical laboratory testing using an extensive panel of microbiological tests failed to yield a diagnosis. This case suggests that the potential severity of disease caused by HPIV-4 in adults may be greater than previously appreciated and illustrates the clinical utility of a microarray for broad-based viral pathogen screening.

Diagnosis of a Critical Respiratory Illness Caused by Human Metapneumovirus by Use of a Pan-Virus Microarray

ABSTRACT A pan-virus DNA microarray (Virochip) was used to detect a human metapneumovirus (hMPV) strain associated with a critical respiratory tract infection in an elderly adult with chronic lymphocytic leukemia. This infection had previously eluded diagnosis despite extensive microbiological testing for possible etiologic agents. The patients hMPV strain did not grow in viral culture, and only one of five specific reverse transcription-PCR assays for hMPV was positive.

Next-generation sequencing of acute myeloid leukemia identifies the significance of TP53 , U2AF1 , ASXL1 , and TET2 mutations

We assessed the frequency and clinicopathologic significance of 19 genes currently identified as significantly mutated in myeloid neoplasms, RUNX1, ASXL1, TET2, CEBPA, IDH1, IDH2, DNMT3A, FLT3, NPM1, TP53, NRAS, EZH2, CBL, U2AF1, SF3B1, SRSF2, JAK2, CSF3R, and SETBP1, across 93 cases of acute myeloid leukemia (AML) using capture target enrichment and next-generation sequencing. Of these cases, 79% showed at least one nonsynonymous mutation, and cases of AML with recurrent genetic abnormalities showed a lower frequency of mutations versus AML with myelodysplasia-related changes (P<0.001). Mutational analysis further demonstrated that TP53 mutations are associated with complex karyotype AML, whereas ASXL1 and U2AF1 mutations are associated with AML with myelodysplasia-related changes. Furthermore, U2AF1 mutations were specifically associated with trilineage morphologic dysplasia. Univariate analysis demonstrated that U2AF1 and TP53 mutations are associated with absence of clinical remission, poor overall survival (OS), and poor disease-free survival (DFS; P<0.0001), whereas TET2 and ASXL1 mutations are associated with poor OS (P<0.03). In multivariate analysis, U2AF1 and TP53 mutations retained independent prognostic significance in OS and DFS, respectively. Our results demonstrate unique relationships between mutations in AML, clinicopathologic prognosis, subtype categorization, and morphologic dysplasia.

STAT3 mutations are frequent in CD30+ T-cell lymphomas and T-cell large granular lymphocytic leukemia.

STAT3 mutations are frequent in CD30+ T-cell lymphomas and T-cell large granular lymphocytic leukemia

The impact of rare variation on gene expression across tissues

Rare genetic variants are abundant in humans and are expected to contribute to individual disease risk. While genetic association studies have successfully identified common genetic variants associated with susceptibility, these studies are not practical for identifying rare variants. Efforts to distinguish pathogenic variants from benign rare variants have leveraged the genetic code to identify deleterious protein-coding alleles, but no analogous code exists for non-coding variants. Therefore, ascertaining which rare variants have phenotypic effects remains a major challenge. Rare non-coding variants have been associated with extreme gene expression in studies using single tissues, but their effects across tissues are unknown. Here we identify gene expression outliers, or individuals showing extreme expression levels for a particular gene, across 44 human tissues by using combined analyses of whole genomes and multi-tissue RNA-sequencing data from the Genotype-Tissue Expression (GTEx) project v6p release. We find that 58% of underexpression and 28% of overexpression outliers have nearby conserved rare variants compared to 8% of non-outliers. Additionally, we developed RIVER (RNA-informed variant effect on regulation), a Bayesian statistical model that incorporates expression data to predict a regulatory effect for rare variants with higher accuracy than models using genomic annotations alone. Overall, we demonstrate that rare variants contribute to large gene expression changes across tissues and provide an integrative method for interpretation of rare variants in individual genomes.