Stability and uniqueness of clonal immunoglobulin CDR3 sequences for MRD tracking in multiple myeloma.

Minimal residual disease (MRD) tracking, by next generation sequencing of immunoglobulin sequences, is moving towards clinical implementation in multiple myeloma. However, there is only sparse information available to address whether clonal sequences remain stable for tracking over time, and to what extent light chain sequences are sufficiently unique for tracking. Here, we analyzed immunoglobulin repertoires from 905 plasma cell myeloma and healthy control samples, focusing on the third complementarity determining region (CDR3). Clonal heavy and/or light chain expression was identified in all patients at baseline, with one or more subclones related to the main clone in 3.2%. In 45 patients with 101 sequential samples, the dominant clonal CDR3 sequences remained identical over time, despite differential clonal evolution by whole exome sequencing in 49% of patients. The low frequency of subclonal CDR3 variants, and absence of evolution over time in active multiple myeloma, indicates that tumor cells at this stage are not under selective pressure to undergo antibody affinity maturation. Next, we establish somatic hypermutation and non-templated insertions as the most important determinants of light chain clonal uniqueness, identifying a potentially trackable sequence in the majority of patients. Taken together, we show that dominant clonal sequences identified at baseline are reliable biomarkers for long-term tracking of the malignant clone, including both IGH and the majority of light chain clones.

Monitoring multiple myeloma by quantification of recurrent mutations in serum.

Circulating tumor DNA is a promising biomarker to monitor tumor load and genome alterations. We explored the presence of circulating tumor DNA in multiple myeloma patients and its relation to disease activity during long-term follow-up. We used digital droplet polymerase chain reaction analysis to monitor recurrent mutations, mainly in mitogen activated protein kinase pathway genes NRAS, KRAS and BRAF Mutations were identified by next-generation sequencing or polymerase chain reaction analysis of bone marrow plasma cells, and their presence analyzed in 251 archived serum samples obtained from 20 patients during a period of up to 7 years. In 17 of 18 patients, mutations identified in bone marrow during active disease were also found in a time-matched serum sample. The concentration of mutated alleles in serum correlated with the fraction in bone marrow plasma cells (r=0.507, n=34, P<0.002). There was a striking covariation between circulating mutation levels and M protein in ten out of 11 patients with sequential samples. When relapse evaluation by circulating tumor DNA and M protein could be directly compared, the circulating tumor DNA showed relapse earlier in two patients (3 and 9 months), later in one patient (4 months) and in three patients there was no difference. In three patients with transformation to aggressive disease, the concentrations of mutations in serum increased up to 400 times, an increase that was not seen for the M protein. In conclusion, circulating tumor DNA in myeloma is a multi-faceted biomarker reflecting mutated cells, total tumor mass and transformation to a more aggressive disease. Its properties are both similar and complementary to M protein.

VOLIN and KJON-Two novel hyperdiploid myeloma cell lines.

Multiple myeloma can be divided into two distinct genetic subgroups: hyperdiploid (HRD) or nonhyperdiploid (NHRD) myeloma. Myeloma cell lines are important tools to study myeloma cell biology and are commonly used for preclinical screening and testing of new drugs. With few exceptions human myeloma cell lines are derived from NHRD patients, even though about half of the patients have HRD myeloma. Thus, there is a need for cell lines of HRD origin to enable more representative preclinical studies. Here, we present two novel myeloma cell lines, VOLIN and KJON. Both of them were derived from patients with HRD disease and shared the same genotype as their corresponding primary tumors. The cell lines' chromosomal content, genetic aberrations, gene expression, immunophenotype as well as some of their growth characteristics are described. Neither of the cell lines was found to harbor immunoglobulin heavy chain translocations. The VOLIN cell line was established from a bone marrow aspirate and KJON from peripheral blood. We propose that these unique cell lines may be used as tools to increase our understanding of myeloma cell biology. © 2016 Wiley Periodicals, Inc.

Selection in the host structures the microbiota associated with developing cod larvae (Gadus morhua).

Marine fish larvae are immature upon hatching, and share their environment with high numbers of bacteria. The microbial communities associated with developing fish larvae might be structured by other factors than those important in developing terrestrial animals. Here, we analysed the beta (ß)-diversity of the microbiota associated with developing cod larvae and compared it with the bacterial communities in water and live feed by applying pyrosequencing of bar coded v4 16S rDNA amplicons. A total of 15 phyla were observed in the cod larval microbiota. Proteobacteria was the most abundant, followed by Firmicutes, Bacteroidetes and Actinobacteria. The composition and diversity of the cod larval microbiota changed considerably with age. The temporal and spatial patterns of ß-diversity could not be explained by stochastic processes, and did not coincide with changes in the rearing conditions. Furthermore, the larval microbiota was highly distinct from the water and the live feed microbiota, particularly at early developmental stages. However, the similarity between larval and water microbiota increased with age. This study suggests that strong selection in the host structures the cod larval microbiota. The changes in community structure observed with increasing age can be explained by altered selection pressure due to development of the intestinal system.

A plasma protein-based risk score to predict hip fractures.

As there are effective treatments to reduce hip fractures, identification of patients at high risk of hip fracture is important to inform efficient intervention strategies. To obtain a new tool for hip fracture prediction, we developed a protein-based risk score in the Cardiovascular Health Study using an aptamer-based proteomic platform. The proteomic risk score predicted incident hip fractures and improved hip fracture discrimination in two Trøndelag Health Study validation cohorts using the same aptamer-based platform. When transferred to an antibody-based proteomic platform in a UK Biobank validation cohort, the proteomic risk score was strongly associated with hip fractures (hazard ratio per s.d. increase, 1.64; 95% confidence interval 1.53-1.77). The proteomic risk score, but not available polygenic risk scores for fractures or bone mineral density, improved the C-index beyond the fracture risk assessment tool (FRAX), which integrates information from clinical risk factors (C-index, FRAX 0.735 versus FRAX + proteomic risk score 0.776). The developed proteomic risk score constitutes a new tool for stratifying patients according to hip fracture risk; however, its improvement in hip fracture discrimination is modest and its clinical utility beyond FRAX with information on femoral neck bone mineral density remains to be determined.

Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures.

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Trøndelag Health Study) with circulating proteomics data (aptamer-based 5 K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 × 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. To increase the understanding of the underlying mechanisms, we performed a meta-analysis of the associations between 4860 circulating proteins and risk of fractures using two large cohorts, including 6430 participants with 643 incident hip fractures. We identified 23 proteins/aptamers associated with incident hip fractures. Two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR were most strongly associated with hip fracture risk. High levels of several inflammation-related proteins were also associated with increased hip fracture risk. Pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. Future mechanistic studies should investigate the underlying biology of these novel protein biomarkers which may be potential drug targets.

Transplantation of gut microbiota from old mice into young healthy mice reduces lean mass but not bone mass.

Aging is associated with low bone and lean mass as well as alterations in the gut microbiota (GM). In this study, we determined whether the reduced bone mass and relative lean mass observed in old mice could be transferred to healthy young mice by GM transplantation (GMT). GM from old (21-month-old) and young adult (5-month-old) donors was used to colonize germ-free (GF) mice in three separate studies involving still growing 5- or 11-week-old recipients and 17-week-old recipients with minimal bone growth. The GM of the recipient mice was similar to that of the donors, demonstrating successful GMT. GM from old mice did not have statistically significant effects on bone mass or bone strength, but significantly reduced the lean mass percentage of still growing recipient mice when compared with recipients of GM from young adult mice. The levels of propionate in the cecum of mice receiving old donor GM were significantly lower than those in mice receiving young adult donor GM. Bacteroides ovatus was enriched in the microbiota of recipient mice harboring GM from young adult donors. The presence of B. ovatus was not only significantly associated with high lean mass percentage in mice, but also with lean mass adjusted for fat mass in the large human HUNT cohort. In conclusion, GM from old mice reduces lean mass percentage but not bone mass in young, healthy, still growing recipient mice. Future studies are warranted to determine whether GM from young mice improves the musculoskeletal phenotype of frail elderly recipient mice.

Identification of three bacterial species associated with increased appendicular lean mass: the HUNT study.

Appendicular lean mass (ALM) associates with mobility and bone mineral density (BMD). While associations between gut microbiota composition and ALM have been reported, previous studies rely on relatively small sample sizes. Here, we determine the associations between prevalent gut microbes and ALM in large discovery and replication cohorts with information on relevant confounders within the population-based Norwegian HUNT cohort (n = 5196, including women and men). We show that the presence of three bacterial species - Coprococcus comes, Dorea longicatena, and Eubacterium ventriosum - are reproducibly associated with higher ALM. When combined into an anabolic species count, participants with all three anabolic species have 0.80 kg higher ALM than those without any. In an exploratory analysis, the anabolic species count is positively associated with femoral neck and total hip BMD. We conclude that the anabolic species count may be used as a marker of ALM and BMD. The therapeutic potential of these anabolic species to prevent sarcopenia and osteoporosis needs to be determined.

An atlas of genetic determinants of forearm fracture.

Osteoporotic fracture is among the most common and costly of diseases. While reasonably heritable, its genetic determinants have remained elusive. Forearm fractures are the most common clinically recognized osteoporotic fractures with a relatively high heritability. To establish an atlas of the genetic determinants of forearm fractures, we performed genome-wide association analyses including 100,026 forearm fracture cases. We identified 43 loci, including 26 new fracture loci. Although most fracture loci associated with bone mineral density, we also identified loci that primarily regulate bone quality parameters. Functional studies of one such locus, at TAC4, revealed that Tac4-/- mice have reduced mechanical bone strength. The strongest forearm fracture signal, at WNT16, displayed remarkable bone-site-specificity with no association with hip fractures. Tall stature and low body mass index were identified as new causal risk factors for fractures. The insights from this atlas may improve fracture prediction and enable therapeutic development to prevent fractures.

Mutational analysis and protein profiling predict drug sensitivity in multiple myeloma cell lines.

Introduction: Multiple myeloma (MM) is a heterogeneous disease where cancer-driver mutations and aberrant signaling may lead to disease progression and drug resistance. Drug responses vary greatly, and there is an unmet need for biomarkers that can guide precision cancer medicine in this disease. Methods: To identify potential predictors of drug sensitivity, we applied integrated data from drug sensitivity screening, mutational analysis and functional signaling pathway profiling in 9 cell line models of MM. We studied the sensitivity to 33 targeted drugs and their association with the mutational status of cancer-driver genes and activity level of signaling proteins. Results: We found that sensitivity to mitogen-activated protein kinase kinase 1 (MEK1) and phosphatidylinositol-3 kinase (PI3K) inhibitors correlated with mutations in NRAS/KRAS, and PI3K family genes, respectively. Phosphorylation status of MEK1 and protein kinase B (AKT) correlated with sensitivity to MEK and PI3K inhibition, respectively. In addition, we found that enhanced phosphorylation of proteins, including Tank-binding kinase 1 (TBK1), as well as high expression of B cell lymphoma 2 (Bcl-2), correlated with low sensitivity to MEK inhibitors. Discussion: Taken together, this study shows that mutational status and signaling protein profiling might be used in further studies to predict drug sensitivities and identify resistance markers in MM.

Assessment of the genetic and clinical determinants of hip fracture risk: Genome-wide association and Mendelian randomization study.

Hip fracture is the clinically most important fracture, but the genetic architecture of hip fracture is unclear. Here, we perform a large-scale hip fracture genome-wide association study meta-analysis and Mendelian randomization study using five cohorts from European biobanks. The results show that five genetic signals associate with hip fractures. Among these, one signal associates with falls, but not with bone mineral density (BMD), while four signals are in loci known to be involved in bone biology. Mendelian randomization analyses demonstrate a strong causal effect of decreased femoral neck BMD and moderate causal effects of Alzheimer's disease and having ever smoked regularly on risk of hip fractures. The substantial causal effect of decreased femoral neck BMD on hip fractures in both young and old subjects and in both men and women supports the use of change in femoral neck BMD as a surrogate outcome for hip fractures in clinical trials.

Clonal evolution after treatment pressure in multiple myeloma: heterogenous genomic aberrations and transcriptomic convergence.

We investigated genomic and transcriptomic changes in paired tumor samples of 29 in-house multiple myeloma (MM) patients and 28 patients from the MMRF CoMMpass study before and after treatment. A change in clonal composition was found in 46/57 (82%) of patients, and single-nucleotide variants (SNVs) increased from median 67 to 86. The highest increase in prevalence of genetic aberrations was found in RAS genes (60% to 72%), amp1q21 (18% to 35%), and TP53 (9% to 18%). The SBS-MM1 mutation signature was detected both in patients receiving high and low dose melphalan. A total of 2589 genes were differentially expressed between early and late samples (FDR < 0.05). Gene set enrichment analysis (GSEA) showed increased expression of E2F, MYC, and glycolysis pathways and a decreased expression in TNF-NFkB and TGFbeta pathways in late compared to early stage. Single sample GSEA (ssGSEA) scores of differentially expressed pathways revealed that these changes were most evident in end-stage disease. Increased expression of several potentially targetable genes was found at late disease stages, including cancer-testis antigens, XPO1 and ABC transporters. Our study demonstrates a transcriptomic convergence of pathways supporting increased proliferation and metabolism during disease progression in MM.

The HUNT study: A population-based cohort for genetic research.

The Trøndelag Health Study (HUNT) is a population-based cohort of ∼229,000 individuals recruited in four waves beginning in 1984 in Trøndelag County, Norway. Approximately 88,000 of these individuals have available genetic data from array genotyping. HUNT participants were recruited during four community-based recruitment waves and provided information on health-related behaviors, self-reported diagnoses, family history of disease, and underwent physical examinations. Linkage via the Norwegian personal identification number integrates digitized health care information from doctor visits and national health registries including death, cancer and prescription registries. Genome-wide association studies of HUNT participants have provided insights into the mechanism of cardiovascular, metabolic, osteoporotic, and liver-related diseases, among others. Unique features of this cohort that facilitate research include nearly 40 years of longitudinal follow-up in a motivated and well-educated population, family data, comprehensive phenotyping, and broad availability of DNA, RNA, urine, fecal, plasma, and serum samples.

RBR: library-less repeat detection for ESTs.

MOTIVATION: Repeat sequences in ESTs are a source of problems, in particular for clustering. ESTs are therefore commonly masked against a library of known repeats. High quality repeat libraries are available for the widely studied organisms, but for most other organisms the lack of such libraries is likely to compromise the quality of EST analysis. RESULTS: We present a fast, flexible and library-less method for masking repeats in EST sequences, based on match statistics within the EST collection. The method is not linked to a particular clustering algorithm. Extensive testing on datasets using different clustering methods and a genomic mapping as reference shows that this method gives results that are better than or as good as those obtained using RepeatMasker with a repeat library. AVAILABILITY: The implementation of RBR is available under the terms of the GPL from http://www.ii.uib.no/~ketil/bioinformatics CONTACT: ketil.malde@bccs.uib.no SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Masking repeats while clustering ESTs.

A problem in EST clustering is the presence of repeat sequences. To avoid false matches, repeats have to be masked. This can be a time-consuming process, and it depends on available repeat libraries. We present a fast and effective method that aims to eliminate the problems repeats cause in the process of clustering. Unlike traditional methods, repeats are inferred directly from the EST data, we do not rely on any external library of known repeats. This makes the method especially suitable for analysing the ESTs from organisms without good repeat libraries. We demonstrate that the result is very similar to performing standard repeat masking before clustering.

SYSTERS, GeneNest, SpliceNest: exploring sequence space from genome to protein.

We have integrated the protein families from SYSTERS and the expressed sequence tag (EST) clusters from our database GeneNest with SpliceNest, a new database mapping EST contigs into genomic DNA. The SYSTERS protein sequence cluster set provides an automatically generated classification of all sequences of the SWISS-PROT, TrEMBL and PIR databases into disjoint protein family and superfamily clusters. GeneNest is a database and software package for producing and visualizing gene indices from ESTs and mRNAs. Currently, the database comprises gene indices of human, mouse, Arabidopsis thaliana and zebrafish. SpliceNest is a web-based graphical tool to explore gene structure, including alternative splicing, based on a mapping of the EST consensus sequences from GeneNest to the complete human genome. The integration of SYSTERS, GeneNest and SpliceNest into one framework now permits an overall exploration of the whole sequence space covering protein, mRNA and EST sequences, as well as genomic DNA. The databases are available for querying and browsing at http://cmb.molgen.mpg.de.

A graph based algorithm for generating EST consensus sequences.

MOTIVATION: EST sequences constitute an abundant, yet error prone resource for computational biology. Expressed sequences are important in gene discovery and identification, and they are also crucial for the discovery and classification of alternative splicing. An important challenge when processing EST sequences is the reconstruction of mRNA by assembling EST clusters into consensus sequences. RESULTS: In contrast to the more established assembly tools, we propose an algorithm that constructs a graph over sequence fragments of fixed size, and produces consensus sequences as traversals of this graph. We provide a tool implementing this algorithm, and perform an experiment where the consensus sequences produced by our implementation, as well as by currently available tools, are compared to mRNA. The results show that our proposed algorithm in a majority of the cases produces consensus of higher quality than the established sequence assemblers and at a competitive speed. AVAILABILITY: The source code for the implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bioinformatics/ CONTACT: ketil@ii.uib.no.

Fast sequence clustering using a suffix array algorithm.

MOTIVATION: Efficient clustering is important for handling the large amount of available EST sequences. Most contemporary methods are based on some kind of all-against-all comparison, resulting in a quadratic time complexity. A different approach is needed to keep up with the rapid growth of EST data. RESULTS: A new, fast EST clustering algorithm is presented. Sub-quadratic time complexity is achieved by using an algorithm based on suffix arrays. A prototype implementation has been developed and run on a benchmark data set. The produced clusterings are validated by comparing them to clusterings produced by other methods, and the results are quite promising. AVAILABILITY: The source code for the prototype implementation is available under a GPL license from http://www.ii.uib.no/~ketil/bio/.