Coping, quality of life, and hope in adults with primary antibody deficiencies

BACKGROUND: Living with a chronic disease, such as primary antibody deficiency, will often have consequences for quality of life. Previous quality-of-life studies in primary antibody deficiency patients have been limited to different treatment methods. We wanted to study how adults with primary antibody deficiencies manage their conditions and to identify factors that are conducive to coping, good quality of life and hope. METHODS: Questionnaires were sent to all patients ≥20 years of age with primary antibody deficiencies who were served by Rikshospitalet University Hospital. The questionnaires consisted of several standardized scales: Ferrans and Powers Quality of Life Index (QLI), Short Form-36 (SF-36), Jalowiec Coping Scale (JCS), Nowotny Hope Scale (NHS), and one scale we devised with questions about resources and pressures in the past. Of a total of 91, 55 patients (aged 23–76 years) answered the questionnaires. The questionnaire study were supplemented with selected interviews of ten extreme cases, five with low and five with high quality of life scores. RESULTS: Among the 55 patients, low quality of life scores were related to unemployment, infections in more than four organs, more than two additional diseases, or more than two specific occurrences of stress in the last 2–3 months. Persons with selective IgA deficiency had significantly higher QLI scores than those with other antibody deficiencies. An optimistic coping style was most frequent used, and hope values were moderately high. Based on the interviews, the patients could be divided into three groups: 1) low QLI scores, low hope values, and reduced coping, 2) low QLI scores, moderate hope values, and good coping, and 3) high QLI scores, moderate to strong hope values, and good coping. Coping was related to the patients' sense of closeness and competence. CONCLUSION: Low quality of life scores in adults with primary antibody deficiencies were linked to unemployment and disease-related strains. Closeness and competence were preconditions for coping, quality of life and hope. The results are valuable in planning care for this patient group

Identification of copy number variants from exome sequence data

Background With advances in next generation sequencing technologies and genomic capture techniques, exome sequencing has become a cost-effective approach for mutation detection in genetic diseases. However, computational prediction of copy number variants (CNVs) from exome sequence data is a challenging task. Whilst numerous programs are available, they have different sensitivities, and have low sensitivity to detect smaller CNVs (1–4 exons). Additionally, exonic CNV discovery using standard aCGH has limitations due to the low probe density over exonic regions. The goal of our study was to develop a protocol to detect exonic CNVs (including shorter CNVs that cover 1–4 exons), combining computational prediction algorithms and a high-resolution custom CGH array. Results We used six published CNV prediction programs (ExomeCNV, CONTRA, ExomeCopy, ExomeDepth, CoNIFER, XHMM) and an in-house modification to ExomeCopy and ExomeDepth (ExCopyDepth) for computational CNV prediction on 30 exomes from the 1000 genomes project and 9 exomes from primary immunodeficiency patients. CNV predictions were tested using a custom CGH array designed to capture all exons (exaCGH). After this validation, we next evaluated the computational prediction of shorter CNVs. ExomeCopy and the in-house modified algorithm, ExCopyDepth, showed the highest capability in detecting shorter CNVs. Finally, the performance of each computational program was assessed by calculating the sensitivity and false positive rate. Conclusions In this paper, we assessed the ability of 6 computational programs to predict CNVs, focussing on short (1–4 exon) CNVs. We also tested these predictions using a custom array targeting exons. Based on these results, we propose a protocol to identify and confirm shorter exonic CNVs combining computational prediction algorithms and custom aCGH experiments

Lessons learned from additional research analyses of unsolved clinical exome cases

BACKGROUND: Given the rarity of most single-gene Mendelian disorders, concerted efforts of data exchange between clinical and scientific communities are critical to optimize molecular diagnosis and novel disease gene discovery. METHODS: We designed and implemented protocols for the study of cases for which a plausible molecular diagnosis was not achieved in a clinical genomics diagnostic laboratory (i.e. unsolved clinical exomes). Such cases were recruited to a research laboratory for further analyses, in order to potentially: (1) accelerate novel disease gene discovery; (2) increase the molecular diagnostic yield of whole exome sequencing (WES); and (3) gain insight into the genetic mechanisms of disease. Pilot project data included 74 families, consisting mostly of parent-offspring trios. Analyses performed on a research basis employed both WES from additional family members and complementary bioinformatics approaches and protocols. RESULTS: Analysis of all possible modes of Mendelian inheritance, focusing on both single nucleotide variants (SNV) and copy number variant (CNV) alleles, yielded a likely contributory variant in 36% (27/74) of cases. If one includes candidate genes with variants identified within a single family, a potential contributory variant was identified in a total of ~51% (38/74) of cases enrolled in this pilot study. The molecular diagnosis was achieved in 30/63 trios (47.6%). Besides this, the analysis workflow yielded evidence for pathogenic variants in disease-associated genes in 4/6 singleton cases (66.6%), 1/1 multiplex family involving three affected siblings, and 3/4 (75%) quartet families. Both the analytical pipeline and the collaborative efforts between the diagnostic and research laboratories provided insights that allowed recent disease gene discoveries (PURA, TANGO2, EMC1, GNB5, ATAD3A, and MIPEP) and increased the number of novel genes, defined in this study as genes identified in more than one family (DHX30 and EBF3). CONCLUSION: An efficient genomics pipeline in which clinical sequencing in a diagnostic laboratory is followed by the detailed reanalysis of unsolved cases in a research environment, supplemented with WES data from additional family members, and subject to adjuvant bioinformatics analyses including relaxed variant filtering parameters in informatics pipelines, can enhance the molecular diagnostic yield and provide mechanistic insights into Mendelian disorders. Implementing these approaches requires collaborative clinical molecular diagnostic and research efforts

The Extended Clinical Phenotype of 26 Patients with Chronic Mucocutaneous Candidiasis due to Gain-of-Function Mutations in STAT1

PURPOSE: Gain-of-function (GOF) mutations in the signal transducer and activator of transcription 1 (STAT1) result in unbalanced STAT signaling and cause immune dysregulation and immunodeficiency. The latter is often characterized by the susceptibility to recurrent Candida infections, resulting in the clinical picture of chronic mucocutaneous candidiasis (CMC). This study aims to assess the frequency of GOF STAT1 mutations in a large international cohort of CMC patients. METHODS: STAT1 was sequenced in genomic DNA from 57 CMC patients and 35 healthy family members. The functional relevance of nine different STAT1 variants was shown by flow cytometric analysis of STAT1 phosphorylation in patients' peripheral blood cells (PBMC) after stimulation with interferon (IFN)-α, IFN-γ or interleukin-27 respectively. Extended clinical data sets were collected and summarized for 26 patients. RESULTS: Heterozygous mutations within STAT1 were identified in 35 of 57 CMC patients (61 %). Out of 39 familial cases from 11 families, 26 patients (67 %) from 9 families and out of 18 sporadic cases, 9 patients (50 %) were shown to have heterozygous mutations within STAT1. Thirteen distinct STAT1 mutations are reported in this paper. Eight of these mutations are known to cause CMC (p.M202V, p.A267V, p.R274W, p.R274Q, p.T385M, p.K388E, p.N397D, and p.F404Y). However, five STAT1 variants (p.F172L, p.Y287D, p.P293S, p.T385K and p.S466R) have not been reported before in CMC patients. CONCLUSION: STAT1 mutations are frequently observed in patients suffering from CMC. Thus, sequence analysis of STAT1 in CMC patients is advised. Measurement of IFN- or IL-induced STAT1 phosphorylation in PBMC provides a fast and reliable diagnostic tool and should be carried out in addition to genetic testing

cnvScan: a CNV screening and annotation tool to improve the clinical utility of computational CNV prediction from exome sequencing data

Background With advances in next generation sequencing technology and analysis methods, single nucleotide variants (SNVs) and indels can be detected with high sensitivity and specificity in exome sequencing data. Recent studies have demonstrated the ability to detect disease-causing copy number variants (CNVs) in exome sequencing data. However, exonic CNV prediction programs have shown high false positive CNV counts, which is the major limiting factor for the applicability of these programs in clinical studies. Results We have developed a tool (cnvScan) to improve the clinical utility of computational CNV prediction in exome data. cnvScan can accept input from any CNV prediction program. cnvScan consists of two steps: CNV screening and CNV annotation. CNV screening evaluates CNV prediction using quality scores and refines this using an in-house CNV database, which greatly reduces the false positive rate. The annotation step provides functionally and clinically relevant information using multiple source datasets. We assessed the performance of cnvScan on CNV predictions from five different prediction programs using 64 exomes from Primary Immunodeficiency (PIDD) patients, and identified PIDD-causing CNVs in three individuals from two different families. Conclusions In summary, cnvScan reduces the time and effort required to detect disease-causing CNVs by reducing the false positive count and providing annotation. This improves the clinical utility of CNV detection in exome data

Adult presentation of ornithine transcarbamylase deficiency: a possible cause of hyperammonemia after high-dose chemotherapy and stem cell transplantation

ABSTRACTHyperammonemia is a rare and often fatal complication following the conditioning therapy in autologous and allogeneic stem cell transplant recipients. It is characterized by anorexia, vomiting, lethargy and coma without any other apparent cause. The diagnosis is often delayed because symptoms can be subtle and ammonia is usually not included among the routine analyzes. Previous reports have not identified the molecular mechanisms behind hyperammonemia in stem cell transplant recipients. Urea cycle disorders (UCDs) are inborn errors of metabolism leading to hyperammonemia that usually presents in early childhood, whereas first presentation in adults is less common. Here we describe an adult woman with hyperammonemia following autologous stem cell transplantation for multiple myeloma. No apparent cause of hyperammonemia was identified, including portosystemic shunting, liver dysfunction or recent hyperammonemia-inducing chemotherapy. Hyperammonemia, normal blood glucose as well as anion gap and a previous history of two male newborns that died early after birth, prompted biochemical and genetic investigations for a UCD. A heterozygous variant in the X-linked gene encoding ornithine transcarbamylase (OTC) was identified and was regarded as a cause of UCD. The patient improved after treatment with nitrogen scavengers and high caloric intake according to a UCD protocol. This case report suggests that UCD should be considered as a possible cause of hyperammonemia following stem cell transplantation