Cas9-directed long-read sequencing to resolve optical genome mapping findings in leukemia diagnostics.

Leukemias are genetically heterogeneous and diagnostics therefore includes various standard-of-care (SOC) techniques, including karyotyping, SNP-array and FISH. Optical genome mapping (OGM) may replace these as it detects different types of structural aberrations simultaneously and additionally detects much smaller aberrations (500 bp vs 5-10 Mb with karyotyping). However, its resolution may still be too low to define clinical relevance of aberrations when they are located between two OGM labels or when labels are not distinct enough. Here, we test the potential of Cas9-directed long-read sequencing (LRS) as an additional technique to resolve such potentially relevant new findings. From an internal Bionano implementation study we selected ten OGM calls that could not be validated with SOC methods. Per variant we designed crRNAs for Cas9 enrichment, prepared libraries and sequenced them on a MinION/GridION device. We could confirm all aberrations and, importantly, the actual breakpoints of the OGM calls were located between 0.2 and 5.5 kb of the OGM-estimated breakpoints, confirming the high reliability of OGM. Furthermore, we show examples of redefinition of aberrations between labels that enable judgment of clinical relevance. Our results suggest that Cas9-directed LRS can be a relevant and flexible secondary technique in diagnostic workflows including OGM.

Copy Number Variant Analysis of Spinocerebellar Ataxia Genes in a Cohort of Dutch Patients With Cerebellar Ataxia.

Background and Objectives: The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of neurodegenerative disorders generally caused by single nucleotide variants (SNVs) or indels in coding regions or by repeat expansions in coding and noncoding regions of SCA genes. Copy number variants (CNVs) have now also been reported for 3 genes-ITPR1, FGF14, and SPTBN2-but not all SCA genes have been screened for CNVs as the underlying cause of the disease in patients. In this study, we aim to assess the prevalence of CNVs encompassing 36 known SCA genes. Methods: A cohort of patients with cerebellar ataxia who were referred to the University Medical Center Groningen for SCA genetic diagnostics was selected for this study. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed using the Infinium Global Screening Array. Following data processing, genotyping data were uploaded into NxClinical software to perform CNV analysis per patient and to visualize identified CNVs in 36 genes with allocated SCA symbols. The clinical relevance of detected CNVs was determined using evidence from studies based on PubMed literature searches for similar CNVs and phenotypic features. Results: Of the 338 patients with cerebellar ataxia, we identified putative clinically relevant CNV deletions in 3 patients: an identical deletion encompassing ITPR1 in 2 patients, who turned out to be related, and a deletion involving PPP2R2B in another patient. Although the CNV deletion in ITPR1 was clearly the underlying cause of SCA15 in the 2 related patients, the clinical significance of the deletion in PPP2R2B remained unknown. Discussion: We showed that CNVs detectable with the limited resolution of SNP array are a very rare cause of SCA. Nevertheless, we suggest adding CNV analysis alongside SNV analysis to SCA gene diagnostics using next-generation sequencing approaches, at least for ITPR1, to improve the genetic diagnostics for patients.

Prevalence of intronic repeat expansions in RFC1 in Dutch patients with CANVAS and adult-onset ataxia.

Recently, an intronic biallelic (AAGGG)n repeat expansion in RFC1 was shown to be a cause of CANVAS and adult-onset ataxia in multiple populations. As the prevalence of the RFC1 repeat expansion in Dutch cases was unknown, we retrospectively tested 9 putative CANVAS cases and two independent cohorts (A and B) of 395 and 222 adult-onset ataxia cases, respectively, using the previously published protocol and, for the first time optical genome mapping to determine the size of the expanded RFC1 repeat. We identified the biallelic (AAGGG)n repeat expansion in 5/9 (55%) putative CANVAS patients and in 10/617 (1.6%; cohorts A + B) adult-onset ataxia patients. In addition to the AAGGG repeat motif, we observed a putative GAAGG repeat motif in the repeat expansion with unknown significance in two adult-onset ataxia patients. All the expanded (AAGGG)n repeats identified were in the range of 800-1299 repeat units. The intronic biallelic RFC1 repeat expansion thus explains a number of the Dutch adult-onset ataxia cases that display the main clinical features of CANVAS, and particularly when ataxia is combined with neuropathy. The yield of screening for RFC1 expansions in unselected cohorts is relatively low. To increase the current diagnostic yield in ataxia patients, we suggest adding RFC1 screening to the genetic diagnostic workflow by using advanced techniques that attain long fragments.

Feasibility of Follow-Up Studies and Reclassification in Spinocerebellar Ataxia Gene Variants of Unknown Significance.

Spinocerebellar ataxia (SCA) is a heterogeneous group of neurodegenerative disorders with autosomal dominant inheritance. Genetic testing for SCA leads to diagnosis, prognosis and risk assessment for patients and their family members. While advances in sequencing and computing technologies have provided researchers with a rapid expansion in the genetic test content that can be used to unravel the genetic causes that underlie diseases, the large number of variants with unknown significance (VUSes) detected represent challenges. To minimize the proportion of VUSes, follow-up studies are needed to aid in their reclassification as either (likely) pathogenic or (likely) benign variants. In this study, we addressed the challenge of prioritizing VUSes for follow-up using (a combination of) variant segregation studies, 3D protein modeling, in vitro splicing assays and functional assays. Of the 39 VUSes prioritized for further analysis, 13 were eligible for follow up. We were able to reclassify 4 of these VUSes to LP, increasing the molecular diagnostic yield by 1.1%. Reclassification of VUSes remains difficult due to limited possibilities for performing variant segregation studies in the classification process and the limited availability of routine functional tests.

Strategies in Rapid Genetic Diagnostics of Critically Ill Children: Experiences From a Dutch University Hospital.

Background: Genetic disorders are a substantial cause of infant morbidity and mortality and are frequently suspected in neonatal intensive care units. Non-specific clinical presentation or limitations to physical examination can result in a plethora of genetic testing techniques, without clear strategies on test ordering. Here, we review our 2-years experiences of rapid genetic testing of NICU patients in order to provide such recommendations. Methods: We retrospectively included all patients admitted to the NICU who received clinical genetic consultation and genetic testing in our University hospital. We documented reasons for referral for genetic consultation, presenting phenotypes, differential diagnoses, genetic testing requested and their outcomes, as well as the consequences of each (rapid) genetic diagnostic approach. We calculated diagnostic yield and turnaround times (TATs). Results: Of 171 included infants that received genetic consultation 140 underwent genetic testing. As a result of testing as first tier, 13/14 patients received a genetic diagnosis from QF-PCR; 14/115 from SNP-array; 12/89 from NGS testing, of whom 4/46 were diagnosed with a small gene panel and 8/43 with a large OMIM-morbid based gene panel. Subsequent secondary or tertiary analysis and/or additional testing resulted in five more diagnoses. TATs ranged from 1 day (QF-PCR) to a median of 14 for NGS and SNP-array testing, with increasing TAT in particular when many consecutive tests were performed. Incidental findings were detected in 5/140 tested patients (3.6%). Conclusion: We recommend implementing a broad NGS gene panel in combination with CNV calling as the first tier of genetic testing for NICU patients given the often unspecific phenotypes of ill infants and the high yield of this large panel.

Exome sequencing in patient-parent trios suggests new candidate genes for early-onset primary sclerosing cholangitis.

BACKGROUND & AIMS: Primary sclerosing cholangitis (PSC) is a rare bile duct disease strongly associated with inflammatory bowel disease (IBD). Whole-exome sequencing (WES) has contributed to understanding the molecular basis of very early-onset IBD, but rare protein-altering genetic variants have not been identified for early-onset PSC. We performed WES in patients diagnosed with PSC ≤ 12 years to investigate the contribution of rare genetic variants to early-onset PSC. METHODS: In this multicentre study, WES was performed on 87 DNA samples from 29 patient-parent trios with early-onset PSC. We selected rare (minor allele frequency < 2%) coding and splice-site variants that matched recessive (homozygous and compound heterozygous variants) and dominant (de novo) inheritance in the index patients. Variant pathogenicity was predicted by an in-house developed algorithm (GAVIN), and PSC-relevant variants were selected using gene expression data and gene function. RESULTS: In 22 of 29 trios we identified at least 1 possibly pathogenic variant. We prioritized 36 genes, harbouring a total of 54 variants with predicted pathogenic effects. In 18 genes, we identified 36 compound heterozygous variants, whereas in the other 18 genes we identified 18 de novo variants. Twelve of 36 candidate risk genes are known to play a role in transmembrane transport, adaptive and innate immunity, and epithelial barrier function. CONCLUSIONS: The 36 candidate genes for early-onset PSC need further verification in other patient cohorts and evaluation of gene function before a causal role can be attributed to its variants.

Targeted RNA-Sequencing Enables Detection of Relevant Translocations and Single Nucleotide Variants and Provides a Method for Classification of Hematological Malignancies-RANKING.

BACKGROUND: Patients with hematological malignancies (HMs) carry a wide range of chromosomal and molecular abnormalities that impact their prognosis and treatment. Since no current technique can detect all relevant abnormalities, technique(s) are chosen depending on the reason for referral, and abnormalities can be missed. We tested targeted transcriptome sequencing as a single platform to detect all relevant abnormalities and compared it to current techniques. MATERIAL AND METHODS: We performed RNA-sequencing of 1385 genes (TruSight RNA Pan-Cancer, Illumina) in bone marrow from 136 patients with a primary diagnosis of HM. We then applied machine learning to expression profile data to perform leukemia classification, a method we named RANKING. Gene fusions for all the genes in the panel were detected, and overexpression of the genes EVI1, CCND1, and BCL2 was quantified. Single nucleotide variants/indels were analyzed in acute myeloid leukemia (AML), myelodysplastic syndrome and patients with acute lymphoblastic leukemia (ALL) using a virtual myeloid (54 genes) or lymphoid panel (72 genes). RESULTS: RANKING correctly predicted the leukemia classification of all AML and ALL samples and improved classification in 3 patients. Compared to current methods, only one variant was missed, c.2447A>T in KIT (RT-PCR at 10-4), and BCL2 overexpression was not seen due to a t(14; 18)(q32; q21) in 2% of the cells. Our RNA-sequencing method also identified 6 additional fusion genes and overexpression of CCND1 due to a t(11; 14)(q13; q32) in 2 samples. CONCLUSIONS: Our combination of targeted RNA-sequencing and data analysis workflow can improve the detection of relevant variants, and expression patterns can assist in establishing HM classification.

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations.

Exome sequencing is now mainstream in clinical practice. However, identification of pathogenic Mendelian variants remains time-consuming, in part, because the limited accuracy of current computational prediction methods requires manual classification by experts. Here we introduce CAPICE, a new machine-learning-based method for prioritizing pathogenic variants, including SNVs and short InDels. CAPICE outperforms the best general (CADD, GAVIN) and consequence-type-specific (REVEL, ClinPred) computational prediction methods, for both rare and ultra-rare variants. CAPICE is easily added to diagnostic pipelines as pre-computed score file or command-line software, or using online MOLGENIS web service with API. Download CAPICE for free and open-source (LGPLv3) at https://github.com/molgenis/capice .

Detection of Fusion Genes to Determine Minimal Residual Disease in Leukemia Using Next-Generation Sequencing.

BACKGROUND: Measuring minimal residual disease (MRD), the persistence of leukemic cells after treatment, is important for monitoring leukemia recurrence. The current methods for monitoring MRD are flow cytometry, to assess aberrant immune phenotypes, and digital droplet PCR (ddPCR), to target genetic aberrations such as single-nucleotide variants and gene fusions. We present the performance of an RNA-based next-generation sequencing (NGS) method for MRD gene fusion detection compared with ddPCR. This method may have advantages, including the capacity to analyze different genetic aberrations and patients in 1 experiment. In particular, detection at the RNA level may be highly sensitive if the genetic aberration is highly expressed. METHODS: We designed a probe-based NGS panel targeting the breakpoints of 11 fusion genes previously identified in clinical patients and 2 fusion genes present in cell lines. Blocking probes were added to prevent nonspecific enrichment. Each patient RNA sample was diluted in background RNA, depleted for rRNA and globin mRNA, converted to cDNA, and prepared for sequencing. Unique sequence reads, identified by unique molecular identifiers, were aligned directly to reference transcripts. The same patient and cell-line samples were also analyzed with ddPCR for direct comparison. RESULTS: Our NGS method reached a maximum sensitivity of 1 aberrant cell in 10 000 cells and was mostly within a factor of 10 compared with ddPCR. CONCLUSIONS: Our detection limit was below the threshold of 1:1000 recommended by European Leukemia Net. Further optimizations are easy to implement and are expected to boost the sensitivity of our method to diagnostically obtained ddPCR thresholds.

A homozygous variant in growth and differentiation factor 2 (GDF2) may cause lymphatic dysplasia with hydrothorax and nonimmune hydrops fetalis.

The etiology of nonimmune hydrops fetalis is extensive and includes genetic disorders. We describe a term-born female neonate with late onset extensive nonimmune hydrops, that is, polyhydramnios, edema, and congenital bilateral chylothorax. This newborn was successfully treated with repetitive thoracocentesis, total parenteral feeding, octreotide intravenously and finally surgical pleurodesis and corticosteroids. A genetic cause seemed plausible as the maternal history revealed a fatal nonimmune hydrops fetalis. A homozygous truncating variant in GDF2 (c.451C>T, p.(Arg151*)) was detected with exome sequencing. Genetic analysis of tissue obtained from the deceased fetal sibling revealed the same homozygous variant. The parents and two healthy siblings were heterozygous for the GDF2 variant. Skin and lung biopsies in the index patient, as well as the revised lung biopsy of the deceased fetal sibling, showed lymphatic dysplasia and lymphangiectasia. To the best of our knowledge, this is the first report of an association between a homozygous variant in GDF2 with lymphatic dysplasia, hydrothorax and nonimmune hydrops fetalis.

A cross-omics integrative study of metabolic signatures of chronic obstructive pulmonary disease.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a common lung disorder characterized by persistent and progressive airflow limitation as well as systemic changes. Metabolic changes in blood may help detect COPD in an earlier stage and predict prognosis. METHODS: We conducted a comprehensive study of circulating metabolites, measured by proton Nuclear Magnetic Resonance Spectroscopy, in relation with COPD and lung function. The discovery sample consisted of 5557 individuals from two large population-based studies in the Netherlands, the Rotterdam Study and the Erasmus Rucphen Family study. Significant findings were replicated in 12,205 individuals from the Lifelines-DEEP study, FINRISK and the Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) studies. For replicated metabolites further investigation of causality was performed, utilizing genetics in the Mendelian randomization approach. RESULTS: There were 602 cases of COPD and 4955 controls used in the discovery meta-analysis. Our logistic regression results showed that higher levels of plasma Glycoprotein acetyls (GlycA) are significantly associated with COPD (OR = 1.16, P = 5.6 × 10- 4 in the discovery and OR = 1.30, P = 1.8 × 10- 6 in the replication sample). A bi-directional two-sample Mendelian randomization analysis suggested that circulating blood GlycA is not causally related to COPD, but that COPD causally increases GlycA levels. Using the prospective data of the same sample of Rotterdam Study in Cox-regression, we show that the circulating GlycA level is a predictive biomarker of COPD incidence (HR = 1.99, 95%CI 1.52-2.60, comparing those in the highest and lowest quartile of GlycA) but is not significantly associated with mortality in COPD patients (HR = 1.07, 95%CI 0.94-1.20). CONCLUSIONS: Our study shows that circulating blood GlycA is a biomarker of early COPD pathology.

A prospective study on rapid exome sequencing as a diagnostic test for multiple congenital anomalies on fetal ultrasound.

OBJECTIVE: Conventional genetic tests (quantitative fluorescent-PCR [QF-PCR] and single nucleotide polymorphism-array) only diagnose ~40% of fetuses showing ultrasound abnormalities. Rapid exome sequencing (rES) may improve this diagnostic yield, but includes challenges such as uncertainties in fetal phenotyping, variant interpretation, incidental unsolicited findings, and rapid turnaround times. In this study, we implemented rES in prenatal care to increase diagnostic yield. METHODS: We prospectively studied 55 fetuses. Inclusion criteria were: (a) two or more independent major fetal anomalies, (b) hydrops fetalis or bilateral renal cysts alone, or (c) one major fetal anomaly and a first-degree relative with the same anomaly. In addition to conventional genetic tests, we performed trio rES analysis using a custom virtual gene panel of ~3850 Online Mendelian Inheritance in Man (OMIM) genes. RESULTS: We established a genetic rES-based diagnosis in 8 out of 23 fetuses (35%) without QF-PCR or array abnormalities. Diagnoses included MIRAGE (SAMD9), Zellweger (PEX1), Walker-Warburg (POMGNT1), Noonan (PTNP11), Kabuki (KMT2D), and CHARGE (CHD7) syndrome and two cases of Osteogenesis Imperfecta type 2 (COL1A1). In six cases, rES diagnosis aided perinatal management. The median turnaround time was 14 (range 8-20) days. CONCLUSION: Implementing rES as a routine test in the prenatal setting is challenging but technically feasible, with a promising diagnostic yield and significant clinical relevance.

A pipeline-friendly software tool for genome diagnostics to prioritize genes by matching patient symptoms to literature.

Despite an explosive growth of next-generation sequencing data, genome diagnostics only provides a molecular diagnosis to a minority of patients. Software tools that prioritize genes based on patient symptoms using known gene-disease associations may complement variant filtering and interpretation to increase chances of success. However, many of these tools cannot be used in practice because they are embedded within variant prioritization algorithms, or exist as remote services that cannot be relied upon or are unacceptable because of legal/ethical barriers. In addition, many tools are not designed for command-line usage, closed-source, abandoned, or unavailable. We present Variant Interpretation using Biomedical literature Evidence (VIBE), a tool to prioritize disease genes based on Human Phenotype Ontology codes. VIBE is a locally installed executable that ensures operational availability and is built upon DisGeNET-RDF, a comprehensive knowledge platform containing gene-disease associations mostly from literature and variant-disease associations mostly from curated source databases. VIBE's command-line interface and output are designed for easy incorporation into bioinformatic pipelines that annotate and prioritize variants for further clinical interpretation. We evaluate VIBE in a benchmark based on 305 patient cases alongside seven other tools. Our results demonstrate that VIBE offers consistent performance with few cases missed, but we also find high complementarity among all tested tools. VIBE is a powerful, free, open source and locally installable solution for prioritizing genes based on patient symptoms. Project source code, documentation, benchmark and executables are available at https://github.com/molgenis/vibe.

A next-generation sequencing method for gene doping detection that distinguishes low levels of plasmid DNA against a background of genomic DNA.

Gene doping confers health risks for athletes and is a threat to fair competition in sports. Therefore the anti-doping community has given attention on its detection. Previously published polymerase chain reaction-based methodologies for gene doping detection are targeting exon-exon junctions in the intron-less transgene. However, because these junctions are known, it would be relatively easy to evade detection by tampering with the copyDNA sequences. We have developed a targeted next-generation sequencing based assay for the detection of all exon-exon junctions of the potential doping genes, EPO, IGF1, IGF2, GH1, and GH2, which is resistant to tampering. Using this assay, all exon-exon junctions of copyDNA of doping genes could be detected with a sensitivity of 1296 copyDNA copies in 1000 ng of genomic DNA. In addition, promotor regions and plasmid-derived sequences are readily detectable in our sequence data. While we show the reliability of our method for a selection of genes, expanding the panel to detect other genes would be straightforward. As we were able to detect plasmid-derived sequences, we expect that genes with manipulated junctions, promotor regions, and plasmid or virus-derived sequences will also be readily detected.

Occupational exposure to gases/fumes and mineral dust affect DNA methylation levels of genes regulating expression.

Many workers are daily exposed to occupational agents like gases/fumes, mineral dust or biological dust, which could induce adverse health effects. Epigenetic mechanisms, such as DNA methylation, have been suggested to play a role. We therefore aimed to identify differentially methylated regions (DMRs) upon occupational exposures in never-smokers and investigated if these DMRs associated with gene expression levels. To determine the effects of occupational exposures independent of smoking, 903 never-smokers of the LifeLines cohort study were included. We performed three genome-wide methylation analyses (Illumina 450 K), one per occupational exposure being gases/fumes, mineral dust and biological dust, using robust linear regression adjusted for appropriate confounders. DMRs were identified using comb-p in Python. Results were validated in the Rotterdam Study (233 never-smokers) and methylation-expression associations were assessed using Biobank-based Integrative Omics Study data (n = 2802). Of the total 21 significant DMRs, 14 DMRs were associated with gases/fumes and 7 with mineral dust. Three of these DMRs were associated with both exposures (RPLP1 and LINC02169 (2×)) and 11 DMRs were located within transcript start sites of gene expression regulating genes. We replicated two DMRs with gases/fumes (VTRNA2-1 and GNAS) and one with mineral dust (CCDC144NL). In addition, nine gases/fumes DMRs and six mineral dust DMRs significantly associated with gene expression levels. Our data suggest that occupational exposures may induce differential methylation of gene expression regulating genes and thereby may induce adverse health effects. Given the millions of workers that are exposed daily to occupational exposures, further studies on this epigenetic mechanism and health outcomes are warranted.

Improving the diagnostic yield of exome- sequencing by predicting gene-phenotype associations using large-scale gene expression analysis.

The diagnostic yield of exome and genome sequencing remains low (8-70%), due to incomplete knowledge on the genes that cause disease. To improve this, we use RNA-seq data from 31,499 samples to predict which genes cause specific disease phenotypes, and develop GeneNetwork Assisted Diagnostic Optimization (GADO). We show that this unbiased method, which does not rely upon specific knowledge on individual genes, is effective in both identifying previously unknown disease gene associations, and flagging genes that have previously been incorrectly implicated in disease. GADO can be run on www.genenetwork.nl by supplying HPO-terms and a list of genes that contain candidate variants. Finally, applying GADO to a cohort of 61 patients for whom exome-sequencing analysis had not resulted in a genetic diagnosis, yields likely causative genes for ten cases.

Limited overlap in significant hits between genome-wide association studies on two airflow obstruction definitions in the same population.

BACKGROUND: Airflow obstruction is a hallmark of chronic obstructive pulmonary disease (COPD), and is defined as either the ratio between forced expiratory volume in one second and forced vital capacity (FEV1/FVC) < 70% or < lower limit of normal (LLN). This study aimed to assess the overlap between genome-wide association studies (GWAS) on airflow obstruction using these two definitions in the same population stratified by smoking. METHODS: GWASes were performed in the LifeLines Cohort Study for both airflow obstruction definitions in never-smokers (NS = 5071) and ever-smokers (ES = 4855). The FEV1/FVC < 70% models were adjusted for sex, age, and height; FEV1/FVC < LLN models were not adjusted. Ever-smokers models were additionally adjusted for pack-years and current-smoking. The overlap in significantly associated SNPs between the two definitions and never/ever-smokers was assessed using several p-value thresholds. To quantify the agreement, the Pearson correlation coefficient was calculated between the p-values and ORs. Replication was performed in the Vlagtwedde-Vlaardingen study (NS = 432, ES = 823). The overlapping SNPs with p < 10- 4 were validated in the Vlagtwedde-Vlaardingen and Rotterdam Study cohorts (NS = 1966, ES = 3134) and analysed for expression quantitative trait loci (eQTL) in lung tissue (n = 1087). RESULTS: In the LifeLines cohort, 96% and 93% of the never- and ever-smokers were classified concordantly based on the two definitions. 26 and 29% of the investigated SNPs were overlapping at p < 0.05 in never- and ever-smokers, respectively. At p < 10- 4 the overlap was 4% and 6% respectively, which could be change findings as shown by simulation studies. The effect estimates of the SNPs of the two definitions correlated strongly, but the p-values showed more variation and correlated only moderately. Similar observations were made in the Vlagtwedde-Vlaardingen study. Two overlapping SNPs in never-smokers (NFYC and FABP7) had the same direction of effect in the validation cohorts and the NFYC SNP was an eQTL for NFYC-AS1. NFYC is a transcription factor that binds to several known COPD genes, and FABP7 may be involved in abnormal pulmonary development. CONCLUSIONS: The definition of airflow obstruction and the population under study may be important determinants of which SNPs are associated with airflow obstruction. The genes FABP7 and NFYC(-AS1) could play a role in airflow obstruction in never-smokers specifically.

From blood to lung tissue: effect of cigarette smoke on DNA methylation and lung function.

BACKGROUND: Genetic and environmental factors play a role in the development of COPD. The epigenome, and more specifically DNA methylation, is recognized as important link between these factors. We postulate that DNA methylation is one of the routes by which cigarette smoke influences the development of COPD. In this study, we aim to identify CpG-sites that are associated with cigarette smoke exposure and lung function levels in whole blood and validate these CpG-sites in lung tissue. METHODS: The association between pack years and DNA methylation was studied genome-wide in 658 current smokers with >5 pack years using robust linear regression analysis. Using mediation analysis, we subsequently selected the CpG-sites that were also associated with lung function levels. Significant CpG-sites were validated in lung tissue with pyrosequencing and expression quantitative trait methylation (eQTM) analysis was performed to investigate the association between DNA methylation and gene expression. RESULTS: 15 CpG-sites were significantly associated with pack years and 10 of these were additionally associated with lung function levels. We validated 5 CpG-sites in lung tissue and found several associations between DNA methylation and gene expression. CONCLUSION: This study is the first to validate a panel of CpG-sites that are associated with cigarette smoking and lung function levels in whole blood in the tissue of interest: lung tissue.

A Genome-Wide Linkage Study for Chronic Obstructive Pulmonary Disease in a Dutch Genetic Isolate Identifies Novel Rare Candidate Variants.

Chronic obstructive pulmonary disease (COPD) is a complex and heritable disease, associated with multiple genetic variants. Specific familial types of COPD may be explained by rare variants, which have not been widely studied. We aimed to discover rare genetic variants underlying COPD through a genome-wide linkage scan. Affected-only analysis was performed using the 6K Illumina Linkage IV Panel in 142 cases clustered in 27 families from a genetic isolate, the Erasmus Rucphen Family (ERF) study. Potential causal variants were identified by searching for shared rare variants in the exome-sequence data of the affected members of the families contributing most to the linkage peak. The identified rare variants were then tested for association with COPD in a large meta-analysis of several cohorts. Significant evidence for linkage was observed on chromosomes 15q14-15q25 [logarithm of the odds (LOD) score = 5.52], 11p15.4-11q14.1 (LOD = 3.71) and 5q14.3-5q33.2 (LOD = 3.49). In the chromosome 15 peak, that harbors the known COPD locus for nicotinic receptors, and in the chromosome 5 peak we could not identify shared variants. In the chromosome 11 locus, we identified four rare (minor allele frequency (MAF) <0.02), predicted pathogenic, missense variants. These were shared among the affected family members. The identified variants localize to genes including neuroblast differentiation-associated protein (AHNAK), previously associated with blood biomarkers in COPD, phospholipase C Beta 3 (PLCB3), shown to increase airway hyper-responsiveness, solute carrier family 22-A11 (SLC22A11), involved in amino acid metabolism and ion transport, and metallothionein-like protein 5 (MTL5), involved in nicotinate and nicotinamide metabolism. Association of SLC22A11 and MTL5 variants were confirmed in the meta-analysis of 9,888 cases and 27,060 controls. In conclusion, we have identified novel rare variants in plausible genes related to COPD. Further studies utilizing large sample whole-genome sequencing should further confirm the associations at chromosome 11 and investigate the chromosome 15 and 5 linked regions.