Ingrid Slade

Chiara Bacchelli

Helen Davies

Anne Murray

Fatemeh Abbaszadeh

Sandra Hanks

Rita Barfoot

Amos Burke

Julia Chisholm

Martin Hewitt

Helen Jenkinson

Derek King

Bruce Morland

Barry Pizer

Katrina Prescott

Anand Saggar

Lucy Side

Heidi Traunecker

Sucheta Vaidya

Paul Ward

P Andrew Futreal

Gordan Vujanic

Andrew G Nicholson

Neil Sebire

John R Priest

Kathryn Pritchard-Jones

Richard Houlston

Clare Turnbull

Charles Stiller

Michael R Stratton

Jenny Douglas

Professor Nazneen Rahman
email: nazneen.rahman@icr.ac.uk

DICER1 syndrome

Keywords: DICER1, microRNA, cancer syndrome, tumor predisposition

INTRODUCTION

DICER1 is an RNase endonuclease important in the production of microRNAs (miRNA) which are non-protein-coding small RNAs that are estimated to regulate the expression of over 30% of protein-coding genes at the post transcriptional level. [START_REF] Matsuda | Molecular cloning and characterization of a novel human gene (HERNA) which encodes a putative RNA-helicase[END_REF][START_REF] Carthew | Gene regulation by microRNAs[END_REF] miRNAs are transcribed as long precursors, known as pri-miRNAs, which are processed in the nucleus to produce pre-miRNAs. [START_REF] Gregory | The Microprocessor complex mediates the genesis of microRNAs[END_REF] The pre-miRNAs are exported to the cytoplasm where DICER1 processing generates a double-strand miRNA duplex. [START_REF] Bernstein | Role for a bidentate ribonuclease in the initiation step of RNA interference[END_REF] The duplex is unwound to generate the final miRNA which interacts with mRNA to regulate gene expression, typically through translational repression or mRNA degradation. [START_REF] Carthew | Gene regulation by microRNAs[END_REF][START_REF] Hammond | Argonaute2, a link between genetic and biochemical analyses of RNAi[END_REF][START_REF] Bartel | MicroRNAs: target recognition and regulatory functions[END_REF] Over 900 human miRNAs are currently recognised. [START_REF] Backes | A dictionary on microRNAs and their putative target pathways[END_REF][START_REF] Griffiths-Jones | miRBase: tools for microRNA genomics[END_REF] These have been implicated in a wide range of biological processes including metabolism, morphogenesis, cell fate determination, cell proliferation and apoptosis. [START_REF] Stadler | Small RNAs: keeping stem cells in line[END_REF][START_REF] Stefani | Small non-coding RNAs in animal development[END_REF] There is increasing evidence implicating dysregulation of miRNAs in several human diseases, including cancer. [START_REF] Zhang | microRNAs as oncogenes and tumor suppressors[END_REF]12] Widespread alteration of miRNA levels is seen in cancers and miRNA profiles characteristic for cancer type and stage are increasingly recognised. [12,13] Furthermore, global downregulation of miRNAs due to abrogation of miRNA processing has been shown to promote tumorigenesis. [14] Recently, germline inactivating DICER1 mutations were shown to cause familial pleuropulmonary blastoma (PPB, OMIM #601200), a rare malignant lung tumor, primarily affecting children before age 6.[15, 16] By linkage analysis Hill et al mapped a familial PPB gene to chromosome 14q. They considered DICER1 to be a promising candidate and identified pathogenic mutations in 11 families. [15] This important finding raises a number of questions. Firstly, what is the contribution of DICER1 mutations to non-familial, sporadic PPB? Mutations in some cancer predisposition genes contribute appreciably to both familial and sporadic forms of disease, whereas for others the contribution to non-familial cases is small. Secondly, do constitutional DICER1 mutations predispose to tumors other than PPB? The International PPB Registry has collected information from over 200 PPB families and a variety of different tumors have been reported in PPB cases and/or their relatives [17,18] However, it is unknown which tumor types are genuinely associated with PPB, which are related to DICER1 mutations, and which reflect ascertainment. Thirdly, do somatic DICER1 mutations contribute to cancer? This is of particular interest as it has been proposed that somatic 14q loss, which has been reported in many cancers, may be targeted at DICER1. [19,20,21] To address these questions we have conducted exhaustive DICER1 sequencing, in >1,600 patient samples, including constitutional DNAs from 823 individuals with a broad range of tumors, but particularly focussing on tumors that have been proposed to be associated with PPB (http://www.ppbregistry.org/pdf/Doc_D.pdf) (Table 1). We also sequenced DICER1 in DNA from 781 cancer cell lines to assess the impact of somatic DICER1 mutation on cancer development (Supplementary Table 1). (20, 5 of whom were deceased), cystic nephroma (15, none deceased) and Sertoli-Leydig cell tumors (7, none deceased) that had been registered since its inception in 1962. The clinicians were contacted to request that they recruit these patients to the FACT study. In addition, a small minority of patients referred to our Clinical Genetics service with these tumors were recruited directly. Tumor DNA from DICER1 mutation-positive paraffin-embedded tissues was extracted using QIAamp DNA FFPE Tissue kit (QIAGEN) according to manufacturer instructions. We analysed whole genome amplified DNA from 781 cancer cell lines as part of the Cancer Genome Project, Cell Line Project (Supplementary Table 1).

DICER1 Sequencing

For analysis of the constitutional DNA we designed PCR primers to amplify the 26 coding exons and intron-exon boundaries of DICER1 in a multiplex PCR reaction (Supplementary Table 2). Products were sequenced by capillary sequencing using the BigDye Terminator Cycle Sequencing Kit and an ABI3730 Genetic Analyzer (Applied Biosystems, Foster City CA). Sequences were analysed using Mutation Surveyor software v3.20 (SoftGenetics, USA). We only included samples in which at least 90% or more of the coding sequence was successfully screened in subsequent analyses. For the cancer cell lines, PCR primers that amplify 500bp PCR products encompassing the 26 coding DICER1 exons and intron-exon boundaries were designed and sequenced as described above. Sequence traces were analyzed using

AutoCSA software[22], followed by manual inspection of putative variants. All putative variants were confirmed by bidirectional sequencing of a second independently amplified PCR product. Matched normal cell lines were available for forty cell lines. The somatic status of variants identified in these forty cell lines was determined by sequencing DNA from the corresponding normal. In the remaining cell lines we assumed that cell line variants that were also identified in the constitutional DNA screen were not somatic. We evaluated the likely pathogenicity of sequence variants using Polyphen, SIFT and NNSplice software.

RESULTS

Germline DICER1 mutation analysis

We identified pathogenic mutations in 19/823 index individuals (Table 2 and Supplementary Figure 1). Seventeen mutations lead to premature protein truncation as a result of frameshift, nonsense or consensus splice-site mutations. Two mutations are missense alterations for which there is substantial evidence of pathogenicity. Firstly, they are the only two missense alterations in the 3214 chromosomes screened that are predicted to be pathogenic by SIFT and Polyphen.

Secondly, both target highly conserved residues in the RNase III domain. Thirdly, they are in the vicinity of a missense variant identified by Hill et al, which resulted in a similar DICER1 histochemical profile to truncating mutations. [15] We also identified several non-pathogenic variants including nine missense variants, 23 synonymous variants and five intronic variants (Supplementary Table 3).

Pleuropulmonary blastoma

We identified DICER1 mutations in 10 individuals with PPB and in the mother of a child that had died from PPB but from whom no sample was available. One child developed an intra-ocular medulloepithelioma four years after PPB. Threegenerational pedigrees were available for most cases and no relative had PPB. One sibling died from neuroblastoma; her DICER1 status is not known, but a mutation was present in her mother. There were three children with PPB in whom we did not identify a DICER1 mutation.

Cystic nephroma

The commonest reported association of PPB is cystic nephroma[17], a rare benign renal tumor that typically presents as a multicystic renal mass without solid nodules.

It has a bimodal incidence with 50% occurring in children less than 4 years and 30% in the 5 th and 6 th decades.

[23] We had DNA from three unilateral childhood cases and in two we identified truncating DICER1 mutations. One of the children had a halfsibling with cystic nephroma who also has the mutation. The second DICER1 mutation-positive case was recently found to have a small lung cyst which is being monitored, but has not had histological evaluation.

Ovarian Sertoli-Leydig tumors

We analysed DNA from 30 individuals with sex cord tumors of which six were ovarian Sertoli-Leydig tumors, which are sex cord-tumors that exhibit testicular differentiation.

[24] The age range of diagnosis is between 2-75 years but ~75% present in the second or third decades.

Seminoma

We analysed DNA from 185 individuals with germ cell tumor, of which 128 had a family history of testicular cancer. We identified one missense DICER1 mutation, Q1580H. A maternal first cousin once removed of this proband developed testicular cancer at 27 years but the proband's mother does not carry the DICER1 mutation. It is not possible to conclusively establish whether this mutation is pathogenic on the available evidence.

Intra-ocular medulloepithelioma

Intra-ocular medulloepithelioma, also known as dictyoma, is a very rare embryonal tumor usually originating in the ciliary body of the eye that most commonly occurs during childhood.[28] One child with PPB also developed a dictyoma, and has a DICER1 mutation.

Thyroid non-toxic goiters / cysts

In the PPB Registry thyroid cancers and thyroid hyperplasia are reported in both probands and relatives of PPB cases. We analysed DNA from 88 individuals with thyroid cancer but did not identify any mutations. However, one proband and six relatives of DICER1 mutation-positive individuals developed thyroid cysts / multinodular colloid goiter between the ages of 9-30 years. All were non-toxic, associated with normal thyroid function and non-malignant. Thyroidectomy was required in four individuals because of recurrent disease.

Other tumors/cysts

We did not identify mutations in any of the other tumor types as detailed in Table 1.

Family studies in DICER1 mutation-positive individuals

We had samples from both parents in 17 families in which a DICER1 mutation had been identified in an index individual. In each, the mutation had been inherited (Table 2). We had grandparental samples for five families. In two families, the mutation was absent in the respective grandparents indicating that the mutation had arisen de novo in the parent. In the other three families, the mutation was present in a grandparent.

We analysed DNA from 51 relatives and we identified 25 relatives with DICER1 mutations. Of these, as described above, one mother had a Sertoli-Leydig tumor, one half-sibling had cystic nephroma and six relatives had thyroid cysts / goiter. The remaining 17 individuals did not have clinical features or symptoms likely to be related to the DICER1 mutation; one relative having muscular dystrophy and another

Wegener's granulomatosis.

Analysis of tumors from DICER1 mutation-positive individuals

We obtained eight tumors from six DICER1 mutation-positive individuals. This included three PPB, four Sertoli-Leydig tumors and one cystic nephroma. We analysed each tumor for the relevant mutation. Each was heterozygous for the mutation, i.e. the tumor showed a similar mutational profile as in the blood and there was no loss of the wild-type allele in any tumor.

DICER1 mutation analysis in cancer cell lines

We screened 781 cancer cell lines (Supplementary Table 1) for DICER1 mutations.

These represent an extensive cross-section of cancers, but do not include many of the cancers in which we identified germline DICER1 mutations. 206 of the cell lines have previously been shown to have loss of heterozygosity of 14q encompassing DICER1.

We identified 4 truncating mutations in the 781 cell lines and these were in microsatellite unstable lines. We identified 22 non-synonymous variants that were either proven to be somatic or in which normal DNA was not available for evaluation.

None were predicted to be deleterious (Supplementary Table 4).

DISCUSSION

In 2009, germline DICER1 mutations were identified in familial pleuropulmonary blastoma, adding to the list of rare familial cancer syndromes that have yielded critical evidence linking essential biological processes with cancer causation. [15] In this study we have expanded knowledge of the link between DICER1 and cancer.

Firstly, we demonstrate that germline DICER1 mutations are the major cause of PPB.

In the UK, 20 cases of PPB have been registered in the National Registry of Childhood Tumors over the last 35 years. We were able to include 14 in the current study, none of whom had a family history of PPB. We identified DICER1 mutations in 11 of these cases.

[15] It is uncertain whether cryptic DICER1 mutations account for any of the negative cases, whether mutations in another gene can also cause PPB, or whether the remaining cases are not due to germline predisposition genes.

However, it is clear that germline DICER1 mutations are the major cause of both familial and non-familial PPB.

We have also demonstrated that DICER1 mutations cause a range of phenotypes; not all families include PPB and a high proportion of mutation carriers are clinically well. In view of this we suggest that 'DICER1 syndrome' is a preferable term to 'PPB familial tumor syndrome' which has previously sometimes been used. The range of different tumors that can occur in individuals with DICER1 mutations is broad and it is likely that more associated tumors will be identified as further mutation testing is undertaken. The contribution of DICER1 mutations to different tumors is very variable. The major tumors that occur in DICER1 syndrome appear to be PPB, cystic nephroma and ovarian Sertoli-Leydig tumor. Evidence for this comes from our mutational data, our clinical and mutational investigation of relatives of mutationpositive probands and from the spectrum of tumors that have been documented in relatives of PPB cases in the PPB Registry. [17,18] The contribution of DICER1 mutations to different tumors is also very variable. Whilst germline DICER1 mutations may contribute significantly to cystic nephroma, ovarian Sertoli-Leydig tumor and intra-ocular medulloepithelioma they are unlikely to have a major impact on the incidence of Wilms tumor, medulloblastoma/infratentorial PNET or neuroblastoma.

In addition to tumors, DICER1 mutations also appear to confer a risk of thyroid cysts.

One proband and six DICER1 mutation-positive relatives developed thyroid cysts in childhood or young adulthood. While histology was only available for two cases, both were non-toxic multinodular colloid goiters. This is of particular interest as the gene for familial non-toxic multinodular thyroid goiter has been previously shown to localise to 14q. [29] The mutation analyses in cancer cell lines suggest that somatic DICER1 mutations do not make a substantial contribution to cancer. This is in contrast to recent reports hypothesising that the 14q hemizygosity observed in 206/761 cell lines is targeted at DICER1. [19,20,21] In the great majority of the cell lines the 14q loss of heterozygosity extends over a very large area and includes many genes. If loss of DICER1 were the main driver, one would anticipate that somatic DICER1 mutations would occur in at least some of the cell lines with normal 14q chromosomes.

However, we only identified four truncating mutations and these were in microsatellite unstable lines and therefore are unlikely to be driver mutations. Thus the somatic mutational profile of DICER1 appears to differ from that of other ubiquitously expressed, critically important genes such as TP53 and RB1 that also predispose to rare childhood cancers when mutated in the germline.

The mechanism of DICER1 tumor predisposition also appears to differ from the majority of known cancer predisposition genes and is likely to operate by a haploinsufficiency mechanism (Figure 1). Our analysis of tumors showed no loss of the wild-type allele and Hill et al showed retained DICER1 expression in tumor cells.

[15] Data from mice studies are also consistent with a haploinsufficiency model and indicate that whilst monoallelic DICER1 inactivation promotes tumorigenesis, biallelic loss is inhibitory. [20,21] Our data further suggests that although inactivation of one DICER1 allele is the initiating event in DICER1 syndrome, presumably because it leads to dysregulation of miRNAs levels, other events must be required for cancer to occur. It is not known what these additional events are, or how many are required for oncogenesis to proceed. However, the low frequency of tumors in DICER1 mutation carriers suggests that either more than one additional event is required, and/or the likelihood of the event(s) occurring is small.

Our data demonstrate that the risk of tumors in DICER1 mutation carriers is low and most mutation-carriers do not develop tumors. This modest penetrance and the variable phenotype of DICER1 syndrome raise significant clinical challenges. We suggest that diagnostic DICER1 testing should be considered in individuals with possible PPB, cystic nephroma, ovarian Sertoli-Leydig tumor or medulloepithelioma.

The prevalence of mutations in these conditions may be considerable and identification of a DICER1 mutation can aid diagnosis and management, particularly for PPB which can show significant clinical overlap with other types of lung cyst. [18,[START_REF] Griffin | CT and histopathological correlation of congenital cystic pulmonary lesions: a common pathogenesis?[END_REF] The issue of surveillance in a pleiotropic condition of modest penetrance is also complex. To date, ad-hoc, variable screening for PPB has been undertaken in individual families, often utilising lung CT, which can require an anaesthetic, involves radiation exposure and is of unproven efficacy. [START_REF] Evans | Malignant transformation and new primary tumours after therapeutic radiation for benign disease: substantial risks in certain tumour prone syndromes[END_REF] Moreover, the natural history and appropriate management of such screen-detected lesions in a well child is unknown.

In view of these considerations, and the modest penetrance, we are currently operating an 'open-door' management policy with early investigation of potential tumor-related symptoms, but we are not undertaking routine surveillance in healthy mutation-positive individuals. This policy will be under continuous review, particularly over the next few years, when extensive expert discussions about the optimal management of DICER1 mutation-carriers are likely to occur.

In this study we clarify the phenotypes associated with constitutional DICER1 mutations and propose that the condition should be called 'DICER1 syndrome'. In the future, additional research will hopefully further clarify the clinical features, tumor risks and optimal management of this condition and will illuminate the mechanisms by which DICER1 haploinsufficiency predisposes to human disease. germline/constitutional mutation predisposes to tumors. One or more additional events are required for oncogenesis to proceed but does not appear to include inactivation of the wild-type DICER1 allele.

  [24] We identified truncating DICER1 mutations in four individuals; three had young-onset bilateral ovarian Sertoli-Leydig tumors, and one had a unilateral ovarian sex cord tumor that could not be further classified because of necrosis. One of the bilateral cases previously had Wilms tumor (see below). The mother of one case had also developed a Sertoli-Leydig tumor at 21 years and carried the DICER1 mutation. She has subsequently had melanoma at 50 years, endometrial cancer at 62 years and breast cancer at 68 years.Wilms tumorWilms tumor is an embryonal cancer of the kidney that affects ~1 in 10,000 children, usually before the age of 6 years.[25, 26] We analysed DNA from 243 individuals with Wilms tumor. We identified one truncating DICER1 mutation, in a child who developed Wilms tumor of atypical histology at the unusually late age of 8 years.Four years after treatment the child developed bilateral ovarian Sertoli-Leydig cell tumors.Medulloblastoma/Infratentorial PNETMedulloblastoma is a primitive neuro-ectodermal tumor that arises in the posterior fossa.[27] We analysed 84 childhood medulloblastoma/infratentorial PNET cases and identified one truncating mutation in a child of 13 years. No other information or samples were available.

FIGURE LEGEND Figure 1 .

 LEGEND1 FIGURE LEGEND

Table 1 .

 1 Tumors in individuals screened for constitutional DICER1 mutations

	Tumor Type	Number of	Number with
		cases	DICER1 mutation
	Lung tumors
	Pleuropulmonary blastoma	14	11
	Congenital lung cyst	1
	Sex-cord stromal tumors
	Testicular Sertoli-Leydig/Sertoli/Leydig tumor	11
	Ovarian Sertoli-Leydig tumor	6	3
	Ovarian granulosa cell tumor	6
	Gonadal stromal cell tumor unclassified	5
	Mixed stromal cell tumor	1
	Stromal sex-cord tumor unclassified	1	1
	Renal tumors Wilms tumor	243	1 a
	Cystic nephroma	3	2
	Clear cell sarcoma	3
	CNS tumors
	Medulloblastoma/Infratentorial PNET	84	1
	Eye tumors Medulloepithelioma (dictyoma)	1	1 b
	Germ cell tumors
	Seminoma	71	1
	Non-seminoma (testis)	52
	Mixed testicular cancer	14
	Embryonal carcinoma	13
	Testicular cancer unspecified	12
	Teratoma	10
	Dysgerminoma/Germinoma	8
	Yolk-sac tumor	4
	Gonadoblastoma	1
	Neuroblastoma	73
	Thyroid carcinoma
	Papillary thyroid carcinoma	51
	Follicular thyroid carcinoma	18
	Thyroid cancer unspecified	15
	Anaplastic thyroid carcinoma	4
	Soft tissue and other extraosseous sarcomas
	Rhabdomyosarcoma	19
	Fibrosarcoma	7
	Other soft tissue sarcomas	49
	Malignant bone tumors
	Ewings sarcoma	8
	Osteosarcoma	7
	Chondrosarcoma	4
	Hepatic tumors
	Hepatoblastoma	2
	Hepatocellular carcinoma	2

a this patient also had ovarian Sertoli-Leydig cell tumor b this patient also had pleuropulmonary blastoma

Table 2 .

 2 Probands and relatives with constitutional DICER1 mutations

	ID	Phenotype	Age at	Current age
			diagnosis (yrs)	(yrs)
	Family 1 -c.4403_4406delCTCT
	proband	pleuropulmonary blastoma	1.5
	parent	none
	uncle	none
	grandparent	none
	Family 2 -c.1716delT
	proband	pleuropulmonary blastoma	0.8
	parent	none
	Family 3 -c.1196_1197dupAG
	proband	pleuropulmonary blastoma	4
	parent	none
	aunt	none
	grandparent	none
	Family 4 -c.3505delT
	proband	pleuropulmonary blastoma	3
	sibling	none
	parent	none
	Family 5 -c.1966C>T p.R656X
	proband	pleuropulmonary blastoma	7
	parent	none
	Family 6 -c.2268_2271delTTTG
	proband	pleuropulmonary blastoma	0.9
	parent	none
	Family 7 -c.3665delT
	proband	pleuropulmonary blastoma a	4.2	died 5.2
	parent	none
	Family 8 -c.3583_3584delGA
	proband	pleuropulmonary blastoma	1.3
		intra-ocular medulloepithelioma	6
	parent	none
	Family 9 -c.2040+1 G>C
	proband	pleuropulmonary blastoma	3
	parent	thyroid cysts unclassified	25
	Family 10 -c.3726C>A p.Y1242X
	proband	pleuropulmonary blastoma	4
	parent	thyroid cysts unclassified	30
	b Family 11 -c.5465A>T p.D1822V
	proband	pleuropulmonary blastoma	1.8

ACKNOWLEDGEMENTS

We thank the children and families involved in the research and the physicians, nurses and pathologists who referred families and provided samples. We are grateful for assistance with recruitment and discussions with the International PPB Registry. We thank Katrina Tatton-Brown, Helen Hanson, Trevor Cole, Anita Bayne, Margaret Warren-Perry, Darshna Dudakia, Polly Gibbs, Jessie Bull and Anna Zachariou for assistance of recruitment. We thank Katrina Spanova, Bernadette Ebbs and Deborah Hughes for running the ABI sequencers. We thank Ann Strydom for assistance with the manuscript. The research was carried out as part of the Factors Associated with Childhood Tumors (FACT) study, which is a UK Children's Cancer and Leukaemia Group (CCLG) study. The Childhood Cancer Research Group receives funding from the Department of Health and the Scottish Ministers. The views expressed in this publication are those of the authors and not necessarily those of the Department of Health and the Scottish Ministers. I.S. is supported by the Michael and Betty Kadoorie Cancer Genetics Research Programme. We acknowledge NHS funding to the NIHR Biomedical Research Centre. This work was supported by Cancer Research UK (grants C8620_A9024 and C8620_A8857) and the Institute of Cancer Research (UK).

Research support: This work was supported by Cancer Research UK (grants C8620_A9024 and C8620_A8857) and the Institute of Cancer Research (UK).

WEB RESOURCES

The URLs for data presented herein are as follows:

ACCESSION NUMBERS

The cDNA Genbank accession number for the DICER1 Sequence reported in this paper is NM_030621.2.

Licence for Publication

The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in JMG editions and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://group.bmj.com/products/journals/instructions-for-authors/licence-forms/)."

Competing Interests

None to declare.


Keywords: pesticides, routine analysis, liquid chromatography, tandem mass spectrometry, 41 instrument software

Routine approach to qualitatively screen for 300 pesticides and quantify those frequently detected in fruits and vegetables using liquid chromatography tandem mass spectrometry Béla Kmellár, László Abrankó, Peter Fodor, Steven Lehotay

validated for hundreds of pesticide residues in many types of foods, and has become AOAC 79 Official Method 2007.01 [START_REF] Lehotay | Determination of Pesticide Residues in Foods by Acetonitrile Extraction 563 and Partitioning with Magnesium Sulfate: Collaborative Study[END_REF] and European Committee for Standardization 80 (CEN) Standard Method EN 15662. 81 Triple quadrupole MS/MS instruments are mainly applicable for sensitive and 82 selective quantitative measurements and identification of known, targeted analytes in selected 83 or multiple reaction monitoring (SRM or MRM) mode. Recently, many new software and 84 hardware capabilities have been introduced from MS/MS manufacturers to allow faster 85 analysis times, lower detection limits, more ion transitions per given time, fast 86 positive/negative switching, and beneficial data handling features. One of the companies, 87

Applied Biosystems, introduced an enhanced product ion (EPI) feature in MRM mode for 88 their linear ion trap products using information dependent acquisition (known as data 89 dependent scanning by other manufacturers) and MS/MS spectral libraries (Applied 90 Biosystems Application Note 114AP38-02, 2005). Such products should be independently 91 evaluated in real-world applications to assess their capabilities and limitations. 92

One of the major problems in LC-MS/MS pesticide analysis due to the typical use of 93 electrospray ionization (ESI) is caused by matrix effects. Quantitative results in LC-MS/MS 94 cannot be trusted unless matrix effects have been assessed and compensated for if they are 95 found to occur [START_REF] Granby | Analysis of pesticides in fruit, vegetables 543 and cereals using methanolic extraction and detection by liquid chromatography-tandem mass 544 spectrometry[END_REF][START_REF] Kruve | Matrix effects in pesticide multi-residue 554 analysis by liquid chromatography-mass spectrometry[END_REF][START_REF] Niessen | Matrix effects in quantitative pesticide analysis 570 using liquid chromatography-mass spectromatry[END_REF]. The best approach to 96 compensate for matrix effects entails the use of isotopically-labeled internal standards for 97 each analyte, but this is not feasible in multiresidue analysis of so many pesticides. Therefore, 98 the most common approach is to use matrix-matched calibration standards. However, it can 99 be difficult to find a blank matrix from which to prepare the calibration standards, and 100 compensation from one sample to another (even for the same matrix) may not be the same. A 101 method of standard additions in the sample extract may be an alternative approach. 102

The aim of this study was to assess in real-world practice the combination of two 103 methods. first, QuEChERS fruit and vegetables extracts were injected in LC-MS/MS using a 104 qualitative analysis of 300 targeted pesticides in the commercial MRM-triggered EPI 105 screening method; and secondly for presumptive positives, a second analysis was conducted 106 using a quantitative/confirmatory MRM method we optimized for 55 previously detected 107 and/or frequently used pesticides. The method combination and its limitations were critically 108 Reagents and materials 113 HPLC grade acetonitrile was purchased from Fisher Scientific (Loughborough, UK), 114 deionized water was obtained from a Milli-Q reagent water system (Billerica, MA; USA), 115 dimethyl formamide was obtained from Reanal (Budapest, Hungary), anhydrous magnesium 116 sulfate was obtained from Scharlau Chemie S.A. (Sentmenat, Spain), and PSA-bonded silica 117 (primary secondary amine) was obtained from Supelco (Bellefonte, PA; USA). Each sample 118 was filtered through a 0.45 µm PVDF filter (Roth, Carlsruhe, Germany) before injection. 119 Acetic acid and sodium acetate (both from Merck, Darmstadt, Germany) were used for the 120 sample preparation procedure. Analytical grade pesticide standards were ordered from 121 Sigma-Aldrich (Steinheim, Germany), Dr. Ehrenstorfer GmbH (Augsburg, Germany) and 122

Riedel-de Haen (Germany) and stored at -30°C. Individual standard stock solutions were 123 prepared by dissolving the crystalline standards in acetonitrile (or dimethyl formamide for 124 those insoluble in acetonitrile) to reach the final concentration of 1000-4000 µg mL -1 . For 125 method optimization, individual standard solutions were used, which were prepared by 126 diluting the stock solution to a concentration of 1-4 µg mL -1 . A standard mix solution in 127 acetonitrile for preparation of calibration standards was prepared from the individual stock 128 soutions to yield 10 µg mL -1 . All solutions were kept at -18°C before use. 129 130

Sample preparation 131

The acetate-buffered QuEChERS sample preparation method for pesticides (AOAC 132 Official Method 2007.01) was applied to all the samples [START_REF] Granby | Analysis of pesticides in fruit, vegetables 543 and cereals using methanolic extraction and detection by liquid chromatography-tandem mass 544 spectrometry[END_REF][START_REF] Kruve | Matrix effects in pesticide multi-residue 554 analysis by liquid chromatography-mass spectrometry[END_REF]133 Niessen, 2006). After homogenization with a house-hold mill (equipped with stainless steel 134 knives), a 15 g portion of the homogenized sample was weighed into a 50 mL PTFE tube and 135 100 µL of 50 µg mL -1 triphenyl phosphate (TPP) surrogate standard solution in acetonitrile 136 was added followed by 15 mL of acetonitrile containing 1% acetic acid (v/v not accounting 137 for purity). Then, 6 g MgSO 4 and 2.5 g sodium acetate trihydrate (equivalent to 1.5 g of 138 anhydrous form) were added, and the sample was shaken forcefully for 4 min. The sample 139 was then centrifuged (Hermle Z206A, Labcompare, San Fransisco, USA) at 4000 rpm (1860 140 rcf) for 5 min, and 5 mL of the supernatant was transferred to a 15 mL PTFE tube to which 141 750 mg MgSO 4 and 250 mg PSA were added. The extract was shaken using a vortex mixer 142 for 20 s and centrifuged at 4000 rpm again for 5 min. Approximately 3 mL of the supernatant 143 was filtered through a 0.45 µm PTFE filter (13 mm diameter), and 800 µL portions were 144 transferred to autosampler vials. The extracts were evaporated to dryness under a stream of 145 For the matrix-matched and standard addition calibrations, 4 x 80 µL of reconstituted 147 samples were transferred into autosampler glass inserts, and 20 µL portions of 0; 250; 500 and 148 1250 ng mL -1 standard mix solutions containing the 55 pesticides in 25/75 acetonitrile/water 149 (v/v) were added to reach the final additional concentrations of 0; 50; 100 and 250 ng g -1 150 equivalents, respectively. 151 152

LC-MS analysis 153

For the LC analysis, an Agilent (Little Falls, DE; USA) 1100 HPLC system was used. 154

It contained a binary pump, a degasser, column thermostat, and an autosampler. A reverse 155 phase C8 analytical column of 150 mm × 4.6 mm i.d. and 5 µm particle size and a guard 156 column of 12.5 mm × 4.6mm and 5 µm particle size (both were Agilent Zorbax Eclipse XDB) 157 were coupled to the LC system. Deionized water containing 0.1% formic acid (mobile phase 158 component A) and acetonitrile (component B) were employed for the gradient program, 159 which started with 20% B for 3 min and was linearly increased to 100% B in 27 min (held for 160 3 min). The column was then re-equilibrated over 12 min. back to 20% B. Thus, the total run 161 time took 45 min. The flow rate was constant at 0.6 mL min -1 , and injection volume was 10 162

µL. 163

For the MS/MS analysis, an Applied Biosystems (Foster City, CA; USA) 3200 164 QTRAP system was used. It was equipped with a turbo ion spray interface which was 165 operated in positive mode (ESI+). Its parameters were as follows in the EPI screening 166 approach for 300 pesticides and MRM quantitation for 55 pesticides, respectively: curtain gas 167 flow = 20 psi and 10 psi; collision gas = 12 and 5 (arbitrary units); ion spray voltage = 5000 168 and 5500 V; temperature = 450°C in both cases; ion source gas1 flow = 40 psi and 50 psi, ion 169 source gas2 flow = 50 psi in both cases; and dwell time of one transition was 5 and 15 ms, 170 respectively. Nitrogen was applied in the ion source and for the collision gas. In the 171 screening method, vendor recommended declustering potentials of 20, 35, and 50 V were 172 applied when the MRM signal automatically triggered the EPI process. 173 Applied Biosystems Analyst 1.4.2 software was used for instrument control and data 174 processing. For the determination of 300 pesticides, the commercial method of Applied

Concept of qualitative screening and quantitation of pesticide residues 181

In this study, we describe the combination of two parallel methods: 1) qualitative 182 screening for 300 target pesticides by LC-MS/MS using MRM data dependent triggered EPI 183 mode with the commercial spectra database; and 2) confirmation and quantitative 184 determination of the frequently used and/or previously detected pesticides using the MRM 185 method we developed for 55 pesticides. Compared to possible alternatives available to us 186 within our budget constraints, this concept was believed to give widest scope with the least 187 effort, and still give excellent qualitative and quantitative results, particularly when using 188 QuEChERS for sample preparation. We sought to evaluate and implement the approach using 189 commercial samples from the market. For efficiency and convenience, the two methods use 190 the same instrument working with the same column and using the same gradient program. 191 The workflow of the concept is shown in Figure 1, and the process is as follows: 1) 192 conduct AOAC Official Method 2007.01 and analyze the extract using the EPI screening 193 method for 300 pesticides; 2) if no pesticides are detected in the sample, no other 194 measurements are necessary; 3) if any of the 55 pesticides from the developed MRM method 195 are found to be positive in the EPI analysis, then re-inject the extract using the MRM method; 196 4) those presumptive positive residues are confirmed and quantified (or found not to be 197 present) using reference standards and a method of standard additions; 5) when a target 198 pesticide is found to be positive in the EPI method but is not included among the 55 MRM 199 analytes, then a reference standard of the pesticide is obtained, optimal ESI+ conditions are 200 determined, and the MRM method is modified to include it for further qualitative and 201 quantitative analysis. In this way, the MRM list of pesticide analytes grows over time. 202 Initial false positive results from the screening method can be uncovered with this 203 approach by comparing retention times between the methods, and findings that don't match 204 are rejected. Furthermore, the peak shapes must be the same, the MS/MS product ion 205 transitions must have similar ratios as the reference standards, the signal/noise (S/N) ratios for 206 all ion peaks must be >10, and quantitation must give a concentration greater than the 207 reporting limit. Quantitation, identification, and confirmation of chemicals using MS 208 techniques are discussed in the literature [START_REF] Lehotay | Identification and confirmation of chemical residues in food by 561 chromatography-mass spectrometry and other techniques[END_REF][START_REF] Bethem | 529 Establishing the Fitness for Purpose of Mass Spectrometric Methods[END_REF][START_REF] Milman | Identification of chemical compounds[END_REF]209 Document No. SANCO/2007/3131). 210 A major drawback in the use of matrix-matched calibration involves the need to find 211 blanks for the matrices needed, thus we chose to apply a method of standard additions using 212 multiple aliquots of the final sample extracts. This entailed taking three additional 80 µL 213 We checked that the slopes of all detected pesticides were linear, which was nearly always the 216 case for original sample concentrations less than about 200 ng g -1 , but if the slope was not 217 linear for higher pesticide concentrations in the sample, we diluted the extracts 5-or 10-fold 218 to reach the linear region. After one year of routine application of this technique, we 219 generated a calibration-slope database for the 55 investigated pesticides in 12 different fruit 220 and vegetable matrices. 221

222

Screening identification of 300 pesticides in EPI 223

In the commercial EPI approach we followed, a chosen (usually the most intensive) 224 transition of each targeted analyte is monitored, which translates to 300 transitions in this 225 method. If the intensity of the ion transition signal exceeds the chosen intensity threshold of 226 500 counts per second (cps), then the quasi-molecular ion is fragmented at 20, 35, and 50 V 227 collision energies to yield product ions, which are further evaluated for possible positive 228 findings (this technique is termed information dependent analysis by Applied Biosystems and 229 data dependent scanning or other terms by other vendors). The detection limits depended on 230 the 500 cps threshold in our study, and naturally, the system would be less sensitive if a 231 higher threshold was used. 232

The total ion current (TIC) chromatogram consists of the intensities of all 300 233 monitored transitions plus any additional product ion signals that arise if the threshold was 234 exceeded. Searches and presumptive identifications of pesticides from the TIC were started 235 manually in this version of software (Analyst 1.4.2.). An advantage of the EPI approach is 236 that MS/MS spectral library searching and comparisons are done automatically by the 237 software for the 20, 35, and 50 V collision energy spectra, but it allows checking and review 238 by the analyst. Several criteria have to be met simultaneously for the presumptive 239 identifications (also known as indications [START_REF] Lehotay | Identification and confirmation of chemical residues in food by 561 chromatography-mass spectrometry and other techniques[END_REF]) to be made: 1) a peak from the 240 precursor and product ion transitions must all have the same retention time; 2) the 241 characteristic fragmentation pattern of ions and their ratios obtained by the 3 different 242 collision energies have to match a compound in the library; and 3) the actual molecular 243 weight of the pesticide presumptively identified has to correlate with the quasi-molecular ion 244 In this example in Figure 2, the MS/MS spectral library search of just the 35 V 262 averaged spectrum is shown (see box v). The software calculates the matching factors for the 263 possible hits in the library and lists them on the screen. The findings can be sorted by name, 264 formula, molecular weight, reverse fit, fit, purity, and collision energy. The collision energy 265 is given along with the library spectra because different spectra are obtained at the different 266 conditions. The software-calculated fit, reverse fit, and purity values are given in terms of 267 percentage (fit and reverse fit relate to the spectral match of the sample spectrum to the library 268 spectrum, and vice versa, respectively, and purity relates to the presence of extra ions in the 269 sample spectrum that are not included in the library spectrum). 270

We analyzed many different types of fruit and vegetable matrices in experiments, and 271 we found that the software worked well on its own to provide the top hit for pesticides in the 272 library. The analyst needed only to review the retention times for the selected ion peaks for 273 the indicated pesticide. In the example shown in Figure 2, azoxystrobin and its most intense 274 first product ion transition, m/z 404 to m/z 372, is presented. The peak for that transition as 275 shown in box (iv) gave a prominent Gaussian peak, and the analyst decided to re-analyze the 276 extract in the MRM method, which included azoxystrobin. 277 278

False indications 279

False presumptive positives are when the pesticide is indicated to be present by the 280 screening method (including analyst review), but is not detected by the MRM method. Many 281 instances occurred when a positive precursor ion in the screening method would trigger the 282 eliminated false presumptive positives. The EPI was "falsely triggered" (threshold exceeded, 284 but no pesticide was identified) most commonly when the TIC contained extensive chemical 285 noise from the matrix background. These matrix components sometimes gave similar 286 fragmentation patterns as pesticides in the library, such as a false indication of the mass 287 spectrum for fenitrothion in lettuce extracts, but they were recognized and eliminated by the 288 analyst with practice during manual evaluation. We deemed it better to re-inject the sample 289 using the MRM method whenever we had reasonable doubt if a pesticide was present or not, 290 but in practice, there was very little reasonable doubt, and none of the re-injected samples 291 from the EPI screening method gave false positives in the MRM confirmation and 292 quantitation method. 293

Possible interferences from matrix are known to increase with respect to lower masses 294 (e.g., m/z < 200), and smaller pesticides tend to yield only a single product ion transition. 295

Compounds with low mass or that yield only one fragment ion had greater potential for false 296 positives (and false negatives) in general. An example of this is diphenylamine with MW 297 =169.2 amu, which gives only m/z 170 to m/z /93.0 transition. In this case, the quasi-298 molecular ion disappears even using the lowest 20 V collision energy, which makes it difficult 299 to detect in the EPI method. In EPI, if a pesticide is hidden behind a peak in the TIC, only 300 one characteristic transition will be seen, but in the MRM method, softer collision energy can 301 be used to obtain two transitions.. 302 303

False negatives 304

Sometimes, when we analyzed for the pesticides in the MRM method for the 55 305 pesticides, identifications would be made for pesticides that were not indicated in the EPI 306 method for 300 pesticides. False negatives mostly depended on the sensitivity difference 307 between the two applied methods (see the LOD values in Table 1). The MRM method only 308 found pesticides missed by the EPI screening method at low concentration levels (e.g., 10 ng 309 g -1 ). For example boscalid in carrot (33 ng g -1 ), in orange (17 ng g -1 ) and in grapes (29 ng g - 310 1 ), quinoxyfen in grapes (10 and 12 ng ng -1 ) and triadimenol in grapes (18 ng ng -1 ) were 311 detected solely by the MRM method. We do not know how many times false negatives 312 occurred when the extracts were not re-analyzed by the MRM method, but the lack of glaring 313 false negatives for pesticides at high concentrations was a good sign that the EPI approach 314 performed well. 315 Otherwise, the possibility of false negatives increases if the threshold value (500 cps in 316 this method) were enhanced, because it results in higher LODs in the EPI approach. We 317 found that this function to be critical; and 500 cps was optimal to obtain sufficiently low 318 detection limits. A lower setting caused an increase in the number of peaks appearing in the 319 TIC that created more manual work for the analyst. Naturally, new generation instruments 320 with similar functions are more sensitive (and faster). 321

A likely reason for the lack of apparent false positives was the manual evaluation of 322 the TIC in the screening method, which required a high level of attention by the analyst to 323 check for peaks for known ion transitions at known retention times for known pesticides. 324

High background levels in some cases made this very difficult, especially for commodities 325 with high fat (e.g., avocado) or high flavor and volatile (e.g., onion, garlic and ginger) 326 composition. 327 328

Achievements and pitfalls 329

As in every method, this screening approach has advantages and disadvantages. One 330 advantage is that pesticide reference standards are not required for all 300 targeted analytes in 331 the library. Presumptive identifications are still possible for pesticides in the extracts (and 332 potentially other chemicals that could be included in the MS/MS library). Extending the 333 method to new analyte(s) is possible as new standards are obtained. Another advantage is that 334 the method can screen for 300 pesticides, which is more than typical in monitoring methods, 335 and extensive validation is not needed for pesticides that are not detected (albeit it is 336 important to show that a pesticide analyte will be detected if it is present). In many cases, no 337 pesticides are found in the fruit and vegetable samples, or only one or a few pesticides will be 338 present. If the extract has few matrix components, then the manual evaluation of the given 339 TIC can be conducted easily. 340

The main disadvantage with any targeted triple quadrupole method is that the list of 341 analytes in the library is limited, and true unknown analysis cannot be conducted. The 342 approach is blind to non-targets, unlike in the case of TOF techniques. Another disadvantage 343 is that the screening method is time-consuming and can be problematic when the matrix is 344 very complicated. 345

Another pitfall in the EPI screening method occurs when two target compounds co-346 elute. Only the most intense precursor ion will trigger the EPI process for that m/z, and the 347 lower intensity ion, which may also exceed the 500 cps threshold, will not be detected. This 348 can also occur if an intense matrix peak at a different m/z masks the precursor ion of a The EPI function only fragments the quasi molecular ion of the more intensive transition, 359 thus, the transition for pyraclostrobin's fragmentation pattern was not recorded in this case. 360

The analyst noticed that pyraclostrobin also appeared in the apple sample extract, which was 361 confirmed by the MRM method and determined to have a concentration of 0.069 mg kg -1 . 362

Due to this "pitfall," the analyst must take extra care to review the EPI screening 363 chromatograms for the presence of pyraclostrobin near the TPP peak in all samples. 364 365

Confirmation of frequently detected pesticides in MRM mode 366

Confirmation 367

For confirmation and quantitation purposes, the two most intensive transitions for the 368 55 more commonly detected pesticide analytes in the MRM method are monitored. The 369 optimized conditions were entered into the method file as given in Table 1 (only one 370 transition could be obtained in the case of haloxyfop), which totaled 111 transitions. Table 1 371 also lists retention times, peak widths, ion ratios, and limits of detection (LODs) for the 372 analytes. The quasi-molecular ions were [M+H] + (M+1) in all cases except for propargite, 373 which had a strong ammonium adduct [M+NH 4 ] + (M+18). 374

Achievements and pitfalls 375

The MRM confirmation/quantitation method targeted those residues known to have 376 occured in Hungarian and secondarily in European markets (Data Pool of the Community 377

Reference Laboratories for Residues of Pesticides), and consequently these are targeted from 378 the aspect of their frequent occurrences. It was not worth the effort to include all 300 analytes 379 in the MRM method and QuEChERS has already been extensively validated in many labs. 380 Thus, we chose the 55 most prominent pesticides, which were those that had been previously 381 detected in the monitoring program. The selectivity and sensitivity of the MRM method are 382 better than the EPI method, as the LODs in shown). The LODs were estimated by injecting 1; 4; 10; 20; and 40 ng g -1 equivalent 385 standard mix solutions (not sample extracts), and when both transitions for an analyte in the 386 MRM method gave an observable signal peak at the correct t R , then that concentration was 387 assigned to be the LOD. In the EPI screening method, the LOD estimation required 388 preparation of 5 mixture solutions 11 pesticides each, which were chosen to avoid co-elutions. 389

The lowest concentration at the pesticide could be identified by the screening method was 390 recorded as the LOD. 391

The reported LODs are well below the MRLs for those pesticide that are registered in 392 typical fruits and vegetables, and the 0.01 mg kg -1 level is often reached for those pesticides 393 that are not registered in the commodities analyzed. It is not likely that false negatives above 394 the reporting limits create a problem in our monitoring approach for LC-amenable pesticides, 395 particularly for those pesticides with MRLs. 396 Matrix interferences are difficult to predict, but the analyst can be made aware of 397 possible analyte-analyte interfering transitions at similar t R . For example, the potential 398 interfering transition of azinphos-methyl and phosmet is presented in Figure 4. Whereas, the 399 317.9/160.2 and the 318.0/160.0 transitions can interfere with each other, their identification 400 in the MRM method relies also on their slightly different t R and 2nd ion transitions. To meet 401 identification criteria, the ion ratios for the pesticide transtions must fall within the intervals 402 listed in the laboratory quality control guidelines in the European SANCO directive 403 (SANCO/2007(SANCO/ /3131, 2007)). 404 405

Matrix effects and calibration slope database 406

The "Achilles heel" of LC-MS/MS for quantitative purposes are matrix effects, 407 typically from ion suppression in ESI mode. Matrix effects lead to uncertainty in the accuracy 408 of the quantitative results, and matrix-matched calibration is the most common approach used 409 to account for matrix effects. The need for blanks and extra extractions required for matrix-410 matching is not convenient and there are no guarantees that the matrix compensation is the 411 same between the different samples. When multiple matrix types appear in the same 412 sequence, it is questionable if one matrix can be used to represent another (the practice is 413 questionable even within the same matrix type). However, matrix-matching is felt to be more 414 practical compared to the few alternatives in routine multiclass, multiresidue analysis, and 415 matrix-matching has become an established custom [START_REF] Kmellár | Validation and uncertainty study of a comprehensive list of 160 pesticide residues in 551 multi-class vegetables by liquid chromatography-tandem mass spectrometry[END_REF]. Indeed, results from 416 The method of standard addition calibration is another alternative, but this also has can 419 be questioned due to potential nonlinearities in the calibration range of the analysis. We 420 chose to spare ourselves the time and materials needed for additional sample preparation of 421 blanks for matrix-matching by taking additional aliquots of each presumptive positive extract 422 for the method of standard additions. All 55 pesticides were added to each extract for 423 confirmation and quantitation in the MRM method even when only a single pesticide was 424 indicated in the EPI screening method. In this way, we generated a large amount of data for 425 calibration experiments and comparisons. 426

At first, we constructed a database about the obtained calibration slopes originating 427 from 12 selected matrices. A total of 10 calibrations were averaged per each pesticide in each 428 matrix, which were performed in the analyses of the 200 samples over the course of a year. 429

The comparison of slopes over time showed a high variation for many pesticides even for the 430 same matrix when the signals were not normalized to the surrogate standard, TPP. To track 431 method performance, we constructed a control chart of peak areas of TPP, which was added at 432 0.333 mg kg -1 to all samples. As shown in Figure 5, a recognizable change occurred after 90 433 samples when the source was thoroughly cleaned and detector voltage changed from 2400 to 434 2500 V (maximum = 3200 V). The curtain plate of the ion source was usually cleaned once 435 per week, but at this time, we also cleaned the orifice plate and the Q0. Considering that the 436 fluctuations of TPP intensities included sample preparation as well as instrument performance 437 aspects, the TPP signal fluctations were reasonably small. Thus, both the sample preparation 438 and the MRM method were performing quite well, especially considering that so many 439 samples and sample types were analyzed. 440 By normalizing the peak areas of the pesticides to peak areas of TPP for each 441 calibration point, the consistency of day-to-day calibration slopes improved. Table 2 presents 442 the TPP-normalized matrix-matched calibration slopes for the 12 different matrices tested. 443

The 54 pesticides (oxamyl was too insensitive for inclusion) are listed in order of t R to 444 possibly infer large matrix co-eluting peaks that induced ion suppression in that part of the 445 chromatogram (of course, TPP could also be affected by matrix co-elutants, which 446 complicates interpretation of the results). The values in bold designate average slopes when 447 RSD >20%. Many of the pesticides gave very consistent slopes from day-to-day and matrix-448 to-matrix, as observable by the overall average slope ± standard deviation column in effects in the different matrices. Conversely, some pesticides gave highly variable slopes in 451 all matrices, which indicated matrix effects or, more likely and simply, that the pesticide is 452 less stable or has more problematic analysis. This is expected in routine multiclass, 453 multiresidue analysis, especially over the course of a year at different instrument maintenance 454 conditions. Even for those pesticides with variable slopes within a particular matrix, only a 455 few pesticides gave overall average slopes with >20% RSD (shown in bold text) among the 456 12 matrices tested. 457 458

Results of a one-year routine application 459

During a one-year routine application of this monitoring approach (March 2008to February 460 2009), 200 samples from the Hungarian market were analyzed (15-20 samples/month). In all 461 13 types of fruit, 14 types of vegetables, and 10 other sample types were analyzed, as listed in 462 Table 3. The confirmed positive results sorted by pesticides and their concentration range in 463 the samples are presented in Table 4. Vegetable samples originated mainly from Hungary and 464 nearby EU countries, but a large number of fruit samples, especially tropical fruits, were 465 imported from southern European countries (e.g. Spain, Italy, and Greece) or non-EU 466 countries in Central or South America, Africa, and Turkey. Exactly half of the samples gave 467 positive confirmations for at least 1 residue (up to 5 pesticides were found in one sample), and 468 none of the 300 LC-amenable pesticides were detected in the other half. 469

The most frequently detected pesticides were the fungicides imazalil and 470 thiabendazole in fruits and azoxystrobin in vegetables. Diphenylamine was detected in the 471 samples independently from the commodity (we checked the tubes, acetonitrile, water and 472 other reagents for contamination of diphenylamine, but found that everything was clear). 473 Among these, the determined concentrations of azoxystrobin were relatively low (0.01-0.55 474 mg kg -1 ), while thiabendazole and imazalil often were found at levels as high as 0.90 and 6.66 475 mg kg -1 , respectively. However, none of these results exceeded the current EU MRLs. 476

Prochloraz was found at high concentration in 3 lemon samples (from Argentina and Turkey) 477 and nicobifen was found to occure at the MRL (10 µg kg -1 ) in a cabbage sample from 478

Hungary. 479

Diphenylamine mostly appeared in samples during the summer months at low 480 concentrations (0.006-0.202 mg kg -1 ), and the appearance was independent from the country 481 of origin and the commodity. Besides being a fungicide, diphenylamine is widely used as a 482 rubber antioxidant and accelerator, solid fuel rocket propellant, stabilizer for explosives, for 483 preparation of pharmaceutical and veterinary medicine, as a storage preservation of apples, and as a reagent in analytical chemistry. It is conceivable that the stored fruits and vegetables 485 were treated with diphenylamine to preserve their quality and freshness, or that it was a 486 contaminant that did not orginate from a pesticide application. 487 488

Conclusions 489

The developed combination of the two described methods permitted the fast and easy 490 qualitative screening of 300 target pesticides in a 45-min LC-MS/MS run. Albeit the manual 491 evaluation of the given chromatograms increased the analysis time by an additional 10 min 492 per sample, very little time, costs, and labor was spent on sample preparation. In the case of 493 dirty samples, some false indications were observed, but these were caught by the use of the 494 MRM confirmatory and quantitative method for the 55 more common pesticides. The 495 construction of standard addition calibration standards was carried out with the same extract 496 that was injected for screening the 300 compounds previously. A large calibration database in 497 different matrices were collected to show the consistency of the average calibration slope, 498 which helped us check the accuracy of the calculated results from the method of standard 499 additions. 500

The one-year routine application of this scheme was a comprehensive study that 501 showed consumer exposure of pesticides from fruits and vegetables that can be purchased in 502 13.9 ± 1.7 Thiamethoxam 1.7 1.9 1.7 1.4 1.8 2.0 1.6 1.4 1.5 1.8 1.5 1.4 1.6 ± 0.2 Methiocarb-sulfoxide 7.0 7.8 8.4 8.5 13.6 11.6 9.8 7.0 8.2 10.9 9.0 9.6 9.3 ± 1.9 Imidacloprid 1.9 2.5 2.3 1.7 2.6 2.6 2.2 1.8 1.7 2.0 2.2 2.1 2.1 ± 0.3 Dimethoate 6.5 7.1 6.6 6.4 6.6 8.5 7.0 5.8 5.4 5.8 5.3 6.5 6.5 ± 0.8 Acetamiprid 6.4 7.4 7.1 6.9 7.6 8.1 6.9 6.1 5.6 6.1 6.0 6.3 6.7 ± 0.7 Methiocarb-sulfone 0.9 1.6 1.2 1.7 5.3 1.9 2.9 1.8 1.5 2.2 2.0 2.9 2.2 ± 1.

  S. Department of Agriculture, Agricultural Research Service, Eastern Regional Research 12 Center, 600 E. Mermaid Ln., Wyndmoor, PA 19038of brand or firm name does not constitute an endorsement by the U.S. 19 Department of Agriculture above others of a similar nature not mentioned.

  discussed and it was tested on 200 fruit and vegetables samples from the Hungarian market.

  , 100 and 250 ng g -1 , which were measured by the MRM method. 215

Figure 2

 2 Figure 2 shows an example for an EPI library-based identification of the pesticide 249 azoxystrobin from a cabbage sample extract. This example shows the evaluation of a peak 250 obtained at the retention time of 22.0 min. As observable in boxes (i) and (ii) in Figure 2, the 251 software detected an enhanced signal in the TIC that exceeded the intensity threshold of 500 252 cps, which triggered collision activated dissociation of the most intense precursor ion at the 253 given 3 collision energy voltages (default values of 20, 35, 50 V were used). As shown in 254 section (iii) of Figure 2, each averaged spectrum represent characteristic fragmentation 255 patterns from the precursor ion. The m/z 404.5 ion that appears in the 20 V spectrum very 256 likely indicates the quasi-molecular ion of the chemical of interest. The other two EPI spectra 257 at increasing collision energies show how the m/z 404.5 ion disappears while ions of lower 258 m/z (fragments of the probable quasi-molecular ion) increase. Box (iv) shows the extracted 259 ion chromatogram for the m/z 404 to m/z 372 transition, which is the most intense and 260 probably indicates the loss of a methoxy group from the molecule. 261

  occur, but the automated library search and analyst review of the spectra 283

  The best example of analyte-analyte co-elution is TPP (t R = 25.8 min) and 350 pyraclostrobin (t R = 26.0 min), which is presented for apple in Figure3. Pyraclostrobin is 351 hardly visible in the TIC because it is masked behind the the large TPP peak. A small tailing 352 effect can be seen in the enlarged picture of the TPP peak. The 3 EPI spectra at 25.8 min 353 show a clear fragmentation pattern, which is known to correspond to the TPP added in all 354 samples at 0.333 mg kg -1 during extraction. Of course, the identification of TPP is expected 355 (required for quality control purposes) in all samples, but the software cannot find 356 pyraclostrobin at low concentrations appearing 0.15 min later than the TPP peak apex, despite 357 the different fragmentation ions (327.1/152.2 for TPP vs. 388.2/194.3 for pyraclostrobin). 358

the

  Hungarian market. Carbendazim, dimethomorph, diphenylamine, nicobifen, haloxyfop, 503 diazinon and dimethoate exceeded the current EU MRLs a total of 12 times among the Piedra L, Hernando M D, Fernández-Alba A R, Contreras M. 2000. Splitless large-516 volume GC-MS injection for the analysis of organophosphorus and organochlorine pesticides 517 in vegetables using a miniaturised ethyl acetate extraction. Analyst 125 1397-1402.

Figure 1 .Figure 2 .Figure 3 .Figure 4 .Figure 5 .

 12345 Figure 1. Workflow for the combination of a screening and quantitation approach by LC-MS/MS. For details, see text. *: commercial method of Applied Biosystems; **: the retention times of the appropiate ion peaks have to be the same for the analyte in both methods 158x119mm (96 x 96 DPI)

  Table 1 demonstrate (LODs of the 245 other

	384	compounds in EPI were not measured, but they are believed to be within the range of the 55
		F o r
		P
		e
		e r
		R
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		v i e
		w
		O n l
		y
		13

  Table 2 449 among the 12 matrices. Those pesticides with consistent slopes likely have little or no matrix

	F o r
	P
	e
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	R
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Table 1 .

 1 Detection parameters in the MRM quantitative method for 55 pesticides plus the TPP surrogate standard, LOD of the MRM and EPI screening method. (DP: Declustering Potential; EP: Entrance Potential; CEP: Collision Cell Entrance Potential; CE: Collision Energy; CXP:

					Food Additives and Contaminants
	Collision Cell Exit Potential)
		MW	[M+H] +	product	ion ratio						t R	pk width	MRM LOD	EPI LOD
	pesticide	(amu)	(m/z)	ions (m/z)	(%)	DP EP CEP CE CXP	(min)	(min)	(ng/kg)	(ng/kg)
	Acetamiprid	222.1	223.2	126.1 56.1	22	26 4.5	14	25 33	4 4	11.5	1.02	4	10
	Azoxystrobin	403.4	404.0	372.0 329.0	33	31 5.5	18	19 39	12 4	22.0	1.03	1	4
	Boscalid	343.2	343.0	307.0 140.0	61	56 8.5	16	25 25	10 4	22.3	0.81	4	40
	Bupirimate	316.1	317.2	108.0 166.2	86	26 8.5	34	37 31	2 4	20.1	1.41	1	4
	Buprofezin	305.4	306.0	201.0 116.0	93	31	4	16	17 21	4 4	25.7	1.56	1	10
	Carbaryl	201.2	202.1	145.0 127.0	34	26	6	14	13 35	4 4	17.8	1.31	1	20
	Carbendazim	191.2	192.2	160.0 132.0	17	36 8.5	12	23 39	4 4	3.6	1.45	1	4
	Cyprodinil	225.1	226.2	76.9 93.1	80	41	4	16	55 43	4 8	19.4	1.69	4	10
	Diazinon	304.3	305.0	169.0 153.0	62	36	5	16	31 25	4 4	26.5	1.29	1	1
	Difenoconazole	406.3	406.1	251.0 111.0	32	41 6.5	30	31 73	4 4	24.9	1.06	1	10
	Diflubenzuron	310.7	311.0	158.1 141.1	15	71	10. 5	14	19 39	4 4	23.2	0.64	20	40
	Dimethoate	229.3	230.0	125.0 199.0	97	16 4.5 14	25 13	4 4	11.3	1.01	1	20
	Dimethomorph	387.0	388.2	301.2 165.2	58	51 4.5	20	27 43	4 4	19.5 & 20.0	1.60	1	40

http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk http://mc.manuscriptcentral.com/tfac Email: fac@tandf.co.uk

Table 2 .

 2 Average least linear squared calibration line slopes for the pesticide analytes (listed in order of increasing t R ) normalized to the equivalent 0.333 mg/kg TPP internal standard signal (*10 -3 ) in matrix-matched calibration standards for 12 different matrices (n = 10)

	: 1 =

0.5 0.2 0.7 0.6 0.8 0.4 0.9 0.5 0.2 0.3 0.3

		Food Additives and Contaminants
	Linuron	2.8 4.1 2.7 2.8 3.1 2.9 2.9 3.0 2.0 3.1 2.7 2.8	2.9 ± 0.4
	Fenamiphos	16.5 19.0 16.8 16.9 16.8 19.3 18.6 18.5 14.0 16.1 14.5 17.2	17.0 ± 1.6
	Azoxystrobin	17.4 18.2 16.9 16.2 17.7 19.7 19.4 17.9 15.8 16.4 16.2 19.2	17.6 ± 1.3
	Phosmet	4.7 5.3 5.5 4.0 7.3 7.2 6.6 3.2 4.9 6.1 5.8 6.2	5.6 ± 1.2
	1 9.2 ± 1.2 3.8 ± 0.5 7.9 ± 0.7 6.8 ± 0.7 14.3 ± 2.3 16.0 ± 1.6 3.5 ± 0.4 5.2 ± 0.4 2.7 ± 0.3 15.8 ± 1.5 2.6 ± 0.5 1.4 ± 0.7 5.4 ± 1.9 8.3 ± 0.8 9.7 ± 1.0 12.1 ± 1.1 0.3 ± 0.1 26.5 ± 2.3 10.9 ± 0.8 28.0 ± 3.4 19.5 ± 2.0 1.1 ± 0.5 3.2 ± 0.5 4.6 ± 0.5 0.9 ± 0.1 13.3 ± 1.3 0.4 0.5 ± 0.2 8.6 10.5 9.8 9.2 11.2 10.8 8.6 7.6 7.0 8.1 8.9 9.6 3.9 4.4 3.7 4.2 2.9 4.7 4.4 4.3 3.4 3.8 3.2 3.3 8.2 8.6 7.4 7.3 8.5 8.7 8.9 7.3 6.7 7.6 7.4 7.9 6.6 7.6 6.5 7.7 7.1 7.8 7.0 7.1 5.9 6.0 5.8 6.0 14.3 15.6 14.7 12.0 17.7 18.1 15.8 10.6 12.4 13.3 11.4 15.2 15.1 17.7 16.0 16.4 16.3 18.5 17.2 17.4 13.0 13.7 14.1 16.1 3.7 3.8 3.3 3.9 3.1 3.5 4.1 3.6 3.4 3.7 2.8 3.1 4.8 5.9 5.4 5.0 5.3 5.8 5.8 4.9 4.3 5.2 5.0 5.1 2.5 3.0 2.9 2.4 3.1 3.0 3.0 2.6 2.2 2.6 2.6 2.9 14.8 18.3 15.9 13.5 16.1 18.0 17.9 15.8 14.1 15.6 14.5 14.5 2.4 3.7 2.5 2.2 3.5 2.9 2.6 2.7 1.9 2.2 2.1 2.4 1.0 2.4 1.2 1.1 2.5 2.8 1.0 1.3 0.8 1.1 1.2 1.0 4.3 8.6 4.9 4.4 7.7 9.2 4.4 5.4 3.3 4.2 4.8 4.0 8.0 8.7 8.3 7.4 9.7 9.8 8.9 7.5 7.3 7.4 7.8 8.9 9.1 11.2 9.8 8.8 9.8 11.4 11.0 9.2 8.3 10.0 9.3 8.4 11.6 13.1 11.2 11.3 13.2 14.2 13.9 10.6 11.4 11.5 11.6 12.0 0.2 0.3 0.2 0.3 0.5 0.4 0.2 0.3 0.2 0.2 0.2 0.2 27.4 28.6 24.1 26.9 26.7 26.4 31.7 27.7 25.5 24.9 22.2 25.5 11.3 11.2 10.7 10.0 10.9 12.3 12.2 10.6 10.2 10.0 10.0 11.5 F o r P e e r R e v i e w Thiophanate-methyl Thiacloprid Imazalil Pyrimethanil Carbaryl Metalaxyl Cyprodinil Fenhexamid Boscalid Tebuconazole Diflubenzuron Haloxyfop Penconazole Malathion Diphenylamine Difenoconazole Kresoxim-methyl Buprofezin Pyraclostrobin F o r Diazinon 27.6 30.7 25.2 31.6 24.4 31.3 32.6 31.7 26.7 28.2 22.3 23.6 Pirimiphos-methyl 19.6 20.9 17.4 21.6 18.3 22.3 22.6 20.4 18.7 19.9 16.1 16.7 Isofenphos-methyl 0.8 1.1 0.4 1.8 1.5 1.9 0.8 1.4 0.8 0.7 0.7 0.8 P Phosalone 3.2 4.2 2.9 3.4 3.2 2.5 3.4 3.1 2.3 3.8 3.4 2.4 Quinoxyfen 5.3 4.8 4.4 4.3 4.2 4.3 5.8 4.1 4.7 5.2 4.1 4.3 Indoxacarb 0.9 1.0 0.9 0.8 1.0 1.0 1.1 0.8 0.8 1.0 0.9 1.1 Trifloxystrobin 15.0 12.5 12.2 14.8 11.6 13.8 16.0 13.0 12.9 13.2 11.4 13.4 e e r O n l y Isofenphos Pyriproxyfen 26.2 20.4 19.6 22.9 21.1 20.0 27.9 20.1 22.9 26.6 17.8 21.5 22.2 ± 3.0 Fenazaquin 16.7 13.3 11.7 15.8 11.8 12.7 16.9 13.4 15.4 16.2 11.0 11.8 R 13.9 ± 2.1 Pendimethalin 2.4 1.8 1.8 2.0 1.8 1.8 2.7 1.8 1.9 2.2 1.8 2.3 2.0 ± 0.3 e
	Dimethomorph Bupirimate Prochloraz Triadimenol Hexythiazox Propargite Methiocarb	4.9 5.6 5.3 4.9 5.9 6.1 5.5 5.5 4.3 4.7 5.0 5.4 4.9 4.9 4.2 5.2 4.1 5.4 5.3 5.3 4.4 4.5 3.8 4.2 6.1 7.0 5.8 5.5 4.5 7.4 7.0 5.3 5.6 5.6 5.7 6.1 7.2 8.4 6.5 7.1 9.5 11.0 9.3 7.7 6.6 7.8 6.1 7.2 2.7 1.8 2.0 2.4 1.8 1.8 2.7 1.7 2.0 2.3 1.9 2.2 0.8 0.3 0.5 1.0 0.4 0.4 0.8 0.7 0.6 0.5 0.3 0.7 v i e 8.8 10.5 9.9 7.9 11.3 11.8 10.3 9.0 8.3 8.8 9.6 10.5 w	5.3 ± 0.5 4.7 ± 0.5 6.0 ± 0.8 2.1 ± 0.3 0.6 ± 0.2 7.9 ± 1.4 9.7 ± 1.2
		O n l
		y

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Table 3 .

 3 Distribution of total and samples found to contain residues per commodity analyzed.

			No. positive /
		Commodity	total samples
	Fruits	Apple	7/14
		Grapes	6/9
		Lemon	8/8
		Watermelon	2/8
		Pear	5/6
		Peach	3/6
		Banana	5/5
		Nectarine	3/3
		Pineapple	0/2
		Strawberry	2/2
		Grapefruit	2/2
		Orange	2/2
		Melon	0/2
	Vegetables	Pepper	10/23
		Lettuce	10/18
		Tomato	5/15
		Cabbage	7/16
		Carrot	5/6
		Garlic	2/5
		Cucumber	4/5
		Parsnip	1/5
		Onion	0/5
		Celery	2/3
		Radish	0/2
		Pumpkin	0/2
	Other	Mushroom	3/8
		Misc.	6/9
	Total		100/200

Table 4 .

 4 Determined pesticides and their concentration ranges in the 200 samples analyzed.

	Fruits (71 samples)	Vegetables/Other (129 samples)

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Pia Ostergaard

Michael A Simpson

Glen Brice

Sahar Mansour

Fiona Connell

Alexandros Onoufriadis

Anne H Child

Jae Hwang

Kamini Kalidas

Peter S Mortimer

Richard Trembath

Steve Jeffery

Rapid identification of mutations in GJC2 in four limb primary lymphoedema using whole exome sequencing combined with linkage analysis

ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

Introduction

The accumulation of protein-rich fluid in the interstitial spaces results from an anatomical or functional defect in the lymphatic vessels and can occur as a non-syndromic Mendelian condition or as part of a more complex, syndromic disorder [START_REF] Connell | Phenotypic characterization of primary lymphedema[END_REF]. Primary lymphoedema most commonly affects the lower limbs, but other body parts (upper limbs, face and genitalia) can also be affected. Lymphoscintigraphy occasionally reveals lymphatic abnormalities in the upper limbs in individuals presenting with oedema of the lower limbs [START_REF] Connell | Phenotypic characterization of primary lymphedema[END_REF]. However, individuals with clinical signs of primary lymphoedema in all four limbs are not commonly seen in the lymphoedema clinic. Connell et al (2010) [START_REF] Ferrell | Hereditary lymphedema: evidence for linkage and genetic heterogeneity[END_REF] reported 23 cases out of a cohort of 333 probands with late-onset multisegmental primary lymphoedema affecting other body parts in addition to the lower limbs.

A proportion of these had an autosomal dominant family history (Connell, personal communication)

As with many other Mendelian traits, positional cloning by linkage mapping has proved to be a powerful approach in the identification of genes underlying primary lymphoedema. To date five genes have been shown to be mutated in disorders where lymphoedema is the major feature.

Three genes were identified by linkage based positional cloning; FLT4 (VEGFR3) in Milroy disease [START_REF] Ferrell | Hereditary lymphedema: evidence for linkage and genetic heterogeneity[END_REF][START_REF] Evans | Sarfarazi M Mapping of primary congenital lymphedema to the 5q35.3 region[END_REF][START_REF] Karkkainen | Missense mutations interfere with VEGFR-3 signalling in primary lymphoedema[END_REF][START_REF] Irrthum | Congenital hereditary lymphedema caused by a mutation that inactivates VEGFR3 tyrosine kinase[END_REF], FOXC2 in Lymphoedema Distichiasis Syndrome [START_REF] Mangion | A gene for Lymphedema-distichiasis maps to 16q24.3[END_REF][START_REF] Fang | Mutations in FOXC2 (MFH-1), a forkhead family transcription factor, are responsible for the hereditary lymphedema-distichiasis syndrome[END_REF] and SOX18 in the rare Hypotrichosis-Lymphoedema-Telangiectasia syndrome [START_REF] Irrthum | Vikkula M Mutations in the transcription factor gene SOX18 underlie recessive and dominant forms of hypotrichosis-lymphedema-telangiectasia[END_REF]. In addition, the human mutation of CCBE1 was identified in Generalised Lymphatic Dysplasia/Hennekam syndrome [START_REF] Alders | Mutations in CCBE1 cause generalized lymph vessel dysplasia in humans[END_REF][START_REF] Connell | Linkage and sequence analysis indicate that CCBE1 is mutated in recessively inherited generalised lymphatic dysplasia[END_REF] because loss of function defects in ccbe1 in the zebrafish mutant 'full of fluid' (fof) highlighted the role of the CCBE1 protein product in lymphangiogenesis [START_REF] Hogan | Ccbe1 is required for embryonic lymphangiogenesis and venous sprouting[END_REF]. Most recently, [START_REF] Ferrell | GJC2 missense mutations cause human lymphedema[END_REF] identified mutations in GJC2 after differential transcript expression analysis highlighted a potential role of this gene in lymphoedema [START_REF] Ferrell | GJC2 missense mutations cause human lymphedema[END_REF].

The experimental route from linkage interval to causative mutation has traditionally been by

Sanger sequencing of the coding regions and associated splice sites of the genes located within the delimiting recombination boundaries. Whilst this approach has proved successful it is often limited by the size of the region of interest and the number of genes within it. Sequencing of more than a handful of genes can become a costly and time consuming process. However, recent developments in high-throughput second generation sequencing and hybrid capture techniques [START_REF] Gnirke | Solution hybrid selection with ultra-long oligonucleotides for massively parallel targeted sequencing[END_REF] now offer a more cost effective approach to this sequencing phase. Several recent investigations have shown the utility of customisable capture arrays for sequencing genes located within linkage intervals [START_REF] Shendure | Next-generation DNA sequencing[END_REF][START_REF] Brkanac | IFRD1 is a candidate gene for SMNA on chromosome 7q22-q23[END_REF][START_REF] Nikopoulos | Next-generation sequencing of a 40 Mb linkage interval reveals TSPAN12 mutations in patients with familial exudative vitreoretinopathy[END_REF][START_REF] Rehman | Targeted capture and next-generation sequencing identifies C9orf75, encoding taperin, as the mutated gene in nonsyndromic deafness DFNB79[END_REF]. However, improvements in capture efficiency with 'in solution' methods combined with increases in sequence yield now make whole exome sequencing an affordable alternative.

We present a large, multigenerational pedigree (Family I in Figure 1) in which four limb primary lymphoedema is segregating in an autosomal dominant manner. Linkage analysis combined with whole exome sequencing rapidly identified two candidate genes with potential pathogenic variants co-segregating with the disease status. Subsequent analysis of these two genes in a cohort of additional individuals with primary lymphoedema confirmed that the identified defect in GJC2 underlies four limb lymphoedema in Family I, and also provides evidence that mutations in GJC2 contribute to a significant proportion of autosomal dominant lymphoedema cases.

Methods

Patients and controls

PCR and Sanger sequencing

Primers were designed to cover exonic and intronic flanking sequences for N VL and GJC2, (primer sequences and PCR conditions are available upon request). PCR products were sequenced using BigDye Terminator v3.1 and an ABI 3130xl Genetic Analyzer. The sequencing traces were visually inspected in Finch TV v1.4 (Geospiza, Inc.) and compared to wild type reference sequence in CLC Sequence Viewer 6.4 (CLC bio A/S).

Results

Clinical assessment of four limb lymphoedema in Family I Family I: seven affected members of this family along with six at-risk relatives were clinically examined by one of the authors (GB). The inheritance pattern was consistent with autosomal dominance and there was no evidence of non-penetrance.

Mutation Validation

Initial investigation to establish which of the variants was pathogenic was undertaken by Sanger sequencing of coding exons and associated splice sites of NVL and GJC2 in a second family (Family II) also consistent with linkage to the same chromosome 1 region. Interestingly, the two variants identified in Family I were also observed and shown to co-segregate in this family.

While clinical family histories did not suggest that the two families were closely related, interrogation of the SNP genotypes generated for linkage mapping across the chr 1q42.1 linkage interval (8 SNPs) suggested the presence of a shared ancestral haplotype across this region in the two families (data not shown).

Further sequencing of NVL and GJC2 was undertaken in a cohort of 19 unrelated individuals with primary lymphoedema and revealed three further families with variants in GJC2 but no additional variants in NVL. The variants in GJC2 observed in this cohort comprised two proposita with the same Ser48Leu variant that was identified in Families I and II, and a single occurrence of a non-synonymous variant (c.629T>G, p.Met210Arg). This variant was not observed in 150 control individuals. These results strongly suggest that GJC2 is the site of mutations underlying the autosomal dominant lymphoedema phenotype linked to this locus.

Clinical assessment of GJC2 mutation positive individuals

Family II: four affected individuals from this family, which showed autosomal dominant inheritance, were clinically examined. They all had four limb lymphoedema, with one having additional involvement of the face and genitals. The most severely affected individual reported multiple episodes of cellulitis. The age of initial onset of oedema was variable but predominantly in childhood. In one individual, leg swelling developed in childhood but arm swelling was not noted until the age of 30 years. Lymph scans were performed in three individuals. All scans revealed that, although lymph channels could be clearly imaged, uptake of tracer in the lymph nodes at two hours post-injection was markedly impaired in all four limbs. Specifically, lymph transport over two hours was substantially reduced. One member of the family had undergone venous duplex scans of the lower limbs. This revealed incompetent great saphenous veins bilaterally.

Family III: two members of this family (father and daughter) were examined in clinic. A history of lymphoedema in several other family members was reported, consistent with autosomal dominant inheritance. Both members of this family who were examined had lower limb lymphoedema only. In the younger of the two family members the oedema significantly worsened at the age of 13 years but there is a history of onset before this age, possibly at birth.

Her father did not recognise he was affected until examined in clinic and therefore the true age of onset is not known. He had, however, suffered with varicose veins from a young age.

Clinically the hands were not oedematous so only lower limb lymph scans were requested.

These showed relatively normal main tract filling but with marked impaired uptake in the groin nodes at two hours, consistent with distal hypoplasia of the lymphatics. Vein scans performed on both individuals revealed identical results, with marked incompetence of the great saphenous vein bilaterally.

Family IV: a Somalian family with two sisters affected by swelling to the knees bilaterally.

Although their parents were distant cousins, their mother and maternal aunt were also reported to be affected; again consistent with autosomal dominant inheritance. The age of onset in both cases was 12 years. Results of four limb lymph scans and duplex vein scans are awaited.

Family V: this family showed clear autosomal dominant inheritance with four affected members in three generations. The age of onset was between the age of 4-40 years. Multiple episodes of cellulitis were a feature. Lymphoscintigraphy showed impaired drainage in all four limbs and a venous duplex scan revealed incompetence of the great saphenous vein bilaterally.

Details of the GJC2 mutations, and summary of the clinical details, are given in Table 1.

Discussion

This study clearly demonstrates the power and efficiency of the combination of linkage analysis with whole exome sequencing in the identification of causative genes in Mendelian phenotypes. Moving from the successful identification of the co-segregating chromosome 1 interval containing 173 genes to the identification of the causative mutation would previously have been prohibitively costly and time consuming, beyond Sanger sequencing of a small number of potential candidate genes. Recent developments in high-throughput sequencing have provided a novel solution to such challenges. The approach undertaken here enabled rapid and cost effective sequencing of the entire exome, but interrogation of the generated sequence data was restricted to genes located within the linkage interval. This initial sequencing led to a shortlist of two potential variants which could not be differentiated within Family I, but ultimately this was resolved through the identification of additional mutations in GJC2 in a cohort of unrelated lymphoedema cases. It is also notable that computational prediction of potential functional consequences of the two variants using the SIFT algorithm was of no benefit in this scenario. The results predicted the Val746Met variant in NVL to be damaging whereas the Ser48Leu variant in GJC2 was proposed to be tolerated. The use of computational predictors of the functional consequences of variants with algorithms including SIFT and PolyPhen have been proposed as a method of filtering variants for potential pathogenicity in high throughput sequencing studies [START_REF] Ng | Targeted capture and massively parallel sequencing of 12 human exomes[END_REF]. However, the experiences in our study and those of Ng et al (2010) [START_REF] Ng | Exome sequencing identifies the cause of a mendelian disorder[END_REF] suggest that the interpretation of computational predictions must be handled with appropriate caution. Ultimately the success of the linkage and second generation sequencing approach in this study is clear, with the identification of GJC2 as the site of mutation in primary lymphoedema. This finding confirms the investigations of Ferrell et al [START_REF] Ferrell | GJC2 missense mutations cause human lymphedema[END_REF], who used the results from a differential gene expression study [START_REF] Wick | Transcriptomal comparison of human dermal lymphatic endothelial cells ex vivo and in vitro[END_REF] to identify candidate genes in lymphoedema on the basis of greater expression in lymphatic endothelial cells (LECs) compared to blood endothelial cells (BECs). GJC2 was highlighted by their approach as its expression levels were five times higher in LECs than BECs [START_REF] Wick | Transcriptomal comparison of human dermal lymphatic endothelial cells ex vivo and in vitro[END_REF].

Subsequent sequencing of this gene in a large cohort (160 probands) of lymphoedema patients revealed six pathogenic mutations within the coding region of GJC2 [START_REF] Ferrell | GJC2 missense mutations cause human lymphedema[END_REF]. [START_REF] Diekmann | Pelizaeus-Merzbacher-like disease is caused not only by a loss of connexin47 function but also by a hemichannel dysfunction[END_REF]. A mechanism to explain this is currently difficult, especially as this mutation is one of those proposed to be loss of function of hemichannels in PMLD rather than dysfunction [START_REF] Diekmann | Pelizaeus-Merzbacher-like disease is caused not only by a loss of connexin47 function but also by a hemichannel dysfunction[END_REF].

We conclude that mutations in GJC2 appear to be a significant cause of autosomal dominantly inherited four limb and bilateral lower limb lymphoedema. Further work will be required to determine the molecular mechanisms by which GJC2 contributes to the formation and maintenance of the lymphatic system. Legend to Figure 1. Family I in which the initial linkage analysis was performed, and family II in which the same two novel variants identified in family I (NVL (c.2236G>A; pVal746Met), and GJC2 (c.143C>T; p.Ser48Leu)) were also observed.

  passed un-noticed in all heterozygotes. More likely is that the mechanism of action is different in the two conditions. Examples of genes causing different diseases where there is dominant or recessive inheritance of mutations include ROR2 in brachydactyly and Robinow whether the same scenario applies here vis a vis PMLD. It is of interest that there appear to be at least two mechanisms for the effect of mutations in PMLD, namely a loss of hemichannel function, or in some cases a dysfunction[START_REF] Orthmann-Murphy | Loss-of-function GJA12/connexin47 mutations cause Pelizaeus-Merzbacher-like disease[END_REF][START_REF] Diekmann | Pelizaeus-Merzbacher-like disease is caused not only by a loss of connexin47 function but also by a hemichannel dysfunction[END_REF]. To further complicate the picture, a mutation identified by Ferrell et al as causative in lymphoedema , p.Gly149Ser, is also reported as being causative for PMLD

	From	a	clinical	viewpoint,	individuals	identified	with	heterozygous	mutations	in	GJC2
	characteristically presented with four limb lymphoedema, although some affected individuals
	only exhibited bilateral lower limb oedema. The age of onset was variable, both between and
	within families, ranging from birth to 40 years of age. It is possible that those affected with only syndrome (27, 28, 29) and BSCL2 in spastic paraplegia type 17 and generalised lipodystrophy
	lower limb lymphoedema may develop upper limb swelling at a later date. The upper limbs are type 2 (30,31). In both these cases there appears to be a loss of function in the recessive
	always less severely affected and need to be examined specifically for lymphoedema. In those conditions and a gain of function, or interference with the wild type product when there is
	individuals subjected to lymphoscintigraphy, functional rather than anatomical abnormalities dominant inheritance.
	have been demonstrated. Thus, lymph drainage routes as seen on images looked normal but There is not yet sufficient evidence on the functional effects of GJC2 mutations in
	quantification lymphoedema to know revealed	unequivocally	reduced	lymph	transport	as	measured	by	ilio-
	inguinal/axillary node uptake over two hours. This was a consistent finding in all five
	lymphoscintograms thus far undertaken. Furthermore, reduced axillary lymph node uptake and
	impaired upper limb transport was evident in one individual without obvious hand oedema.
	Therefore, phenotyping for this category of lymphoedema requires a careful history and
	examination of hand oedema, as well as upper limb lymphoscintigraphy with quantification of
	lymph transport. The mechanism for lymph drainage failure needs further investigation.
	Most of the affected individuals (particularly the adults) suffered with truncal varicose veins or
	had evidence of reflux of the great saphenous vein on duplex ultrasound examination. A true
	venous phenotype needs confirmation, but the findings support the view that genetic forms of
	lower limb lymphoedema are often associated with venous valve failure, as has been
	demonstrated with VEGFR3 and FOXC2 mutations [24,25]. Venous reflux in adults may
	contribute to lower limb but not upper limb oedema, because of increased fluid filtration from
	venous	hypertension.	Greater	gravitational	stress	(dependency)	through	higher	venous
	pressures may explain increased expression of lower limb lymphoedema, with vulnerable upper
	limb drainage relatively protected from dependency.
	Mutations in GJC2 have previously been described in the literature as the cause of autosomal
	recessively	inherited		Pelizaeus-Merzbacher-like	disease	(PMLD),	which	is	a	rare
	hypomyelinating disorder of the CNS. Uhlenberg et al [26]	noted that their heterozygous

individuals had no neurological symptoms. PMLD is a very rare condition, so it is possible that mild lymphoedema could have been present in the parents, but it seems improbable that this would have

Table 1 .

 1 Clinical, lymphoscintigraphic and venous parameters known for those patients with a mutation in GJC2.

Acknowledgements

We are grateful to all of our patients and family members who have contributed to this and related lymphoedema genetic studies. FC and KK were supported by the BHF, PO by the BSF. The resources of the Biomics Unit at SGUL were essential for the study. The authors acknowledge the financial support from the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre award to Guy's & St Thomas' NHS Foundation Trust in partnership with King's College London and King's College Hospital NHS Foundation Trust The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non-exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd and its Licensees to permit this article (if accepted) to be published in Journal of Medical Genetics and any other BMJPGL products to exploit all subsidiary rights, as set out in our licence (http://group.bmj.com/products/journals/instructions-for-authors/licence-forms).