Human MutationDATABASES

Development of NIPBL Locus-Specific DatabaseUsing LOVD: From Novel Mutations to FurtherGenotype–Phenotype Correlations in Corneliade Lange Syndrome

Jorge Oliveira,1y Cristina Dias,2y,z Egbert Redeker,3 Eurico Costa,1 Joao Silva,2 Margarida Reis Lima,2y

Johan T. den Dunnen,4 and Rosario Santos1�

1Unidade de Genetica Molecular, Centro de Genetica Medica Dr. Jacinto Magalhaes, Instituto Nacional de Saude Dr. Ricardo Jorge, Porto,

Portugal; 2Unidade de Genetica Medica, Centro de Genetica Medica Dr. Jacinto Magalhaes, Instituto Nacional de Saude Dr. Ricardo Jorge,

Porto, Portugal; 3Department of Clinical Genetics, Academic Medical Centre, University of Amsterdam, Amsterdam, The Netherlands; 4Center of

Human and Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands

Communicated by George PatrinosReceived 31 May 2010; accepted revised manuscript 16 August 2010.

Published online 7 September 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI 10.1002/humu.21352

ABSTRACT: The establishment of Locus Specific Data-bases (LSDB) is a crucial aspect for the Human Geneticsfield and one of the aims of the Human Variation Project.We report the development of a publicly accessible LSDBfor the NIPBL gene (http://www.lovd.nl/NIPBL) impli-cated in Cornelia de Lange Syndrome (CdLS). This raredisorder is characterized by developmental and growthretardation, typical facial features, limb anomalies, andmultiple organ involvement. Mutations in the NIPBLgene, the product of which is involved in control of thecohesion complex, account for over half of the patientscurrently characterized. The NIPBL LSDB adopted theLeiden Open Variation database (LOVD) software plat-form, which enables the comprehensive Web-based listingand curation of sequence variations and associatedphenotypical information. The NIPBL-LOVD databasecontains 199 unique mutations reported in 246 patients(last accessed April 2010). Information on phenotypiccharacteristics included in the database enabled furthergenotype–phenotype correlations, the most evident beingthe severe form of CdLS associated with prematuretermination codons in the NIPBL gene. In addition to theNIPBL LSDB, 50 novel mutations are described in detail,resulting from a collaborative multicenter study.Hum Mutat 31:1216–1222, 2010. & 2010 Wiley-Liss, Inc.

KEY WORDS: Cornelia de Lange Syndrome; Leiden OpenVariation Database; Locus Specific Database; NIPBL

Introduction

Cornelia de Lange Syndrome (CdLS) (CDLS1; MIM] 122470,CDLS2; MIM] 300590, CDLS3; MIM] 610759) is a rare multi-systemic disorder, characterized by a typical albeit variablephenotype, which includes developmental delay, characteristicfacial features (synophrys, high arched eyebrows, ptosis, longeyelashes, upturned nasal tip, long smooth philtrum, thin upperlip, down-turned corners of the mouth, micrognathia), pre- andpostnatal growth retardation, and a wide spectrum of upper limbabnormalities. These may range from small hands, with fifth fingerclinodactyly, to severe reduction defects such as adactyly or absentforearm. Patients frequently show hirsutism and cutis marmorata[Jackson et al., 1993]. Congenital heart defects are seen inapproximately one-third of the patients [Selicorni et al., 2009].There is a high frequency of gastrointestinal complications, namely,gastroesophageal reflux (GERD) and less frequently intestinalmalrotation or diaphragmatic hernia [Jackson et al., 1993; Klineet al., 2007]. CdLS is also associated with behavioural issues:hyperactivity, self-injurious behaviour, autism spectrum disorder,and compulsive behaviours [Oliver et al., 2008]. Other problemsinclude conductive and/or sensorineural hearing loss, ophthalmo-logic disorders, genitourinary anomalies, and cleft palate.

In 2004, experimental evidence showed that the NIPBL gene(5p13.1 [MIM] 608667]) is associated with CdLS [Krantz et al.,2004; Tonkin et al., 2004]. Mutations in the NIPBL gene have sincebeen described in up to 56% of CdLS patients [Bhuiyan et al.,2005; Gillis et al., 2004; Krantz et al., 2004; Miyake et al., 2005;Tonkin et al., 2004]. CdLS shows genetic heterogeneity, however,as a small number of patients have causal mutations in one ofthree other genes: SMC1A (Xp11.2 [MIM] 300040]), SMC3(10q25 [MIM] 606062]) [Deardorff et al., 2007; Musio et al.,2006] and PDS5B (13q12.3 [MIM] 605333]) [Zhang et al., 2009](see http://www.LOVD.nl/CDLS). All of these genes involved inCdLS are thought to play a role in sister chromatid cohesion[Dorsett and Krantz, 2009].

NIPBL encodes for delangin, the human orthologue of theDrosophila melanogaster Nipped-B and of the Saccharomyces sisterchromatid cohesion protein 2 [Krantz et al., 2004; Tonkin et al.,2004]. In Drosophila it has been shown that Nipped-B and cohesinbind to transcriptionally active regions. Nipped-B is thought to

OFFICIAL JOURNAL

www.hgvs.org

& 2010 WILEY-LISS, INC.

Additional Supporting Information may be found in the online version of this article.yThese authors contributed equally to the work.zCurrently at Department of Medical Genetics, British Columbia Women’s Hospital

and Health Centre, Vancouver, British Columbia, Canada.yCurrently at Unidade de Genetica Medica, Hospital da Boavista, Porto, Portugal.�Correspondence to: Rosario Santos, Prac-a Pedro Nunes, Unidade de Genetica

Molecular, Centro de Genetica Medica Dr. Jacinto Magalhaes, Instituto Nacional de

Saude Dr. Ricardo Jorge, no. 88, Porto, Portugal. E-mail: rosario.santos@insa.min-saude.pt

regulate the effect of cohesion on transcription by dynamiccontrol of cohesin binding, or of subunit interactions [Misulovinet al., 2008]. The human protein contains PxVxL motifs (Pro-Xaa-Val-Xaa-Leu) that directly interact with the C-terminal chromoshadow-domain of CBX5, involved in heterochromatin organiza-tion [Lechner et al., 2005]. It is involved in cohesin complexloading, mediating chromatin modifications through recruitmentof histone deacetylases [Jahnke et al., 2008]. In human mutantNIPBL cells, the binding of cohesin to promoter regions of activelyexpressed genes is reduced, suggesting a role for transcriptionaldysregulation in the pathogenesis of CdLS [Liu et al., 2009].

Somatic mutations in NIPBL (and SMC1A, SMC3, and PDS5B)have also been associated with some gastrointestinal cancers,suggesting that altered sister chromatid cohesion may be anunderlying cause of human cancer [Barber et al., 2008; Manniniet al., 2010]. Although two cases of Wilms tumor and one ofsuprasellar germinoma have been reported in patients with a CdLSphenotype [Maruiwa et al., 1988; Sugita et al., 1986], there is noevidence for an increased risk for cancer. Additionally, it is notknown whether these patients harbored a germline or a somaticmutation in one of the known CdLS genes.

The present report describes the development of gene sequencevariant databases (LSDBs) for Cornelia de Lange Syndrome(www.LOVD.nl/CDLS), specifically the NIPBL gene. For nucleo-tide numbering in this gene, which contains 47 exons spanning189 kb, we used the reference sequences NG_006987.1 (genomic)and NM_133433.3 (coding DNA). The database collates muta-tional and clinical data from 246 CdLS patients, allowing theestablishment of further genotype–phenotype correlations.

NIPBL-LOVD Development

The NIPBL LSDB was implemented using the LOVD software[Fokkema et al., 2005], adapted to include a total of 17 molecular

items and 26 clinical/patient items (example of an entry in Fig. 1).In order to provide a standardized description of the patients, theclinical items were set up using a drop-down list with predefinedvariables (Supp. Table S1). The choice and detail of the clinicalfeatures was based on their reported prevalence and relevance interms of organ and systems development, cognitive ability andprognosis [Jackson et al., 1993; Kline et al., 2007; Selicorni et al.,2009]. The NIPBL LSDB (http://www.lovd.nl/NIPBL) is nowpublically available through the Cornelia de Lange Syndromemutation database installation (http://www.lovd.nl/CDLS), whichcurrently includes other gene-specific databases related with thedisorder (SMC1A, SMC3, PDS5A and PDS5B). These databases allshare the same molecular and clinical parameters. Recently, themutational data in these LSDBs was integrated with NCBIsequence viewer and USCS genome browser, increasing theirvisibility to a wider range of data viewers/users.

Curating Procedure

Part of the work consisted in reviewing all the clinical andmolecular data of CdLS cases both published in peer-reviewedliterature, and the new variants detected in our laboratories (seeNIPBL-LOVD homepage).

The cohort of 42 CdLS patients studied in a multicentercollaborative study in Portugal had initially been classified as mild,moderate, or severe according to an algorithm based on severity ofpre- and postnatal growth retardation, severity of limb malforma-tions, microcephaly, other associated congenital anomalies (e.g.,congenital heart defect), medical complications (e.g., GERD) andfacial gestalt [Dias et al., 2008]. All patients were seen by a clinicalgeneticist according to a specifically designed clinical protocol. Thescoring system described by Kline and coworkers [2007] includesdata regarding psychomotor development, upper limb malforma-tion, other major malformations and hearing loss. As hearing loss

Figure 1. Example of a submission from NIPBL-LOVD; A: Clinical items; B: molecular items.

HUMAN MUTATION, Vol. 31, No. 11, 1216–1222, 2010 1217

is present in up to 80% of the patients [Marchisio et al., 2008] andspeech may be impaired as a consequence thereof, this scoringsystem may bias the classification toward a greater severity inchildren with hearing loss, regardless of whether it is conductive orsensorineural. We reclassified the Portuguese patients according tothe referred scoring system and, when compared with the resultsusing our initial algorithm, obtained a concordance of 95.2% (40of 42 patients). In light of this, it was decided that the NIPBL-LOVD should adopt the scoring system proposed by Kline et al.,2007 as it is widely disseminated and based on parameters that areeasy to assess in the clinic. The additional fields with clinicalfeatures in the database may provide the curator with theinformation necessary to classify the patients’ phenotype whenthis classification is not provided by the submitter.

The mutational data description was confirmed using eithersoftware developed in-house, which allows annotation of genomicsequences according to the HGVS (Human Genome VariationSociety) nomenclature [den Dunnen and Antonarakis, 2000], orwith the Web-based software Mutalyzer, to which LOVD softwareis currently also linked [Wildeman et al., 2008]. Further analysis ofsequence variations was conducted using bioinformatic toolsincluding Polyphen (http://genetics.bwh.harvard.edu/pph/) formissense mutations, and Human Splicing Finder V2.4 (http://www.umd.be/HSF/) for possible splicing mutations [Desmet et al.,2009]. NIPBL variations submitted directly to the LSDB wererechecked with these tools and discrepancies or queries wereredirected to the submitter.

New Mutations

The development of the LSDB was an opportunity to updatethe mutation spectrum of the NIPBL gene. In keeping with recentrecommendations [Cotton, 2010], efforts were made to collectdata from major groups known to be working in this field.

The database describes a total of 50 unpublished NIPBLmutations provided by the Dutch and the Portuguese groups(Table 1). In these mutation positive cases, parental DNA wasanalysed whenever available, to ascertain whether the mutationwas familial or de novo, and population screening was carried outusing at least 150 anonymous controls, in order to exclude thepolymorphic nature of single nucleotide changes.

The most frequent type of mutations were deletions (n 5 18),the majority of which predictably result in premature terminationcodons (PTC). The exception was c.3751_3753delATG, whichpredicts an in-frame single codon deletion (p.Met1251del). A totalof 10 splicing mutations were also identified. Because these werenot further characterized at the cDNA level, their effect wasinferred by bioinformatic analysis. All of these changes are locatedin the acceptor splice sites (positions –5, –1, 0) or donor splicesites (positions 0, 13, 15), thereby lowering the probability ofrecognition by the splicing machinery. Seven of the eightduplications reported induce a reading-frame shift. The other,c.7299_7301dup, predictably duplicates a single aminoacid(p.Asn2434dup) maintaining the remainder of the polypeptidesequence intact. Seven new missense mutations are also described,affecting residues that are conserved across vertebrate species.Additionally, two de novo single nucleotide substitutions(c.3574G4A and c.4422G4T) are predicted to either be missenseor to affect a donor splice site. Further studies will be necessary toclarify the effect of these two mutations. Finally, five nonsensemutations (c.133C4T, c.2422C4T, c.826C4T, c.7340T4A, andc.8377C4T), one insertion (c.2291_2292insC), and one indel(c.4766_4767delins) are also reported for the first time.

Database Content Analysis

The NIPBL-LOVD database contains 199 unique mutationsreported in 246 patients (last accessed April 2010). Mutationsdescribed include all types: deletions (27.6%, n 5 55), missense(21.1%, n 5 42), nonsense (17.3%, n 5 33), splicing (17.1%, n 5 34),duplications (13.6%, n 5 27), insertions (1.5%, n 5 3), and indels(1.5%, n 5 3). Gross genomic duplications or deletions appear to bevery rare: only one 5.2 kb deletion encompassing exons 41 to 42(c.6955–1095_726313244del) [Bhuiyan et al., 2005] and a duplica-tion of exons 11 to 22 (c.3122�?_46431?dup) [Vrouwe et al., 2007].

The majority of mutations in NIPBL have a de novo origin andonly a limited number of cases report proven parent-to-childtransmission or kindreds with two or more affected siblings[Borck et al., 2004; Gillis et al., 2004; Krantz et al., 2004; Niu et al.,2006]. Overall, only nine recurrent mutations were reported inthree or more nonrelated patients, namely, c.65–5A4G,c.2389C4T, c.2479_2480delAG, c.4606C4T, c.6653_6655delATA,c.676315G4T, c.676315G4A, c.6892C4T, and c.6893G4A(details in Supp. Table S2). Altogether, these represent 13.8% ofthe mutated alleles described in the database. By analyzing themutations’ sequence context, we observed that four of theserecurrent mutations coincide with the hypermutable CpGdinucleotides that might be affected by methylation-mediateddeamination. We further evaluated the influence of CpGs on therest of the NIPBL mutational data and found that 18 mutations(9.0% of total unique mutations) were located in CpG dinucleo-tides, seven of which were common to more than one patient. Theother major cause for mutations in NIPBL appear to becontractions (deletions) or expansions (duplications) of repetitivesequences such as short tandem repeats (e.g., c.6653_6655delATA,deleting one of three ATA repeats) or homopolymeric nucleotidestretches (e.g., c.1513dupA, extending an [A]7 stretch).

Considering the above observations, and in order to determinethe distribution of mutations within NIPBL, we plotted the totalmutation frequency for each exon and the normalized mutationfrequency according to exon size (mutation count/exon size� 100)(Fig. 2). Although there are no clear mutational hotspots, thefrequency of mutations varied within the gene, in a manner thatcould be attributed to overall exon sequence composition or theexistence of specific sequence elements. Because some gene regionsseemed to be more mutation-prone than others, and given thelarge size of the gene, the feasibility of using a more cost-effective‘‘first approach strategy’’ for NIPBL screening was evaluated. Tothis end, a meta-analysis of the NIPBL-LOVD mutational data wasconducted using the normalized mutation frequency value plottedagainst the difference between the mutation detection rate and thepercentage of the coding region (details in Supp. Tables S3, S4, andSupp. Fig. S1). The highest value (27.9%) was obtained for(mutation count/exon size� 100)Z2.8, which picks out 21 of the47 NIPBL exons (namely, 2, 3, 7, 10, 13, 15, 17, 19, 22, 26, 28–31,35, 36, 39, 40, 42, 43, and 45). This means that theoretically amutation detection rate of almost 80% could be achieved bysequencing only half of the coding sequence.

Genotype–phenotype correlations

A total of 246 patients are currently reposited in the database.Clinical data could be collected for 138 patients, 100 of which hadsufficient clinical data for a phenotypic classification of CdLS:27.0% were mild, 33.0% moderate, and 40.0% severe. In theremaining 38 patient reports the clinical data entry wasinsufficient for phenotype classification.

1218 HUMAN MUTATION, Vol. 31, No. 11, 1216–1222, 2010

Phenotypic data was correlated with the mutational data in twodistinct ways, according to (1) mutation type (missense, insertion,deletion, duplication, nonsense, or splicing) and (2) predicted effectat the protein level: (a) premature termination codons (PTC) andout of frame deletions, duplications or insertions (del/dup/ins), or(b) missense mutations and in frame del/dup/ins. Predicted splicesite mutations were excluded from this second analysis, asinformation on the phenotype at the protein level was unavailablein most reports. For the purpose of analysis of specific phenotypicfindings, only entries with information available (i.e., present or

absent) for that specific feature were included in the analysis.Entries for which the respective information was not provided, wereexcluded from the analysis of each subset (Supp. Tables S5 and S6)so as to avoid a bias generated from inclusion of false negatives.

Statistical analysis was performed using the SPSS software(version 17.0). A nonparametric pair wise comparison ofpredicted protein effect and phenotypic features was performedusing the chi-square test. The variable correlation was evaluated bythe Spearman’s correlation coefficient test and results wereconsidered statistically significant at Po0.05.

Table 1. New NIPBL Mutations Submitted in NIPBL-LOVD

Patients Id

in database Gene region Mutation� Mutation type

Predicted

protein effect Mutation origin CdLS phenotype Gender

Geographical

origin

13422 Exon 3 c.133C4T nonsense p.Arg45X unknown unknown M Denmark

13446 Intron 4 c.35813G4T spl (b) ? unknown unknown F Belgium

13424 Exon 8 c.826C4T nonsense p. Gln276X de novo unknown F Netherlands

13454 Exon 9 c.889dupC duplication p.Leu297ProfsX39 de novo unknown M Netherlands

13437 Exon 9 c.998delA deletion p.Lys333ArgfsX15 unknown unknown M Netherlands

13439 Exon 9 c.1275_1278delAACA deletion p.Thr426HisfsX54 unknown unknown F Sweden

12051 Exon 9 c.1445_1448delGAGA deletion p.Arg482AsnfsX20 de novo Moderate F Portugal

13455 Exon 10 c.1774_1787del deletion p.Thr592SerfsX2 unknown unknown F Scotland

13419 Exon 10 c.2007delT deletion p.Glu670SerfsX124 de novo unknown F Scotland

13415 Exon 10 c.2116_2117dupAA duplication p.Gly707ArgfsX88 unknown unknown M Canada

12053 Exon 10 c.2270delC deletion p.Thr757AsnfsX37 unknown Severe M Portugal

13450 Exon 10 c.2291_2292insC insertion p.Arg765X unknown unknown M Austria

12054 Exon 10 c.2422C4T nonsense p.Arg808X de novo Moderate F Portugal

13409 Exon 10 c.2479delA deletion p.Arg827GlyfsX20 de novo unknown M Netherlands

13457 Exon 10 c.2611delA deletion p.Arg871GlyfsX58 unknown unknown F Finland

13421, Exon 10 c.3117_3120delTAAA deletion p.Asn1039LysfsX4 unknown unknown F England

13452 unknown unknown M Portugal

13456 Intron 11 c.330411G4T spl (b) ? de novo unknown F Ireland

12055 Exon 13 c.3574G4A (c) spl (b)/missense ?/p.Glu1192Lys de novo Moderate F Portugal

13447 Exon 15 c.3751_3753delATG deletion p.Met1251del unknown unknown M Portugal

13410 Intron 15 c.376813A4T spl (b) ? de novo unknown F Finland

13429 Intron 16 c.3856-5del spl? ? de novo unknown M Netherlands

13405 Exon 17 c.3902T4G (c) missense p.Met1301Arg unknown Mild F Portugal

13417 Exon 17 c.4013A4G missense p.Gln1338Arg de novo unknown M Canada

13444 Exon 18 c.4202T4G missense p.Leu1401Arg unknown unknown F Canada

13416 Exon 19 c.4293delG deletion p.Gln1431HisfsX7 unknown unknown M Finland

12059 Intron 20 c.4422–1G4A spl (a) ? de novo Moderate F Portugal

13418 Exon 21 c.4422G4T spl?/missense ?/p.Arg1474Ser de novo unknown M Netherlands

13408 Exon 23 c.4766_4767delins deletion p.Gly1589ValfsX3 unknown unknown M Netherlands

TTTGTTAGGTAAGAGA insertion

13441 Exon 26 c.5051_5052delCA deletion p.Thr1684AsnfsX14 unknown unknown M Netherlands

13430 Intron 26 c.522513A4C spl (a) ? unknown unknown M England

13458 Exon 28 c.5412dupC duplication p.Ser1805GlnfsX7 de novo unknown M Netherlands

13443 Exon 29 c.5471C4T missense p.Ser1824Leu unknown unknown F Sweden

12060 Exon 30 c.5594G4C (c) missense p.Arg1865Thr de novo Moderate M Portugal

13440 Exon 30 c.5693A4G missense p.Asp1898Gly unknown unknown F Netherlands

13453 Intron 31 c.580811G4A spl (a) ? unknown unknown F England

13438 Intron 38 c.658915G4A spl (b) ? de novo unknown M Norway

13411, Exon 39 c.6697G4A missense p.Val2233Met unknown unknown M Netherlands

13413 unknown unknown F Netherlands

13406 Intron 39 c.676315G4C spl (b) ? unknown Severe M Portugal

13459 Exon 40 c.6803delG deletion p.Gly2268ValfsX7 de novo unknown M Netherlands

13427 Exon 40 c.6852delA deletion p.Lys2284AsnfsX19 unknown unknown M Netherlands

13423 Exon 43 c.7299_7301dup duplication p.Asn2434dup unknown unknown F Denmark

13425 Exon 43 c.7340T4A nonsense p.Leu2447X unknown unknown F England

13451 Exon 45 c.7788_7792delCCTGC deletion p.Phe2596LeufsX3 unknown unknown F Portugal

13414 Exon 45 c.7819dupA duplication p.Thr2607AsnfsX25 unknown unknown F England

12067 Exon 45 c.7833_7834dupAA duplication p.Arg2612LysfsX4 de novo Moderate M Portugal

13436 Exon 47 c.8301delA deletion p.Glu2768SerfsX11 unknown unknown M Netherlands

13433 Exon 47 c.8315_8318delTTTA deletion p.Ile2772ThrfsX6 unknown unknown M Canada

13426 Exon 47 c.8326dupA duplication p.Ile2776AsnfsX7 unknown unknown F Wales

12068 Exon 47 c.8364delT deletion p.Val2789PhefsX36 de novo Mild F Portugal

12069 (d), Exon 47 c.8377C4T nonsense p.Arg2793X unknown Mild M Portugal

12070 (d) unknown Mild F Portugal

Spl, splicing; (a), affects acceptor splice site (bioinformatic prediction); (b), affects donor splice site (bioinformatic prediction); (c), not detected in 300 control alleles;(d), siblings; M, male; F, female.�Nomenclature according to den Dunnen and Antonarakis [2000] reference cDNA sequence NM_133433.3.

HUMAN MUTATION, Vol. 31, No. 11, 1216–1222, 2010 1219

In general, data analysis suggests that individuals with anonsense mutation or out of frame del/dup/ins more oftenpresent a severe phenotype than those with a mutation that has aless detrimental effect on the protein (Table 2). No statisticalsignificance (P 5 0.052) was found when comparing groupsdivided according to mutation type. However, when correlatingphenotype with predicted mutation effect at the protein level, aclear statistical significance (P 5 0.005) was found. Truncatingmutations have previously been associated with a more severeclinical phenotype, but the analysis had been restricted tomissense versus all other mutation types [Gillis et al., 2004].

In addition to this correlation using the overall phenotypeclassification, genotype–phenotype correlation was attempted forspecific phenotypical traits, namely, upper limb defects, intrau-terine growth retardation (IUGR), postnatal growth retardation,craniofacial cleft, congenital heart disease (CHD), genital andurinary anomalies, and GERD (Supp. Tables S5 and S6).

Overall, 35.0% of individuals with NIPBL mutations hadreduction defects of the upper limbs (Supp. Table S5), 36.8% hadsmall hands only, and 28.2% had no abnormality of the upperlimbs. The frequency of severe reduction defects involving the

forearm was 6.8%. A statistically significant difference wasobtained when comparing the extent of upper limb reductionboth with mutation type (P 5 0.042) and with the predicted effecton protein (P 5 0.029).

No statistically significant difference was found for craniofacialclefts, present in 17.7% (11/62) of reported individuals, all withcleft palate. Similarly, for the remaining specific phenotypic traits,there was no evidence of correlation with either mutation type orpredicted polypeptide effect (Supp. Table S6).

CHD was reported in 49.3% of cases, although the type was notspecified in every case. Reported defects included ventricularseptal defect (n 5 3), atrial septal defect (n 5 3), pulmonic stenosis(n 5 3), tetralogy of Fallot (n 5 2), mitral valve prolapse (n 5 1),and supravalvular aortic stenosis (n 5 1). This frequency of CHDis greater than previously estimated [Selicorni et al., 2009].

Among the 100 patients that could be classified, most presentthe severe phenotype. This may be due to sample bias, becausepatients with a severe phenotype are more likely to come tomedical attention and/or to be selected for molecular testing. Onthe other hand, it is possible that a deficit in delangin could bemore compromising than that affecting other gene productsinvolved in CdLS. Indeed, mutations in the SMC1A gene havebeen associated with the milder end of the CdLS phenotypicspectrum [Mannini et al., 2010].

Concluding Remarks

The development and maintenance of LSDBs is currently animportant effort in the human genetics field, considering theenormous amount of data that is generated on a daily basis, bothof disease-causing mutations as well as unclassified variants. Thesegenetic and clinical driven databases allow clinicians, geneticistsand investigators to access high-quality updated information, andwill ultimately ensure a consistent interpretation of the data. TheHuman Variome Project recognized the need to collect andannotate such data in a standardized and unifying manner, withthe ultimate goal of health care improvement [Cotton et al., 2009;Kaput et al., 2009].

Considering the genetics of CdLS, the authors decided toestablish LSDBs for this syndrome, beginning with NIPBL, whichis the current candidate gene responsible for most cases of CdLS.In developing this database, published recommendations for‘‘ideal’’ curation of LSDBs were taken into account [Cotton et al.,

Figure 2. NIPBL-LOVD database content analysis. Distribution of mutations and frequency in the NIPBL gene.

Table 2. Genotype–Phenotype Correlation Analysis UsingNIPBL-LOVD Data

Phenotype

CdLS

mild

CdLS

moderate

CdLS

severe Total

P

(chi-square test)

Genotype– phenotype correlation I

Mutation type

Deletion 5 7 13 25

Duplication 1 4 1 6

Insertion 0 0 1 1 0.052

Missense 10 7 5 22

Nonsense 2 8 14 24

Splicing 9 7 6 22

Total 27 33 40 100

Genotype– phenotype correlation II

Protein effect

Missense/In frame del/dup/ins 12 10 7 29 (37.2%) 0.005

PTC/Out of frame del/dup/ins 6 16 27 49 (62.8%)

Total 18 26 34 78

PTC, mutation induces a premature termination codon; del/dup/ins, deletion,duplication, or insertion. Chi-square test, Pearson chi-square. P-value significant o0.05.

1220 HUMAN MUTATION, Vol. 31, No. 11, 1216–1222, 2010

2008], namely, (1) review and compilation of all mutationspublished in the literature, (2) mutation collection extended toother research groups/diagnostic laboratories, (3) LSDB main-tenance by a team of curators with complementary expertise(clinical and molecular geneticists), (4) use of bioinformaticmodules that ensure the correct annotation of molecular data andaid data interpretation (some modules packaged with LOVD). Themost challenging of these was the collection of data from otherdiagnostic and research groups. With the LSDB now up andrunning, we have contacted specialists that have published CdLSvariants before and hope they will support our initiative, sharetheir data, and help to keep the gene variant databases up to date.

LSDBs with information on phenotypical characteristics mayprovide further insight into the phenotypic spectrum of thedisorders, which is useful for clinicians to direct screening ofadditional anomalies on diagnosis and anticipatory care. Analysisof the information in the NIPBL-LOVD database revealed that,although the mutation type is correlated with the overall severityof phenotype (mild, moderate, or severe), this is significant forupper limb defects but not for other specific anomalies orcomplications such as GERD. Also of note is that the frequency ofcongenital heart defects is greater than previously reported, whichshould prompt clinicians to search for these anomalies in patients.It is expected that as the amount of data increases, so too will thestrength of this analysis.

An important aspect of LSDBs is that they assist in assessing thepathogenicity of unclassified variants (UVs). This is exemplifiedby the variant c.6109�3T4C previously thought to be patho-genic, according to two independent reports in the literature[Gillis et al., 2004; Selicorni et al., 2009], although no familial orfunctional studies were reported to substantiate its pathogenicnature. We have now detected this variant in a patient and also inhis healthy mother. The bioinformatic tool Human Splice Finderpredicts an increase in the acceptor splice site score (wild type:83.33; mutant: 91.01), which further supports the low likelihoodof this variant being pathogenic. Further studies would contributetoward clarifying the nature of this variant. In fact, this applies tothe majority of splice site mutations reported.

Our analysis of the NIPBL-LOVD also illustrates how LSDBscan be useful in establishing targeted testing. Current data suggeststhat by screening half of the coding sequence of the NIPBL gene, itis possible to achieve a diagnostic yield of around 80%.

As shown, in addition to contributing toward finding thesignificance of rare sequence variants, the standardized collection ofdisease-specific information provides the scientific community witha useful tool for genotype–phenotype correlations. LOVD softwareis flexible and can be easily customized to include distinct molecularand phenotypical items. These items can also be shared by distinctLSBDs associated in the same syndrome or group of diseases, inwhat may be defined as a disease-centered LOVD installation. Asthe same patient may present one or several variations in differentgenes, these can be linked by a common identifier (patient internalID). This type of database structure allows further data integration,and it is expected that LSDBs be developed for additional causalgenes and integrated in this CdLS-centered installation.

Acknowledgments

The authors thank the clinical geneticists that contributed with patient

information: Marcia Martins, Ana Maria Fortuna, Ana Berta Sousa, Teresa

Taylor Kay, Heloısa Santos, Ana Medeira, Isabel Cordeiro, Teresa Lourenc-o,

and Luıs Nunes. We thank all patients and families, and the patient

association ‘‘Rarıssimas’’ for their collaboration.

References

Barber TD, McManus K, Yuen KW, Reis M, Parmigiani G, Shen D, Barrett I, Nouhi Y,

Spencer F, Markowitz S, Velculescu VE, Kinzler KW, Vogelstein B, Lengauer C,

Hieter P. 2008. Chromatid cohesion defects may underlie chromosome

instability in human colorectal cancers. Proc Natl Acad Sci USA 105:3443–3448.

Bhuiyan ZA, Klein M, Hammond P, van Haeringen A, Mannens MM, Van

Berckelaer-Onnes I, Hennekam RC. 2005. Genotype–phenotype correlations of

39 patients with Cornelia de Lange syndrome: the Dutch experience. J Med

Genet 43:568–575.

Borck G, Redon R, Sanlaville D, Rio M, Prieur M, Lyonnet S, Vekemans M,

Carter NP, Munnich A, Colleaux L, Cormier-Daire V. 2004. NIPBL mutations

and genetic heterogeneity in Cornelia de Lange syndrome. J Med Genet 41:e128.

Cotton RGH. 2010. Database overkill. Hum Mutat 31:1.

Cotton RGH, Al Aqeel AI, Al-Mulla F, Carrera P, Claustres M, Ekong R, Hyland VJ,

Macrae FA, Marafie MJ, Paalman MH, Patrinos GP, Qi M, Ramesar RS, Scott RJ,

Sijmons RH, Sobrido MJ, Vihinen M; members of the Human Variome Project

Data Collection from Clinics, Data Collection from Laboratories and

Publication, Credit and Incentives Working Groups. 2009. Capturing all

disease-causing mutations for clinical and research use: toward an effortless

system for the Human Variome Project. Genet Med 11:843–849.

Cotton RGH, Auerbach AD, Beckmann JS, Blumenfeld OO, Brookes AJ, Brown AF,

Carrera P, Cox DW, Gottlieb BR, Greenblatt MS, Hilbert P, Lehvaslaiho H,

Liang P, Marsh S, Nebert DW, Povey S, Rossetti S, Scriver CR, Summar M,

Tolan DR, Verma IC, Vihinen M, den Dunnen JT. 2008. Recommendations for

locus-specific databases and their curation. Hum Mutat 29:2–5.

Deardorff MA, Kaur M, Yaeger D, Rampuria A, Korolev S, Pie J, Gil-Rodrıguez C,

Arnedo M, Loeys B, Kline AD, Wilson M, Lillquist K, Siu V, Ramos FJ, Musio A,

Jackson LS, Dorsett D, Krantz ID. 2007. Mutations in cohesin complex members

SMC3 and SMC1A cause a mild variant of Cornelia de Lange syndrome with

predominant mental retardation. Am J Hum Genet 80:485–494.

den Dunnen JT, Antonarakis SE. 2000. Mutation nomenclature extensions and

suggestions to describe complex mutations: a discussion. Hum Mutat 15:7–12.

Desmet FO, Hamroun D, Lalande M, Collod-Beroud G, Claustres M, Beroud C.

2009. Human Splicing Finder: an online bioinformatics tool to predict splicing

signals. Nucleic Acids Res 37:e67.

Dias C, Costa E, Oliveira J, Silva J, Martins M, Fortuna AM, Sousa AB, Basto JP,

Soares-Silva I, Kay T, Santos H, Medeira A, Cordeiro I, Lourenc-o T, Nunes L,

Santos R, Reis-Lima M. 2008. Clinical characterization and NIPBL mutation

analysis of 42 Portuguese patients with Cornelia de Lange Syndrome. Eur J Hum

Genet 16(Suppl 2):97 (P01.266).

Dorsett D, Krantz ID. 2009. On the molecular etiology of Cornelia de Lange

Syndrome. Ann NY Acad Sci 1151:22–37.

Fokkema IF, den Dunnen JT, Taschner PE. 2005. LOVD: easy creation of a locus-

specific sequence variation database using an ‘‘LSDB-in-a-box’’ approach. Hum

Mutat 26:63–68.

Gillis LA, McCallum J, Kaur M, DeScipio C, Yaeger D, Mariani A, Kline AD, Li HH,

Devoto M, Jackson LG, Krantz ID. 2004. NIPBL mutational analysis in 120

individuals with Cornelia de Lange syndrome and evaluation of genotype–

phenotype correlations. Am J Hum Genet 75:610–623.

Jackson L, Kline AD, Barr MA, Koch S. 1993. de Lange syndrome: a clinical review of

310 individuals. Am J Med Genet 47:940–946.

Jahnke P, Xu W, Wulling M, Albrecht M, Gabriel H, Gillessen-Kaesbach G, Kaiser FJ.

2008. The cohesin loading factor NIPBL recruits histone deacetylases to mediate

local chromatin modifications. Nucleic Acids Res 36:6450–6458.

Kaput J, Cotton RG, Hardman L, Watson M, Al Aqeel AI, Al-Aama JY, Al-Mulla F,

Alonso S, Aretz S, Auerbach AD, Bapat B, Bernstein IT, Bhak J, Bleoo SL,

Blocker H, Brenner SE, Burn J, Bustamante M, Calzone R, Cambon-Thomsen A,

Cargill M, Carrera P, Cavedon L, Cho YS, Chung YJ, Claustres M, Cutting G,

Dalgleish R, den Dunnen JT, Dıaz C, Dobrowolski S, dos Santos MR, Ekong R,

Flanagan SB, Flicek P, Furukawa Y, Genuardi M, Ghang H, Golubenko MV,

Greenblatt MS, Hamosh A, Hancock JM, Hardison R, Harrison TM, Hoffmann R,

Horaitis R, Howard HJ, Barash CI, Izagirre N, Jung J, Kojima T, Laradi S, Lee YS,

Lee JY, Gil-da-Silva-Lopes VL, Macrae FA, Maglott D, Marafie MJ, Marsh SG,

Matsubara Y, Messiaen LM, Moslein G, Netea MG, Norton ML, Oefner PJ,

Oetting WS, O’Leary JC, de Ramirez AM, Paalman MH, Parboosingh J,

Patrinos GP, Perozzi G, Phillips IR, Povey S, Prasad S, Qi M, Quin DJ,

Ramesar RS, Richards CS, Savige J, Scheible DG, Scott RJ, Seminara D,

Shephard EA, Sijmons RH, Smith TD, Sobrido MJ, Tanaka T, Tavtigian SV,

Taylor GR, Teague J, Topel T, Ullman-Cullere M, Utsunomiya J, van Kranen HJ,

Vihinen M, Webb E, Weber TK, Yeager M, Yeom YI, Yim SH, Yoo HS;

Contributors to the Human Variome Project Planning Meeting. 2009. Planning

the Human Variome Project: The Spain Report. Hum Mutat 30:496–510.

Kline AD, Krantz ID, Sommer A, Kliewer M, Jackson LG, FitzPatrick DR, Levin AV,

Selicorni A. 2007. Cornelia de Lange Syndrome: Clinical review, diagnostic and

scoring systems, and anticipatory guidance. Am J Hum Genet 143:1287–1296.

HUMAN MUTATION, Vol. 31, No. 11, 1216–1222, 2010 1221

Krantz ID, McCallum J, DeScipio C, Kaur M, Gillis LA, Yaeger D, Jukofsky L,

Wasserman N, Bottani A, Morris CA, Nowaczyk MJ, Toriello H, Bamshad MJ,

Carey JC, Rappaport E, Kawauchi S, Lander AD, Calof AL, Li HH, Devoto M,

Jackson LG. 2004. Cornelia de Lange syndrome is caused by mutations in NIPBL,

the human homolog of the Drosophila Nipped-B gene. Nat Genet 36:631–635.

Lechner MS, Schultz DC, Negorev D, Maul GG, Rauscher III FJ. 2005. The

mammalian heterochromatin protein 1 binds diverse nuclear proteins through a

common motif that targets the chromoshadow domain. Biochem Biophys Res

Commun 331:929–937.

Liu J, Zhang Z, Bando M, Itoh T, Deardorff MA, Clark D, Kaur M, Tandy S, Kondoh T,

Rappaport E, Spinner NB, Vega H, Jackson LG, Shirahige K, Krantz ID. 2009.

Transcriptional dysregulation in NIPBL and cohesin mutant human cells. PLoS

Biol 7:e1000119.

Mannini L, Liu J, Krantz ID, Musio A. 2010. Spectrum and consequences of SMC1A

mutations: the unexpected involvement of a core component of cohesin in

human disease. Hum Mutat 31:5–10.

Marchisio P, Selicorni A, Pignataro L, Milani D, Baggi E, Lambertini L, Dusi E,

Villa L, Capaccio P, Cerutti M, Esposito S, Principi N. 2008. Otitis media with

effusion and hearing loss in children with Cornelia de Lange syndrome. Am J

Med Genet A 146A:426–432.

Maruiwa M, Nakamura Y, Motomura K, Murakami T, Kojiro M, Kato M, Morimatsu M,

Fukuda S, Hashimoto T. 1988. Cornelia de Lange syndrome associated with

Wilms’ tumour and infantile haemangioendothelioma of the liver: report of two

autopsy cases. Virchows Arch A Pathol Anat Histopathol 413:463–468.

Misulovin Z, Schwartz YB, Li XY, Kahn TG, Gause M, MacArthur S, Fay JC,

Eisen MB, Pirrotta V, Biggin MD, Dorsett D. 2008. Association of cohesin and

Nipped-B with transcriptionally active regions of the Drosophila melanogaster

genome. Chromosoma 117:89–102.

Miyake N, Visser R, Kinoshita A, Yoshiura K, Niikawa N, Kondoh T, Matsumoto N,

Harada N, Okamoto N, Sonoda T, Naritomi K, Kaname T, Chinen Y, Tonoki H,

Kurosawa K. 2005. Four Novel NIPBL mutations in Japanese patients with

Cornelia de Lange Syndrome. Am J Med Genet 135:103–105.

Musio A, Selicorni A, Focarelli ML, Gervasini C, Milani D, Russo S, Vezzoni P,

Larizza L. 2006. X-linked Cornelia de Lange syndrome owing to SMC1L1

mutations. Nat Genet 38:528–530.

Niu DM, Huang JY, Li HY, Liu KM, Wang ST, Chen YJ, Udaka T, Izumi K, Kosaki K.

2006. Paternal gonadal mosaicism of NIPBL mutation in a father of siblings with

Cornelia de Lange syndrome. Prenat Diagn 26:1054–1057.

Oliver C, Arron K, Sloneem J, Hall S. 2008. Behavioural phenotype of Cornelia de

Lange syndrome: case–control study. Br J Psychiatry 193:466–470.

Selicorni A, Colli AM, Passarini A, Milani D, Cereda A, Cerutti M, Maitz S, Alloni V,

Salvini L, Galli MA, Ghiglia S, Salice P, Danzi GB. 2009. Analysis of congenital

heart defects in 87 consecutive patients with Brachmann-de Lange syndrome.

Am J Med Genet A 149A:1268–1272.

Sugita K, Izumi T, Yamaguchi K, Fukuyama Y, Sato A, Kajita A. 1986. Cornelia de

Lange syndrome associated with a suprasellar germinoma. Brain Dev 8:541–546.

Tonkin ET, Wang TJ, Lisgo S, Bamshad MJ, Strachan T. 2004. NIPBL, encoding a

homolog of fungal Scc2-type sister chromatid cohesion proteins and fly

Nipped-B, is mutated in Cornelia de Lange syndrome. Nat Genet 36:636–641.

Vrouwe MG, Elghalbzouri-Maghrani E, Meijers M, Schouten P, Godthelp BC,

Bhuiyan ZA, Redeker EJ, Mannens MM, Mullenders LH, Pastink A, Darroudi F.

2007. Increased DNA damage sensitivity of Cornelia de Lange syndrome cells:

evidence for impaired recombinational repair. Hum Mol Genet 16:1478–1487.

Wildeman M, van Ophuizen E, den Dunnen JT, Taschner PE. 2008. Improving

sequence variant descriptions in mutation databases and literature using the

Mutalyzer sequence variation nomenclature checker. Hum Mutat 29:6–13.

Zhang B, Chang J, Fu M, Huang J, Kashyap R, Salavaggione E, Jain S, Kulkarni S,

Deardorff MA, Uzielli ML, Dorsett D, Beebe DC, Jay PY, Heuckeroth RO, Krantz I,

Milbrandt J. 2009. Dosage effects of cohesin regulatory factor PDS5 on

mammalian development: implications for cohesinopathies. PLoS One 4:e5232.

1222 HUMAN MUTATION, Vol. 31, No. 11, 1216–1222, 2010