We thank the Human Gene Mutation Database (HGMD) team for critically analysing our results, and highlighting some potential problems with our analysis.
Many of the criticisms raised by Stenson et al. relate to mutations that were outside the terms of reference of the study. For instance, a major criticism raised by Stenson et al. was that the review was not comprehensive viz we negle...
We thank the Human Gene Mutation Database (HGMD) team for critically analysing our results, and highlighting some potential problems with our analysis.
Many of the criticisms raised by Stenson et al. relate to mutations that were outside the terms of reference of the study. For instance, a major criticism raised by Stenson et al. was that the review was not comprehensive viz we neglected to compare all categories of mutations. We limited our comparison to single-base-mutations, as it was found too difficult to reliably text-mine other mutation types from OMIM. This could be viewed as indirect discrimination against HGMD but these mutations do represent the majority of characterized mutations in the database and thus represent a reasonable variable to quantify.
We concluded that both OMIM and HGMD were the most comprehensive, but differences between them, including missing genes, highlighted the importance of using both resources when searching for information on a gene.
Another criticism was our failure to distinguish between somatic and heritable mutations but nor did we claim to do so. Both are associated with disease. Also, it is not clear why HGMD does not include mitochondrial mutations, as these are inherited.
Claim 1 - 143 genes are present in OMIM but have no corresponding HGMD entry.
Of the 143 genes identified as not having single-base mutations in HGMD although they are present in OMIM:
30% of these genes were missing from HGMD because the database was not up-to-date.
Another 45% were excluded from HGMD because they did not fit HGMD's criteria for inclusion (mitochondrial, somatic, low quality).
Although CD2AP is listed in HGMD it does not have any single base mutations and therefore was fairly counted. Presumably this is the case for the other 9% listed in this category.
The remaining 14% deserves further scrutiny. A genuine error did arise with the 12 genes mentioned that included FUZ. This error arose because many genes in OMIM and HGMD do not follow the HGNC official gene names. In our attempt to ensure that we compared the same gene from OMIM and HGMD, we converted all genes to their HGNC gene name, where available. Unfortunately, for a few cases, genes were assigned the wrong HGNC name. An example is the FUZ gene highlighted by Stenson et al. as having no mutations. This was a problem originating from OMIM where the gene described was not found to be a standard name, but a non-unique alias - FY, which is used for two different genes. FY was converted to the wrong HGNC name - FUZ, rather than the correct gene - DARC. This highlights a further problem in the general mutation databases and the importance that datasets adhere to the HGNC to prevent confusion.
The remaining eight genes, which included GPT, are listed as normal polymorphic variants. These are legitimately excluded from HGMD which specifically addresses disease but included in OMIM which has wider terms of reference "a catalog of human genes and genetic disorders". In the context of the purpose of our study which focused on disease, it is fair to call their inclusion into question.
Claim 2 - 226 genes in OMIM contain more mutation entries than HGMD.
Of the 83 genes listed by HGMD:
34% are indeed missing or were added to HGMD after our analysis and were fairly counted.
28% contained additional somatic allelic variants - we did not distinguish between somatic and heritable mutations in our study.
21% have an equal number or fewer mutations than HGMD - this is only true if you include all mutation types rather than just single-base mutations.
This leaves 18% that contained additional polymorphic variants, haplotypes or non-disease associated variants - we agree that it was probably not fair to include these.
Claim 3 - Many mutations are missing from HGMD that were published in the journal Human Mutation.
Stenson et al. claim that the data presented in Supplementary Table 2 is "highly misleading" and that "HGMD is not missing any of the mutations that the authors claim." We have (yet again) performed searches in the public version of HGMD for the variations listed in Supplementary Table 2 from issues 25(5) - 27(12) of Human Mutation and stand by our original assertion that many mutations are missing from the public version of HGMD.
While the mutations under examination may very well have been entered into HGMD Professional within "1-2 of their publication in the Human Mutation issue cited in the table" as Stenson et al. claim, due to the delayed release of HGMD to non-subscribers, these mutations are not available in the public version, the specific database release our study sought to examine.
Stenson et al. go on to claim that "Several mutations had already been described in the literature prior to their publication as 'novel' in Human Mutation (e.g. PAX6 1410delC)." We note that the source of the PAX6 1410delC mutation (Sale et al. 2004) claims it as a novel mutation, and our inclusion of it, rather than counting against our study, could be seen as an indicator of the inaccuracies of variation databases, as non-novel mutations are being, not only mislabelled as novel, but published as such.
Finally, Stenson et al. note that we included "many neutral and somatic variants." As we outlined above, we never claimed to distinguish between somatic and heritable mutations.
As we noted in our paper, it is not always clear if a particular mutation is included in HGMD due to gene name changes between publications and HGMD, and HGMD’s use of non-standard nomenclature. In these cases, we have endeavoured to give HGMD the benefit of the doubt.
Claim 4 - R158Q in PAH is in error.
We thank Stenson et al. for pointing out the error in the electronic version of our manuscript regarding R158Q in PAH, we have now updated the main manuscript. The Dworniczak et al. (1989) article reports a G>A base change gives rise to R158E, but it gives rise to R158Q. Both OMIM and HGMD had rectified this error in their databases, but there is no annotation to indicate the correction. The original source, which lacks a published correction is cited as the definitive reference. This error has been corrected in our manuscript but it does highlight the need for detailed annotation of mutations eg conflicting reports.
Claim 5 - HGMD is missing two specific genes (COL9A1 and PTCH2)
& Claim 6 - Patchy coverage of gene and mutation data in HGMD.
Again, the use of single-base mutations only is a fair assessment as they do make up the majority of HGMD. The purpose of our study was to gauge what data is currently available and HGMD actually did well in comparison to the other databases.
Claim 7 - The authors claim no competing interests.
Competing interests usually refers to commercial interests. The interest of "several of the authors" is not to set up "from scratch a new and all embracing human variation/mutation databases". The aim is a complete collection of variation, and their phenotypes so that they can be curated expertly in locus specific databases that are public and which can be harvested/sent to comprehensive databases such as HGMD and those at NCBI, EBI and UCSC. We are pleased to say that a consortium of members of HGVS (www.hgvs.org) has been responsible for hundreds of LSDBs being created, being publicly available and made use of by HGMD and this effort will continue also under the banner of the Human Variome Project (www.humanvariomeproject.org).
In conclusion, we congratulate the curators of HGMD and OMIM for providing two such crucial resources for inherited disease diagnostics and research. Our study raised a number of explicable problems outlined by Stenson et al., many of which highlight the problems of the mutation databasing field viz: Non use of standard nomenclature, non coverage of all types of variation, lack of annotation of corrections and the need for public and private versions of HGMD due to funding strictures.
References:
1. Sale MM, Craig JE et al. Broad phenotypic variability in a single pedigree with a novel 1410delC mutation in the PST domain of the PAX6 gene, Human Mutation 2004;20:322
2. Dworniczak B, Aulehla-Scholz C and Horst J. Phenylketonuria: detection of a frequent haplotype 4 allele mutation. Hum Genet 1989;84:95-96.
In their interesting manuscript, Tomita-Mitchell and colleagues present four novel GATA4 sequence variations as pathogenic substrates for congenital heart disease (CHD) in humans[1]. CHD are the most common birth defect and affect almost 1% of all newborns. Since surgical approaches have substantially improved over the last decades, the number of grown ups with CHD (GUCH) is growing continuously. This fact dema...
In their interesting manuscript, Tomita-Mitchell and colleagues present four novel GATA4 sequence variations as pathogenic substrates for congenital heart disease (CHD) in humans[1]. CHD are the most common birth defect and affect almost 1% of all newborns. Since surgical approaches have substantially improved over the last decades, the number of grown ups with CHD (GUCH) is growing continuously. This fact demands better insights into genetics and heredity of CHD.
The authors identified a variety of synonymous variants with a potential impact on translational kinetics of GATA4. Interestingly, all eighteen CHD associated synonymous sequence variants were exclusively found in patients with septal or conotruncal defects (excluding D-TGA), which led to the conclusion that the genetic aetiology of D-TGA may be different from other conotruncal defects. We agree that there is growing evidence about functional consequences of “silent” sequence variations in cardiac diseases. Recently, mRNA analysis of plakophilin-2 in a patient with a congenital arrhythmogenic cardiac disease revealed a cryptic splice site induced by a variant, which was predicted to be translationally silent [2]. We also report the GATA4 C274C variant in two patients with isolated secundum ASDII [3] supporting the authors’ conclusion of an association of
prevalent synonymous variants with congenital septal defects. Yet, functional studies are needed to further investigate this important issue.
As mentioned above Tomita-Mitchell et al. present four CHD associated GATA4 mutations [1]. The large screening population allows the authors to draw conclusion about an overall prevalence of GATA4 mutations among patients with sporadic CHD. When combining results from previous sequencing approaches the prevalence of GATA4 mutations ranges among 0.4% (2 out of 482) in patients with sporadic CHD [3,4,5]. Thus, the overall rarity of CHD associated GATA4 mutations is reinforced by Tomita-Mitchell et al. who report four mutations among 628 subjects with sporadic CHD
(0.6%)[1]. Yet, the A411V variant appears to our knowledge to be the first GATA4 mutation in a patient with isolated ventricular septal defect. We have also identified the A411V mutation in a female patient with cribriform ASDII and partial anomalous pulmonary venous return (PAPVR)[3]. A secundum ASD of cribriform type was previously described as a remarkable phenotype in a patient with a secundum ASD due to a mutation in NKX2.5 [6]. Therefore, one may assume that cribriform atrial septal defects are more excessively associated with transcription factor mutations than other
forms of ASDII and patients with this specific phenotype may constitute interesting screening candidates. Thorough assessment of minor and more subtle clinical features may thus help to find common phenotypes in patients with a genetic CHD. That is why we do regret the lack of any medical features of the index patients and affected relatives in the paper of Tomita-Mitchell et al [1]. Information about specific phenotypes of mutation carriers is indispensable for dealing with the future challenges
of GUCH patients. We believe that the vast heterogeneity of genetics and CHD demands systematic and detailed phenomic approaches, which may allow an identification of common clinical features among patients with genetic CHD. This may alleviate the identification and genetic counselling of
patients with hereditary CHD.
References:
1 Tomita-Mitchell A, Maslen CL, Morris CD, Garg V, Goldmuntz E. GATA4 sequence variants in patients with congenital heart disease.J Med Genet. 2007 Dec;44(12):779-783
2 Awad MM, Dalal D, Tichnell C, James C, Tucker A, Abraham T, Spevak PJ, Calkins H, Judge DP. 2006. Recessive arrhythmogenic right ventricular dysplasia due to novel cryptic splice mutation in PKP2. Hum Mutat 27:1157.
3 Posch MG, Perrot A, Schmitt K, Mittelhaus S, Esenwein EM, Stiller B, Geier C, Dietz R, Gessner R, Ozcelik C, Berger F Mutations in GATA4, NKX2.5, CRELD1 and BMP4 are infrequently found in patients with congenital
cardiac septal defects Am J Med Genet Part A in press
4 Nemer G, Fadlalah F, Usta J, Nemer M, Dbaibo G, Obeid M, Bitar F. 2006. A novel mutation in the GATA4 gene in patients with Tetralogy of Fallot. Hum Mutat 27:293-294.
5 Schluterman MK, Krysiak AE, Kathiriya IS, Abate N, Chandalia M, Srivastava D, Garg V. 2007. Screening and biochemical analysis of GATA4 sequence variations identified in patients with congenital heart disease. Am J Med Genet A 143:817-823.
6 Hirayama-Yamada K, Kamisago M, Akimoto K, Aotsuka H, Nakamura Y, Tomita H, Furutani M, Imamura S, Takao A, Nakazawa M, Matsuoka R. 2005. Phenotypes with GATA4 or NKX2.5 mutations in familial atrial septal defect. Am J Med Genet A 135:47-52.
We read with interest the study by Antoniou et al, [1] in which they
compared a number of the described methods for assessing the probability
that a BRCA1 or BRCA2 gene mutation is the cause of a family history of
breast or ovarian cancer in 1934 families of non-Ashkenazi Jewish origin.
In this study a number of methods, particularly the BOADICEA model,
demonstrated a high degree of disc...
We read with interest the study by Antoniou et al, [1] in which they
compared a number of the described methods for assessing the probability
that a BRCA1 or BRCA2 gene mutation is the cause of a family history of
breast or ovarian cancer in 1934 families of non-Ashkenazi Jewish origin.
In this study a number of methods, particularly the BOADICEA model,
demonstrated a high degree of discrimination between families who are
mutation positive and negative on current testing. We believe these data
fully support the authors conclusion that “More systematic use of these
models in clinic… would have the advantage of ensuring equity of
access to genetic testing as well as making the management decision making
process clearer and more explicit.” In their accompanying commentary,
Hopper et al [2] go further and suggest that the accuracy of the best
methods, such as BOADICEA, warrant them taking the prime position in the
decision-making process when assessing which families should go forward
for clinical BRCA1 and BRCA2 mutation testing. When it comes to clinical
application, however it appears that the picture revealed by these data is
more complex and show that the assessment of families needs to occur
within a framework of clinical judgement if the resources available for
genetic testing are to be converted into the greatest possible health
benefits for these families.
In the study by Antoniou et al, the majority of patients who had been
tested through a clinical service had a pre-test probability of detecting
a mutation below the 20% threshold suggested in the UK NICE guidelines [3]
(as assessed by any of the methods used; BOADICEA, BRCAPRO, IBIS, the
Myriad data, and the Manchester Score). Hopper et al., note one reason
for this is that the NICE recommendations were only introduced in 2004,
but a more fundamental reason is that there remains no accepted “gold
standard” for establishing the pre-test risk and indeed the NICE
guidelines do not prescribe a specific model for this purpose. In the past
the assessment of mutation risk was guided by clinical criteria believed
to equate to a high level of risk. However, while these criteria proved
sensitive, they suffered from a lack of specificity and over-testing of
low risk families was common. More recently, more accurate probabilistic
methods [4,5], empirical data [6] and clinical scoring [7] systems have
become available that improve case selection, but although all the methods
identify a low risk group of families to be excluded from testing, they do
not necessarily agree on which families belong in that group. In a cohort
of 209 non-Ashkenazi families who underwent BRCA1 and BRCA2 testing in
Victoria [8] we found that concordance between the assessment methods
examined (which did not include BOADICEA) was low. Overall complete
agreement as to which families should be tested (at the 10% threshold used
in Victoria) as assessed by BRCAPRO, the Myriad tables, and the Manchester
Score (combined score of 15) was only 44%. In low to moderate risk
families (BRCAPRO score <30%) the agreement fell to only 12%. We would
be interested in the equivalent levels of concordance between the methods
in the Antoniou study, but our data suggest that despite the appearance of
objectivity, the definition of a low risk family remains highly dependent
on exactly which assessment model is used.
In their paper Antoniou et al., report good accuracy for a number of
methods in discriminating families across a range of pre-test
probabilities – the majority of positive tests occurring in the high risk
families as expected. In clinical practice, however, it is rare for the
decision to test a high risk family to present a clinical challenge.
Instead, further assistance is required with the assessment of low to
moderate risk families who represent a sizeable majority of the referrals
to familial cancer centres and the bulk of newly diagnosed breast cancer
patients. There is evidence in this paper that the methods described are
also less effective when assessing low to moderate risk families. For
families around the 20% threshold for testing (i.e. 10-30%), the odds
ratio that a family with a gene mutation would be selected for testing by
any of the methods ranged from 0.28 to 1.35 and in no case was this
significantly better than the likelihood that would be expected by chance
alone (OR = 1) [Table 1.]. Considered from this point of view, the
assessment methods are effective in reducing the overall number of
families who would be offered testing in this low-moderate risk group, but
this short-term economic benefit would only be converted into improved
long-term clinical outcomes and economic benefits (i.e. more women from
mutation positive families receiving the right specialist advice and
management) if the resources saved could be directed at finding other
families who are more likely to be mutation positive to take their place.
We believe that the reported performance in the low-moderate risk
groups cannot be interpreted to mean that there is no room for clinical
judgment in the decision-making process. Instead these data show that a
wider consideration of an individual or families specific circumstances is
essential when interpreting the output of these methods. Improved
discrimination amongst the large number of families with low-moderate risk
based on family history requires further development of the models to
incorporate other sources of predictive information such as pathological
characteristics and tumour immuno-phenotyping [8,9,10]. Currently this
information forms a key component of clinician’s judgement. In addition,
where resources are scarce, a clinician assessing a family lying close to
the testing threshold must consider more than small differences in pre-
test probability, but examine the potential clinical impact of finding a
mutation as a whole, for the individual as well as their families, when
determining how that resource can be used to achieve the best health
outcomes. Although it is possible to imagine an algorithm that was able to
account for economic benefits or potential life years saved within a given
pedigree based on the outcome of testing, this clearly remains some way
off and these considerations also remain within the sphere of clinical
judgement.
When we consider the wider context of breast cancer screening and
management it is clear that genetic testing represents a very modest cost
in comparison to life-long screening programs, risk-reducing interventions
or the management of breast cancer. Consequently, it is far from clear
that a strategy that merely further restricts access to testing will
ultimately deliver the increased equity and efficiency that is hoped for.
Uncritical use of the current methods would reduce the chances of
identifying mutation carriers who do not have a conventional cancer family
history, often due to reasons such as paternal inheritance or a limited
pedigree structure [11]. Their modest performance in the low-moderate risk
group further suggests that used in isolation they are not well suited to
the routine consideration of the underlying genetic aetiology that
increasingly forms part of the clinical decision making that takes place
with every new breast cancer diagnosis.
Overall we conclude that, despite the encouraging results reported by
Antoniou et al, for now, at least in the clinical setting, BOADICEA and
other assessment tools should remain an instrument for use by a clinician
rather than the other way around.
Paul A James, Marion Harris, Geoffrey J Lindeman and Gillian Mitchell
References:
[1] Antoniou AC, Hardy R, Walker L, Evans DG, Shenton A, Eeles R,
Shanley S, Pichert G, Izatt L, Rose S, Douglas F, Eccles D, Morrison PJ,
Scott J, Zimmern RL, Easton DF, Pharoah PDP. Predicting the likelihood of
carrying a BRCA1 or BRCA2 mutation: validation of BOADICEA, BRCAPRO, IBIS,
Myriad and the Manchester scoring system using data from UK genetics
clinics
J Med Genet 2008; 45: 425 - 431
[2] Hopper JL, Dowty JG, Apicella C, Southey MC, Giles GG, Winship I.
Towards more effective and equitable genetic testing for BRCA1 and BRCA2
mutation carriers. J Med Genet 2008 45: 409-410
[3] National Institute for Clinical Excellence. Clinical guideline
14. Familial breast cancer: The classification and care of women at risk
of familial breast cancer in primary, secondary and tertiary care. 2004.
National Institute for Clinical Excellence.
[4] Parmigiani G, Berry D, Aguilar O. Determining carrier
probabilities for breast cancer-susceptibility genes BRCA1 and BRCA2. Am J
Hum Genet 1998; 62(1):145-158.
[5] Antoniou AC, Pharoah PP, Smith P, Easton DF. The BOADICEA model
of genetic susceptibility to breast and ovarian cancer. Br J Cancer 2004;
91(8):1580-1590.
[6] Frank TS, Deffenbaugh AM, Reid JE, Hulick M, Ward BE,
Lingenfelter B, Gumpper KL, Scholl T, Tavtigian SV, Pruss DR, Critchfield
GC. Clinical characteristics of individuals with germline mutations in
BRCA1 and BRCA2: analysis of 10,000 individuals. J Clin Oncol 2002;
20(6):1480-1490.
[7] Evans DG, Eccles DM, Rahman N, Young K, Bulman M, Amir E, Shenton
A, Howell A, Lalloo F. A new scoring system for the chances of identifying
a BRCA1/2 mutation outperforms existing models including BRCAPRO. J Med
Genet 2004; 41(6):474-480.
[8] James PA, Doherty R, Harris M, Mukesh BN, Milner A, Young M-A,
Scott C. Optimal Selection of Individuals for BRCA Mutation Testing: A
Comparison of Available Methods. J Clin Oncol 2006 24: 707-715
[9] Lakhani SR, van de Vijver MJ, Jacquemier J, Anderson TJ, Osin PP,
McGuffog L, Easton DF. The pathology of familial breast cancer: predictive
value of immunohistochemical markers estrogen receptor, progesterone
receptor, HER-2, and p53 in patients with mutations in BRCA1 and BRCA2. J
Clin Oncol 2002; 20(9):2310-2318.
[10] Lakhani SR, Reis-Filho JS, Fulford L, Penault-Llorca F, van d,
V, Parry S, Bishop T, Benitez J, Rivas C, Bignon YJ, Chang-Claude J,
Hamann U, Cornelisse CJ, Devilee P, Beckmann MW, Nestle-Kramling C, Daly
PA, Haites N, Varley J, Lalloo F, Evans G, Maugard C, Meijers-Heijboer
H, Klijn JG, Olah E, Gusterson BA, Pilotti S, Radice P, Scherneck S, Sobol
H, Jacquemier J, Wagner T, Peto J, Stratton MR, McGuffog L, Easton DF.
Prediction of BRCA1 status in patients with breast cancer using estrogen
receptor and basal phenotype. Clin Cancer Res 2005; 11(14):5175-5180.
[11] Weitzel JN, Lagos VI, Cullinane CA, Gambol PJ, Culver JO, Blazer
KR, Palomares MR, Lowstuter KJ, MacDonald DJ. Limited Family Structure and
BRCA Gene Mutation Status in Single Cases of Breast Cancer. JAMA
2007;297(23):2587-2595.
We read with interest the article by Wheeler and coworkers who reported on factors associated with mutant CAG repeat instability in Huntington's disease (HD).1 Familial clustering appeared to be one of the factors involved as repeat instability was found to be correlated between siblings (r = 0.28).1 However, and surprisingly, the authors do not report on a far more sensitive and direct measure of heritabil...
We read with interest the article by Wheeler and coworkers who reported on factors associated with mutant CAG repeat instability in Huntington's disease (HD).1 Familial clustering appeared to be one of the factors involved as repeat instability was found to be correlated between siblings (r = 0.28).1 However, and surprisingly, the authors do not report on a far more sensitive and direct measure of heritability, namely the relation between CAG repeat-length changes upon inheritance and repeat-length variation in the sperm of male offspring. Therefore, we re-analyzed the data set that was included in a supplementary Excel-file accompanying the article (http://jmg.bmj.com/supplemental). For the three subjects with multiple sperm samples, we used data from the first collection as repeat-variability in sperm was highly consistent over time for each subject.1 We indeed found that transmission instability is very strongly correlated to repeat-length variations in sperm (n = 70, Pearson r = 0.76, p <0.0001). However, as CAG repeat length itself is the strongest predictor of both transmission instability and repeat-variability in sperm, we then controlled for either parental CAG repeat length or the subject’s constitutive repeat length using partial correlations. Interestingly, this hardly changed the results which remained highly significant (r = 0.80 and p <0.0001 if controlled for parental CAG repeat length; r = 0.46 and p <0.0001 if controlled for subject’s constitutive repeat length). When we controlled for both expanded CAG repeat length and birth order these relations even became somewhat stronger (r = 0.82 and p <0.0001 if controlled for parental CAG repeat length; r = 0.50 and p <0.0001 if controlled for subject’s constitutive repeat length), probably reflecting the disappearance of a weak age-effect of the parent at the time of transmission.1 Multiple linear regression confirmed the above findings and, in addition, showed that the sex of the affected parent did not modify the relation between transmission instability and repeat length variation in sperm (p of regression coefficient = 0.6000). All together, these findings demonstrate that genetic factors, other than the repeat length itself, are involved to a much greater degree in intergenerational CAG repeat instability than can be appreciated from the findings of Wheeler and coworkers alone.1 Characterization of these genetic factors could not only provide better possibilities for parental counseling but could also shed more light on the mechanisms underlying de novo mutations.2
N. Ahmad Aziz, M.Sc.;
Martine J. van Belzen, PhD;
Raymund A.C. Roos, MD, PhD;
Leiden University Medical Centre,
Departments of Neurology and Clinical Genetics,
P.O. Box 9600,
Albinusdreef 2300 RC,
Leiden, the Netherlands,
E-mail: N.A.Aziz@lumc.nl
Reference List
1. Wheeler VC, Persichetti F, McNeil SM, Mysore JS, Mysore SS, MacDonald ME et al. Factors associated with HD CAG repeat instability in Huntington disease. J Med Genet 2007; 44(11):695-701.
2. De Rooij KE, Koning Gans PA, Skraastad MI, Belfroid RD, Vegter-Van Der Vlis M, Roos RA et al. Dynamic mutation in Dutch Huntington's disease patients: increased paternal repeat instability extending to within the normal size range. J Med Genet 1993; 30(12):996-1002.
The statement that "an important predictor of dyslexia, phonological
awareness, can be understood as poor auditory structuring ability applied
to language" raises some questions for me.
/1/
If dyslexia correlates with poor auditory structuring ability, it seems
very strange that some alleles leading to dyslexia would also lead to
musical ability. One would generally assume that musical ability would
involve m...
The statement that "an important predictor of dyslexia, phonological
awareness, can be understood as poor auditory structuring ability applied
to language" raises some questions for me.
/1/
If dyslexia correlates with poor auditory structuring ability, it seems
very strange that some alleles leading to dyslexia would also lead to
musical ability. One would generally assume that musical ability would
involve making good (rather than poor) use of auditory information. This
leads me to ask whether your research plans to find out what particular
aspects of human auditory ability (in people with the music/dyslexia
alleles) might enhance musical learning/performance while simultaneously
worsening literacy learning/performance.
/2/
Does the possession of phonological awareness indeed predict the
possession of poor reading ability? From other research, I had always
assumed that possessing phonological awareness went along with good
(rather than poor) reading ability.
/3/
Similarly, it seems strange to see phonological awareness (rather than its
absence) described as "poor auditory structuring ability." Can you please
clarify how the ability to isolate and sequence the successive sounds
within a spoken word would constitute "poor" (rather than good) "auditory
structuring ability"?
We thank Kate Gladstone for the interest towards our study and answer
to the comments as following:
The statement that "an important predictor of dyslexia, phonological
awareness, can be understood as poor auditory structuring ability applied
to language" raises some questions for me.
/1/ If dyslexia correlates with poor auditory structuring ability, it
seems very strange that some alleles leading to dyslexia wo...
We thank Kate Gladstone for the interest towards our study and answer
to the comments as following:
The statement that "an important predictor of dyslexia, phonological
awareness, can be understood as poor auditory structuring ability applied
to language" raises some questions for me.
/1/ If dyslexia correlates with poor auditory structuring ability, it
seems very strange that some alleles leading to dyslexia would also lead
to musical ability. One would generally assume that musical ability would
involve making good (rather than poor) use of auditory information. This
leads me to ask whether your research plans to find out what particular
aspects of human auditory ability (in people with the music/dyslexia
alleles) might enhance musical learning/performance while simultaneously
worsening literacy learning/performance.
We apologize that a very unfortunate error has indeed crept into the text
during the writing/editing process. The sentence should be: "We have
previously suggested that an important predictor of dyslexia, phonological
awareness, can be understood as auditory structuring ability applied to
language and have shown that a low score in KMT significantly predicts
dyslexia".
We want to clarify here that our quantitative phenotype is linked to the
same microsatellite markers at chromosome 18q that have been shown to be
linked to dyslexia (DYX6 locus). We can speculate that the phenotype in
our study that has low points in auditory structuring ability is linked to
this locus.
/2/ Does the possession of phonological awareness indeed predict the
possession of poor reading ability? From other research, I had always
assumed that possessing phonological awareness went along with good
(rather than poor) reading ability.
We agree with this. Possessing phonological awareness goes along with good
reading ability.
/3/ Similarly, it seems strange to see phonological awareness (rather than
its absence) described as "poor auditory structuring ability." Can you
please clarify how the ability to isolate and sequence the successive
sounds within a spoken word would constitute "poor" (rather than good)
"auditory structuring ability"?
See point /1/.
No competing interests.
With great interest we read the article of Malan et al., who reported
on a novel clinically recognizable 19q13.11 microdeletion syndrome.1 Here
we report on a fifth patient with an interstitial deletion overlapping the
19q13.11 region and compare our findings with those described by Malan et
al. The proband was born after 37 weeks of gestation as one of dizygotic
twins with a birth weight of 1620 g (-3.5 SD). His twin sist...
With great interest we read the article of Malan et al., who reported
on a novel clinically recognizable 19q13.11 microdeletion syndrome.1 Here
we report on a fifth patient with an interstitial deletion overlapping the
19q13.11 region and compare our findings with those described by Malan et
al. The proband was born after 37 weeks of gestation as one of dizygotic
twins with a birth weight of 1620 g (-3.5 SD). His twin sister had a
normal birth weight of 2290 g (p25). They were the first children of
healthy non-consanguineous parents. Pregnancy was complicated by
intrauterine growth retardation. At birth the proband had cutis aplasia
over the posterior occiput, hypospadias, abnormal positioning of the feet,
and a third nipple on the left side of the chest (the latter was also
present in the father) whereas no dysmophisms where reported in his
sister. During the first years of life, feeding difficulties, failure to
thrive, and psychomotor delay were noted: he sat independently at two
years of age, started crawling at the same age and started walking at the
age of three years and ten months. Because of fatigue, he was able to walk
short distances only, and walked with a stiff gait. He suffered from
recurrent airway infections. At the age of four years and 10 months he
could not speak, but was able to communicate with pictograms. He had
hypermetropia (+3D/+4D) similar to his sister. At that age his height was
101.5 cm (-2.5 SD), weight was 15.4 kg (-0.5 SD), and head circumference
was 45.5 cm (-3.5 SD). He had deep-set eyes, a broad nasal tip, a broad
mouth with thin lips, broad gums, irregular placed teeth and retrognatia.
Other features were long fingers with slender thumbs and long, dysplastic
nails, a third nipple on the left side of the thorax, hypospadias, a
sacral dimple and hyperlaxity of the joints (figure 1A-G).
Routine cytogenetic analysis with GTG-banding and subsequent
Multiplex Ligation Dependent Probe Amplification (MLPA) analysis of the
subtelomeric regions did not reveal any abnormalities. Array based
comparative genomic hybridisation analysis (~ 32.000 BAC clones with an
average resolution of 300 kb) was performed as previously described (de
Vries et al. 2005 2) and revealed a 2.4 Mb loss in 19q13.11q13.12 (39.5-
41.9 Mb) encompassing ~ 50 genes (46,XY.arr cgh 19q13.11q13.12(RP11-615P -
> RP11-679B20)x1). This deletion was subsequently confirmed by region
specific Fluorescence In Situ Hybridisation (FISH) analysis using three
BAC clones which map to the aberrant region (46,XY.ish
del(19)(q13.11.q13.12)(RP11_615P5-,RP11_233i16-,RP11_679B20-). In
addition, high resolution 250K SNP array analysis (Affymetrix, Inc., Santa
Clara, CA, USA; average practical resolution of 200 kb) was performed to
further characterize the extend of the deletion (figure 1H). Both SNP
array and FISH analysis were performed in the parents showing that the
deletion occurred de novo, that the maternal allele was deleted in the
proband and that the mother was carrier of an intrachromosomal,
submicroscopic insertion on chromosome 19 (46,XX.ish
ins(19)(q13.?3q13.11q13.12)(q13.11)(RP11_615P5-, RP11_223i16-
)(q13.12)(RP11_679B20-) (q13.?3)(RP11_615P5+,RP11_223i16+, RP11_679B20+).
Therefore, recombination during meiosis is the underlying mechanism for
the deletion to occur in her son (data not shown).
In addition to the report by Malan et al. and Kulharya et al., 3 this
is the fifth patient with an interstitial deletion of the 19q13.11 region,
overlapping the smallest region of overlap of the previously described
patients by only 750 kb. Remarkably though, our patient shares several
major features with the previously reported patients including
intrauterine and postnatal growth retardation, primary microcephaly,
speech disturbance, mental retardation, hypospadias and ectodermal
dysplasia presented by scalp aplasia, dysplastic nails and a dry skin
(table 1). The feeding problems in our patient did not seem to be as
severe as in the patients described by Malan et al. No cardiac defects or
deafness were noted, although the latter was only reported in the case
with the large 11 Mb deletion.
The deletion in the current patient narrows down the critical region
for this novel microdeletion syndrome to ~ 750 Kb (B36.1:CHR19:39 378 624
- 40 131 974) containing only 11 RefSeq genes (NCBI RNA reference sequence
collection 4,5) (figure 1I). For three genes, PDCD2L, KIAA0355, SCGBL, the
function is unknown. The glucose phosphate isomerase gene (GPI; OMIM
#172400) encodes a housekeeping cytosolic enzyme playing a major role in
the glycolysis and the gluconeogenesis pathway. As GPI mutations cause
autosomal recessive chronic hemolytic anemia it is not likely that
haploinsuffiency of this gene contributes to the phenotype in this novel
microdeletion syndrome.6,7,8 Wilms tumor 1 interacting protein (WTIP) is
shown to interact with WT1, which is a zinc finger transcription factor.
ZNF302, ZNF181, ZNF599 and ZNF30 are clustered on chromosome 19q13.11 and
belong to the KRAB-ZNF subfamily. KRAB-ZNFs have been described as
transcription repressors. ZNF clusters have expanded in the primate
evolution lineage and are suspected to contribute to higher cognitive
functioning in primates. 9,10 As three zinc finger genes have previously
been shown to be involved in X-linked mental retardation in males, ZNF41,
ZNF81, ZNF674, 11,12,13 it might be that haploinsuffiency of the zinc
finger cluster in 19q13.11 is involved in the pathogenesis in this novel
syndrome. LSM14A is a Sm-like protein with sequence homology with the Sm
protein family. Sm-like proteins are evolutionary conserved in eukaryotes
and are thought to have a fundamental role in control of mRNA translation
making LSM14A a interesting candidate gene.14,15 Ubiquitin-like modifier
activation enzyme 2 (UBA2) is playing a role in the ubiquitin pathway.
Ubiquitin and ubiquitin-like modifiers regulate multiple important
cellular processes: cell differentiation, apoptosis, posttranslational
modification, transcriptional regulation and DNA repair and are known to
be involved in mental retardation syndromes such as Angelman syndrome
(OMIM#105830), Opitz syndrome (OMIM #300000), Bardet-Biedl syndrome
(OMIM#209900) and limb-girdle muscular dystrophy type 2H (OMIM
#254110).16,17
As our patient has a similar phenotype as the patients described by
Malan et al. and Kulharya et al. we narrowed down the critical region of
this novel microdeletion syndrome from 2,87 Mb to 750 Kb encompassing 11
genes. It is very likely that haploinsufficiency of one or more genes in
this region give rise to this microdeletion syndrome for which LSM14A and
UBA2 seem the most promising candidates.
J.H.M. Schuurs-Hoeijmakers, S. Vermeer, B.W.M. van Bon, R. Pfundt, C.
Marcelis, A.P.M. de Brouwer, N. de Leeuw, B.B.A. de Vries
Department of Human Genetics, Nijmegen Centre for Molecular Life Sciences,
Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands
Correspondence to: Bert B.A. de Vries, Department of Human Genetics
849, Radboud University Nijmegen Medical Centre, P.O. Box 9101, 6500 HB
Nijmegen, The Netherlands. Tel: +31 (0) 243613946; fax: +31 (0) 243668753;
e-mail: b.devries@antrg.umcn.nl
Acknowledgements: We are sincerely appreciative to the patient and
his parents for their support and cooperation. This work was supported by
grants from the Netherlands Organisation for Health Research and
Development (ZON-MW) (BBAdV), Hersenstichting Nederland (BBAdV), and
grants from the AnEUploidy project (LSHG-CT-2006-037627) supported by the
European Commission under FP6 (BBAdV, BvB). The authors wish to
acknowledge the absence of any competing interest.
Competing interest: None.
Patient consent: Consent was obtained from the patient's family for
publishing patient details and images in figure 1.
References
1. Malan V, Raoul O, Firth HV, Royer G, Turleau C, Bernheim A et al.
19q13.11 deletion syndrome: a novel clinically recognizable genetic
condition identified by array-CGH. J Med Genet. Epub 2009 Jan 6.
2. de Vries BB, Pfundt R, Leisink M, Koolen DA, Vissers LE, Janssen IM et
al. Diagnostic genome profiling in mental retardation. Am J Hum Genet.
2005;77(4):606-16.
3. Kulharya AS, Michaelis RC, Norris KS, Taylor HA, Garcia-Heras J.
Constitutional del(19)(q12q13.1) in a three-year-old girl with severe
phenotypic abnormalities affecting multiple organ systems. Am J Med Genet.
1998;77(5):391-4.
4. Kent WJ. BLAT - the BLAST-like alignment tool. Genome Res.
2002;12(4):656-64.
5. Pruitt KD, Tatusova T, Maglott DR. NCBI Reference Sequence (RefSeq): a
curated non-redundant sequence database of genomes, transcripts and
proteins. Nucleic Acids Res. 2005;33(Database issue):D501-4
6. Arnold H. Inherited glucosephosphate isomerase deficiency. A review of
known variants and some aspects of the pathomechanism of the deficiency.
Blut. 1979;39(6):405-17. Review.
7. Kanno H, Fujii H, Hirono A, Ishida Y, Ohga S, Fukumoto Y et al.
Molecular analysis of glucose phosphate isomerase deficiency associated
with hereditary hemolytic anemia. Blood. 1996;88(6):2321-5
8. Kugler W, Breme K, Laspe P, Muirhead H, Davies C, Winkler H et al.
Molecular basis of neurological dysfunction coupled with haemolytic
anaemia in human glucose-6-phosphate isomerase (GPI) deficiency. Hum
Genet. 1998;103(4):450-4
9. Urrutia R. KRAB-containing zinc-finger repressor proteins. Genome Biol.
2003;4(10):231. Review.
10. Emerson RO, Thomas JH. Adaptive evolution in zinc finger transcription
factors. PLoS Genet. 2009;5(1):e1000325. Epub 2009 Jan 2.
11. Lugtenberg D, Yntema HG, Banning MJ, Oudakker AR, Firth HV, Willatt L,
et al. ZNF674: a new kruppel-associated box-containing zinc-finger gene
involved in nonsyndromic X-linked mental retardation. Am J Hum Genet.
2006;78(2):265-78.
12. Kleefstra T, Yntema HG, Oudakker AR, Banning MJ, Kalscheuer VM, Chelly
Jet al. Zinc finger 81 (ZNF81) mutations associated with X-linked mental
retardation. J Med Genet 2004;41:394¡V399
13. Shoichet SA, Hoffmann K, Menzel C, Trautmann U, Moser B, Hoeltzenbein
M et al. Mutations in the ZNF41 gene are associated with cognitive
deficits: identification of a new candidate for X-linked mental
retardation. Am J Hum Genet 2003;73:1341¡V1354.
14. Marnef A, Sommerville J, Ladomery . RAP55: Insights into an
evolutionarily conserved protein family. Int J Biochem Cell Biol. E pub
2008 Aug 3.
15. Yang WH, Yu JH, Gulick T, Bloch KD, Bloch DB. RNA-associated protein
55 (RAP55) localizes to mRNA processing bodies and stress granules. RNA.
2006;12(4):547-54.
16. Lois LM, Lima CD. Structures of the SUMO E1 provide mechanistic
insights into SUMO activation and E2 recruitment to E1. EMBO J.
2005;24(3):439-51.
17. Li T, Santockyte R, Shen RF, Tekle E, Wang G, Yang DC, Chock PB. A
general approach for investigating enzymatic pathways and substrates for
ubiquitin-like modifiers. Arch Biochem Biophys. 2006;453(1):70-4.
We read with great interest the paper by Evans et al1 published
online in your journal. The authors should be commended for having
collected data from different sources to present a substantial series to
try and draw some inferences. However their inferences from these data are
questionable and they have failed to recognise that their data suggest a
change in stage distribution as a result of screenin...
We read with great interest the paper by Evans et al1 published
online in your journal. The authors should be commended for having
collected data from different sources to present a substantial series to
try and draw some inferences. However their inferences from these data are
questionable and they have failed to recognise that their data suggest a
change in stage distribution as a result of screening.
1. Absence of controls
The authors suggest that annual screening ¡°is ineffective in
improving survival in BRCA carriers.¡± Whilst this is possible, we cannot
see how this inference is justified on the basis of the data presented.
The analysis does not use any appropriate control group i.e. unscreened
women. Although the authors presented some data from their historical
controls at one centre, no statistical comparison was made. In addition,
the group with which they have compared BRCA carrier survival includes
high-risk women some of whom have not undergone genetic testing and
therefore may also be carriers. Such a comparison is of limited value and
hard to interpret. In the absence of a prospective randomised controlled
trial comparing screening with no intervention, which is not considered
practical in the high risk group (or ethical by some) the best surrogate
for survival benefit is a change in stage distribution.
The proportion of early stage cancers (23%) detected at prevalent
screen in the study is similar to clinically detected early stage disease
reported in the literature.2,3 Our analysis indicates that a sample size
of 134 cancers would be required for an 80% power (where actual ¥á= 0.04)
to document a doubling of screen detected early cancers to 46%. Hence, it
is likely that the study is underpowered to elicit a significant change in
stage distribution between prevalent and incident screens for the cohort
as a whole.
2. Significant change in stage distribution present in carriers
We do not understand the inclusion of borderline cancers in the
analysis. BRCA mutations are not linked to borderline cancers and their
excellent a priori prognosis is unlikely to be affected by screening. We
therefore reanalysed the data excluding the borderlines (table-1) and
found a change in the stage distribution between prevalent and incident
screens which just reached a significant level (p= 0.046) in BRCA
carriers, suggesting that annual screening has had a positive effect on
stage distribution at diagnosis in this cohort.
Population based data suggest that approximately 80% 2,3 of ovarian
cancers present at stage 3 or stage 4 in BRCA carriers. In our analysis of
the BRCA associated ovarian cancers, only 47% are stage 3 or stage 4 in
the incident screen. Although comparison with historical data has
limitations, this finding raises the possibility that annual screening has
resulted in the down staging of some cancers. The authors do not appear to
have recognised this finding, which is all the more important as the study
may be underpowered.
In the light of interval cancers in many high risk screening studies
there has been an emerging opinion that annual screening may not improve
survival in the high-risk population. More frequent 4 monthly screening is
now being evaluated in ongoing studies (UK FOCSS in the UK and the CGN/GOG
studies in the USA). However, the data in table-1 are the first evidence
we are aware of suggesting the possibility of significant change in the
stage distribution between prevalent and incident screens, and may offer
hope of improved survival for some women even with annual screening.
3. Interval cancers
The authors have defined interval cancers as those occurring ¡°within
12-14 months¡± from last screen. Though this may reflect the ¡°real-
world¡±, where slight delays in annual screens may occur, it would have
been better if a median and range for the time from last screen to
clinical presentation of interval cancers was provided. It is also
important to indicate how many of the interval cancers occurred between 12
and 14 months as such cases are potentially due to delayed annual
screening, rather than being true interval cancers occurring between
annual screens. Therefore we feel that the description of the ¡°interval¡±
cases may not be an accurate representation of true annual screening
performance.
It would be prudent to wait for the 4 monthly high-risk population
screening studies to report, along with the ongoing general postmenopausal
population studies (UKCTOCS and PLCO trials) before drawing firm
conclusions regarding the efficacy of screening for ovarian cancer. If 4-
monthly screening in the familial group shows a significant stage shift
and if general population screening shows a mortality benefit, then there
would be a strong argument in favour of offering screening to high-risk
women who do not want to undergo risk-reducing salpingo-oophorectomy.
Until these data are available, we concur with the authors¡¯ closing
remarks concerning the need for women at high risk to be included in
research trials of screening.
2. Moslehi R, Chu W, Karlan B, Fishman D, Risch H, Fields A, Smotkin
D, Ben-David Y, Rosenblatt J, Russo D, Schwartz P, Tung N, Warner E, Rosen
B, Friedman J, Brunet JS, Narod SA. BRCA1 and BRCA2 mutation analysis of
208 Ashkenazi Jewish women with ovarian cancer. Am J Hum Genet.
2000;66(4):1259-72
3. Hirsh-Yechezkel G, Chetrit A, Lubin F, Friedman E, Peretz T,
Gershoni R, Rizel S, Struewing JP, Modan B. Population attributes
affecting the prevalence of BRCA mutation carriers in epithelial ovarian
cancer cases in Israel. Gynecol Oncol 2003; 89(3):494-8.
Statement re Conflict of interest
The authors declare no conflict of interest
License Statement
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BMJPGL products to exploit all subsidiary rights, as set out in the
licence (http://jmg.bmj.com/iforalicence.pdf).
Ehtics Committee
This manuscript is only a re-anlaysis of data recently published in
the journal. Hence, separate ethics approval was not requested.
New challenges for informed consent through whole-genome array
testing
Christian Netzer1,2, Christine Klein3, Jürgen Kohlhase4, Christian
Kubisch1,2
1Institute of Human Genetics, University of Cologne, Germany
2Center of Molecular Medicine Cologne, University of Cologne, Germany
3Department of Neurology, University of Lübeck, Germany
4Center for Human Genetics Freiburg, Freiburg, Germany
We read with great interest the article by Schwarzbraun et al. on
predictive diagnosis of Li-Fraumeni syndrome established as an accidental
finding in whole-genome array testing originally performed to identify the
molecular cause of mental retardation (MR) in a seven-year-old child1. We
would like to expand the spectrum of unexpected and unintended findings
with this new technique: In a five-year-old Kurdish boy with mental
retardation and normal karyotype, array CGH with an Agilent platform
(using the Human Genome CGH 244A Microarray Kit with a medium spatial
resolution of 12 kb and a threshold of 5 consecutive aberrant clones)
identified a heterozygous intragenic deletion spanning exons 4 and 5 of
the Parkin gene (PARK2) as the only significant change (minimal deletion
boundaries for NCBI Build 36, chromosome 6: 162,339,755-162,582,128). Bi-
allelic mutations of Parkin cause early-onset parkinsonism (OMIM 600116),
a neurodegenerative disorder without phenotypic overlap to the MR syndrome
of the five-year-old boy. Hence, array CGH accidentally revealed a carrier
status for a more late-onset autosomal recessive disease.
We informed the patient´s parents about this result. They planned to
have another child and asked us about the risk for their future offspring
to be affected by this type of parkinsonism. The maximum frequency of
putative recessive heterozygous Parkin mutations reported in the
literature is 3.1% 2-5. Hence this risk would be up to 0.75%, if the
Parkin deletion was inherited from either parent (offspring risk for
carrying two mutations then can be calculated as 1 x 3/100 x 1/4, assuming
no consanguinity between the parents). We complied with the parents´
request to clarify this situation through additional genetic tests and
initiated MLPA analyses at the PARK2 locus (MRC Holland, SALSA Kit P051)
on DNA samples of the parents and the MR-affected son, as well as direct
sequencing of all coding exons and adjacent splice sites of Parkin on
parental DNA. The Parkin exon 4-5 deletion turned out to be inherited from
the patient´s mother, and neither the patient nor his parents carried
another mutated Parkin allele.
Of note, testing the parents for mutations in Parkin by MLPA and
direct sequencing had a low, but not negligible probability of being a
predictive genetic test for early-onset parkinsonism: The disease is not
fully penetrant by age 35 and 43, respectively, and since a de-novo Parkin
exon 4-5 deletion in the index patient was in our view a priori rather
unlikely, there was an up to 3% chance that the parent who inherited this
deletion carried a mutation on the other allele, as well. In addition,
testing the Parkin gene in the mentally retarded child by MLPA, which we
considered to be necessary in order to validate the array CGH finding with
an independent method, was associated with a (considerably lower)
probability of identifying an exon-spanning deletion also on the other
Parkin allele. This further complexity for genetic counselling, caused by
the fact that the Parkin Type of Juvenile Parkinson Disease is not an
early-childhood-onset autosomal recessive disorder, may be rather the
exception than the rule. However, in our view it would have been a
sufficient but not mandatory argument to decline the parents´ request for
carrier testing in this case. Adding a final level of complexity, there is
a growing body of evidence that heterozygous Parkin mutations may act as a
risk factor for complex inherited (late-onset) Parkinson disease6, a
potentially relevant issue for genetic counselling. Interestingly, the
family history of the patient´s mother was positive for Parkinson
disease, with her paternal grandfather being affected in the seventh
decade of life.
This experience prompted us to rethink our procedure to obtain
informed consent to array CGH. We reasoned that – as now reported by
Schwarzbraun et al. – also mutations of genes underlying autosomal-
dominantly inherited tumor predisposition syndromes or late-onset
neurological disorders (e. g., Hereditary Neuropathy with Liability to
Pressure Palsies [OMIM 162500], which is typically caused by a
heterozygous 1.5-Mb deletion on chromosome 17p11.2) might be accidentally
identified through array CGH analyses for mental retardation syndromes.
These deletions or duplications do not necessarily have to be an integral
part of the imbalance causing the phenotype in question, as it was the
case with the seven-year-old mentally retarded boy, who carried a de-novo
deletion of 47 genes including the Li-Fraumeni gene TP53. They can of
course be inherited independently, and this knowledge could sometimes be
of great importance for the entire family (e. g., if an HNPCC gene was
affected, as life-saving surveillance programs exist for this cancer
predisposition syndrome [OMIM 120435]). On the other hand, some of these
conditions may be untreatable or fatal, and whether or not such predictive
genetic information should be disclosed is a very personal decision. In
addition to these considerations, we are aware of one individual with a
non-hereditary hematologic disease (chronic lymphocytic leukemia, with
somatic deletions involving chromosome 4 and 11q) accidentally
“rediagnosed� in the course of an array CGH research project comparing
the genomes of monozygotic twins on the basis of DNA extracted from
peripheral leukocytes7.
As a consequence, we have now revised our procedure to obtain
informed consent to array CGH prior to the analyses. Patients or their
parents have to decide whether
- they wish to be informed about any additional genetic findings
(without direct connection to the phenotype in question) with predictive
value for the health of the proband and potentially her / his family;
- they only whish to be informed about such additional genetic
findings if effective treatment options or surveillance programs are
available;
- they whish to be informed about a carrier status for an autosomal
recessive disease, i.e., about a condition which may have implications for
reproductive decisions of the proband and/or family members.
Once the resolution of array CGH is high enough to accurately detect
single-exon aberrations, the latter point may in fact be the one most
frequently occurring in clinical practice, simply because there are
hundreds if not thousands of autosomal recessive disease genes in the
human genome. The resulting genetic risks can be substantial, especially
if consanguinity is an issue.
To our knowledge, the implications and challenges for the informed
consent procedure resulting from a more detailed look at the humane genome
have not yet been broadly discussed with respect to routine clinical
testing. However, they have to be addressed in order to cope with such
“accidents� of array CGH analysis and to comply with patients´
autonomy.
Correspondence to: Dr. Christian Netzer, Institut für Humangenetik,
Uniklinik Köln, Kerpener Str. 34, 50931 Köln, Germany;
christian.netzer@uk-koeln.de
Competing interests: None.
REFERENCES
1. Schwarzbraun T, Obenauf A, Langmann A, et al. Predictive diagnosis
of the cancer prone Li-Fraumeni syndrome by accident: new challenges
through whole-genome array testing. J Med Genet. Published Online First: 5
March 2009. doi:10.1136/jmg.2008.064972
2. Clark LN, Afridi S, Karlins E, et al. Case-control study of the
parkin gene in early-onset Parkinson disease. Arch Neurol 2006;63(4):548-
52.
3. Kann M, Jacobs H, Mohrmann K, et al. Role of parkin mutations in
111 community-based patients with early-onset parkinsonism. Ann Neurol
2002;51(5):621-5.
4. Kay DM, Moran D, Moses L, et al. Heterozygous parkin point
mutations are as common in control subjects as in Parkinson's patients.
Ann Neurol 2007;61(1):47-54.
5. Lincoln SJ, Maraganore DM, Lesnick TG, et al. Parkin variants in
North American Parkinson's disease: cases and controls. Mov Disord
2003;18(11):1306-11.
6. Klein C, Lohmann-Hedrich K, Rogaeva E, et al. Deciphering the role
of heterozygous mutations in genes associated with parkinsonism. Lancet
Neurol 2007;6(7):652-62.
7. Bruder CE, Piotrowski A, Gijsbers AA, et al. Phenotypically
concordant and discordant monozygotic twins display different DNA copy-
number-variation profiles. Am J Hum Genet 2008;82(3):763-71.
The report by van Bon et al. contributes additional data on
phenotypic variability associated with the newly described recurrent,
microdeletion at 15q13.3. However, I have two objections to the data
presentation and conclusions of the article.
First, the authors continue an unfortunate new trend of combining
data presentations for microdeletions and their reciprocal
microduplication products. It is extremely r...
The report by van Bon et al. contributes additional data on
phenotypic variability associated with the newly described recurrent,
microdeletion at 15q13.3. However, I have two objections to the data
presentation and conclusions of the article.
First, the authors continue an unfortunate new trend of combining
data presentations for microdeletions and their reciprocal
microduplication products. It is extremely rare that deletions and
duplications of the same chromosomal region share any phenotypic
similarities or conform to a type-countertype relationship (i.e., opposite
phenotypes). Combining data presentation and discussions of genotype-
phenotype relationships of a deletion syndrome and reciprocal duplication
is inappropriate and can be confusing to readers who may "blend" or
average the phenotypic effects of these two distinctly different genetic
disorders.
Second, the conclusion expressed in the abstract and discussion "The
existence of microdeletion syndromes, associated with an unpredictable and
variable phenotypic outcome, will pose the clinician with diagnostic
difficulties and challenge the commonly used paradigm in the diagnostic
setting that aberrations inherited from a phenotypically normal parent are
usually without clinical consequences." is not justified. Certainly,
genetic disorders that display incomplete penetrance and variable
expressivity present challenges to clinicians, but are not new phenomenon
to clinical geneticists (e.g., del 22q11.2). The "commonly used paradigm"
in diagnostic labs of interpreting novel, inherited copy number changes as
likely benign is true in the great majority of cases (well over 95% of the
time), and should not be challenged or thrown out based on exceptional
cases. It would be a disservice to our patients and referring clinicians
to not provide our best clinical interpretation based on today's
knowledge, understanding that our knowledge of pathogenic vs. benign copy
number changes will increase rapidly in the next several years.
David H. Ledbetter, Ph.D.
david.ledbetter@emory.edu
Dear Editor
We thank the Human Gene Mutation Database (HGMD) team for critically analysing our results, and highlighting some potential problems with our analysis.
Many of the criticisms raised by Stenson et al. relate to mutations that were outside the terms of reference of the study. For instance, a major criticism raised by Stenson et al. was that the review was not comprehensive viz we negle...
In their interesting manuscript, Tomita-Mitchell and colleagues present four novel GATA4 sequence variations as pathogenic substrates for congenital heart disease (CHD) in humans[1]. CHD are the most common birth defect and affect almost 1% of all newborns. Since surgical approaches have substantially improved over the last decades, the number of grown ups with CHD (GUCH) is growing continuously. This fact dema...
To the Editor: Dear Sir
We read with interest the study by Antoniou et al, [1] in which they compared a number of the described methods for assessing the probability that a BRCA1 or BRCA2 gene mutation is the cause of a family history of breast or ovarian cancer in 1934 families of non-Ashkenazi Jewish origin. In this study a number of methods, particularly the BOADICEA model, demonstrated a high degree of disc...
The statement that "an important predictor of dyslexia, phonological awareness, can be understood as poor auditory structuring ability applied to language" raises some questions for me.
/1/ If dyslexia correlates with poor auditory structuring ability, it seems very strange that some alleles leading to dyslexia would also lead to musical ability. One would generally assume that musical ability would involve m...
We thank Kate Gladstone for the interest towards our study and answer to the comments as following:
The statement that "an important predictor of dyslexia, phonological awareness, can be understood as poor auditory structuring ability applied to language" raises some questions for me. /1/ If dyslexia correlates with poor auditory structuring ability, it seems very strange that some alleles leading to dyslexia wo...
With great interest we read the article of Malan et al., who reported on a novel clinically recognizable 19q13.11 microdeletion syndrome.1 Here we report on a fifth patient with an interstitial deletion overlapping the 19q13.11 region and compare our findings with those described by Malan et al. The proband was born after 37 weeks of gestation as one of dizygotic twins with a birth weight of 1620 g (-3.5 SD). His twin sist...
Dear Sirs,
We read with great interest the paper by Evans et al1 published online in your journal. The authors should be commended for having collected data from different sources to present a substantial series to try and draw some inferences. However their inferences from these data are questionable and they have failed to recognise that their data suggest a change in stage distribution as a result of screenin...
New challenges for informed consent through whole-genome array testing
Christian Netzer1,2, Christine Klein3, Jürgen Kohlhase4, Christian Kubisch1,2
1Institute of Human Genetics, University of Cologne, Germany
2Center of Molecular Medicine Cologne, University of Cologne, Germany
3Department of Neurology, University of Lübeck, Germany
4Center for Human Genetics Freiburg, F...
The report by van Bon et al. contributes additional data on phenotypic variability associated with the newly described recurrent, microdeletion at 15q13.3. However, I have two objections to the data presentation and conclusions of the article.
First, the authors continue an unfortunate new trend of combining data presentations for microdeletions and their reciprocal microduplication products. It is extremely r...
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