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 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.
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.
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 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.
I was most interested to read the paper of Iwaki et al. on ‘SCA16’, in a large ataxia kindred with a deletion of the ITPR1 gene 1.
SCA15 has been a close interest of our group, going from the study of the original family that defined the condition, to the recent discovery of the ITPR1 gene as its basis2 3 4 5.
It is interesting and useful information from Iwaki et al. that the...
I was most interested to read the paper of Iwaki et al. on ‘SCA16’, in a large ataxia kindred with a deletion of the ITPR1 gene 1.
SCA15 has been a close interest of our group, going from the study of the original family that defined the condition, to the recent discovery of the ITPR1 gene as its basis2 3 4 5.
It is interesting and useful information from Iwaki et al. that the ‘head-to-head’ adjacent SUMF1 gene is not deleted in their family, and it’s only ITPR1 that is deleted. We had suspected, on theoretical grounds, that SUMF1 would not be involved in the molecular pathogenesis of
the ataxia, in the three SCA15 families reported in van de Leemput et al. (2007), and that ITPR1 must be the real culprit; but now Iwaki et al. provide definite proof. Good!
But my comment is this: now that the original – and only – ‘SCA16’ family has been shown to have the ITPR1 gene as its basis, can we not now change the number in this family, and call it SCA15? Could we not now see SCA15 as ‘ITPR1-associated ataxia’? – so far (n = 4) the association being with a large deletion, taking out the 5’ extent of the gene, and extending for variable distances into the 3’ extent.
Is it not (potentially) confusing to continue to refer to SCA16?
My suggestion: SCA16 should become a ‘vacant SCA’ (there’s precedent for this with SCA9) – and the family in Iwaki et al. should be regarded as having SCA15, as should any further familial ataxia families coming to be identified with an ITPR1 mutation.
R J McKinlay Gardner
Melbourne, 17 Nov 2007
References:
1. Iwaki A, Kawano Y, Miura S, Shibata H, Matsuse D, Li W, Furuya H, Ohyagi Y, Taniwaki T, Kira JI, Fukumaki Y. Heterozygous deletion of ITPR1, but not SUMF1 in spinocerebellar ataxia type 16. J Med Genet. 2007 Oct 11;
[Epub ahead of print]
2. Gardner RJM, Knight MA, Hara K, Tsuji S, Forrest SM, Storey E.
Spinocerebellar ataxia type 15. Cerebellum. 2005;4(1):47-50.
3. Knight MA, Kennerson ML, Anney RJ, Matsuura T, Nicholson GA, Salimi-Tari P, Gardner RJM, Storey E, Forrest SM. Spinocerebellar ataxia type 15 (sca15) maps to 3p24.2-3pter: exclusion of the ITPR1 gene, the human
orthologue of an ataxic mouse mutant. Neurobiol Dis. 2003 Jul;13(2):147-57.
4. Storey E, Gardner RJM, Knight MA, Kennerson ML, Tuck RR, Forrest SM, Nicholson GA. A new autosomal dominant pure cerebellar ataxia. Neurology. 2001 Nov 27;57(10):1913-5.
5. van de Leemput J, Chandran J, Knight MA, Holtzclaw LA, Scholz S, Cookson MR, Houlden H, Gwinn-Hardy K, Fung HC, Lin X, Hernandez D, Simon-Sanchez J, Wood NW, Giunti P, Rafferty I, Hardy J, Storey E, Gardner RJM, Forrest SM, Fisher EM, Russell JT, Cai H, Singleton AB. Deletion at ITPR1 underlies ataxia in mice and spinocerebellar ataxia 15 in humans. PLoS Genet. 2007 Jun;3(6):e108.
Prevous studies have demonstrated that the prevalence rate of R1195Q in SCN5A gene ranges from 0.2% to 12% and suggested this mutation may be a risk factor for long QT syndrome (LQTS) [1,2]. However, Chen et al showed no association between R1193Q and the disease process or ECG abnormalities in a four-generation Chinese family with cardiac conduction abnormalities and sudden death[1].
Prevous studies have demonstrated that the prevalence rate of R1195Q in SCN5A gene ranges from 0.2% to 12% and suggested this mutation may be a risk factor for long QT syndrome (LQTS) [1,2]. However, Chen et al showed no association between R1193Q and the disease process or ECG abnormalities in a four-generation Chinese family with cardiac conduction abnormalities and sudden death[1].
We recently identified the R1193Q polymorphism by direct DNA sequencing of SCN5A in a four-generation Han Chinese pedigree with progressive cardiac conduction defect (PCCD) and LQTS. Out of the seven R1193Q carriers, five (III-7, III-10, III-12, III-13, IV-5) were diagnosed as PCCD, and two (III-10, III-12) also had prolonged QTc; one carrier (III -1) had no PCCD but with borderline prolonged QTc; only the youngest carrier (IV-8) had normal ECG now (Table 1 and Figure 1).
Table 1
None of the family members had electrocardiographic signs of Brugada syndrome and quinidine or sotalol or amiodarone was not prescribed. No echocardiographic abnormalities were detectable. Our finding indicates that R1193Q polymorphism of the SCN5A gene might be associated with PCCD and LQTS in this Chinese family.
The electrophysiological studies by Wang et al showed R1193Q destabilised channel inactivation and generated a persistent late inward current via dispersed reopening, so they considered R1193Q as a functional mutation that can increase the susceptibility to LQTS [2]. In contrast to
their finding in the 4-generation Chinese pedigree with cardiac conduction abnormalities and sudden death, Chen et al identified one of the nine R1193Q carriers was affected with LQTS (QTc = 472ms) and another had borderline QTc (QTc = 437ms) in general Chinese population [1]. Our present results are, therefore, in line with Chen's [1] and Wang's [2] findings suggesting that R1193Q may be a risk factor for LQTS.
Progressive cardiac conduction defect (PCCD) is one of the most common cardiac conduction abnormalities that is characterized by progressive alteration of cardiac conduction, leading to complete atrio-ventricular block (AVB) and causing syncope and sudden death. In 1999,
Scott et al reported associations betweenSCN5A mutations and PCCD in a large French family and non-progressive conduction defect in a smaller Dutch family[3]. Since then, some other mutations of SCN5A resulting in PCCD have been identified [4-6]. Till now, only few cases were reported on coexistence of PCCD and LQTS[7,8]. Our present study revealed a SCN5A
polymorphism R1193Q in the familial PCCD with LQTS. One carrier (IV-8) with normal EKG in this family is at his young age (16 years old) now and it will be interesting to follow up this carrier to see if he will develop
PCCD or LQTS later on.
A recent report suggested that R1193Q might be a protective factor for some cardiac conduction abnormalities caused by SCN5A W1421X mutation [9] and authors identified a novel mutation W1421X in a Chinese family with cardiac conduction abnormalities and most family members who carried
this W1421X mutation developed major clinical manifestations and EKG abnormalities (sinus bradycardia or AVB), and several family members died in their mid-lives. But a 73-year-old grandfather, who carried both the W1421X and R1193Q mutations, remained healthy with only subtle EKG
abnormalities. Thus, they suggested that R1193Q may protect cardiac conduction system from the impairment of W1421X mutation. Though we did not find the coexisted W1421X or other mutations in our study, our results argue against a protective role of R1193Q on cardiac conduction
abnormalities.
In summary, our results derived from this four-generation Chinese family with PCCD and LQTS suggested that R1193Q might increase the risk of LQTS.
Acknowledgements
This study was supported by a grant from Shanghai Basic Research Program (05QMX1411), and a grant from the National Natural Science Foundation of China (NSFC) (30700317)
Competing interests: none declared.
References:
1. Chen YT, Hwang HW, Niu DM, Hwang BT, Chen JJ, Lin YJ, Shieh RC,
Lee MT, Hung SI, Wu JY. R1193Q of SCN5A, a Brugada and long QT mutation, is a common polymorphism in Han Chinese. J Med Genet 2005;42:e7.
2. Wang Q, Chen S, Chen Q, Wan X, Shen J, Hoeltge GA, Timur AA, Keating MT, Kirsch GE. The common SCN5A mutation R1193Q causes LQTS-type electrophysiological alterations of the cardiac sodium channel. J Med Genet 2004;41:e66.
3. Schott JJ, Alshinawi C, Kyndt F, Probst V, Hoorntje TM, Hulsbeek M, Wilde AA, Escande D, Mannens MM, Le Marec H. Cardiac conduction defects associate with mutations in SCN5A. Nat Genet 1999;23:20-1.
4. Napolitano C, Rivolta I, Priori SG. Cardiac Sodium Channel Diseases. Clin Chem Lab Med 2003;41:439-444.
5. Subbiah RN, Campbell TJ, Vandenberg JI. Inherited cardiac arrhythmia syndromes: what have they taught us about arrhythmias and anti-arrhythmic therapy? Clin Exp Pharmacol Physiol 2004; 31:906-912.
6. Laitinen-Forsblom PJ, Makynen P, Makynen H, Yli-Mayry S, Virtanen V, Kontula K, Aalto-Setala K. SCN5A Mutation Associated with Cardiac Conduction Defect and Atrial Arrhythmias. J Cardiovasc Electrophysiol 2006;17:480-485.
7. Pruvot E, De Torrente A, De Ferrari GM, Schwartz PJ, Goy JJ. Two-to-one AV block associated with the congenital long QT syndrome. J Cardiovasc Electrophysiol 1999;10:108-13.
8. Lupoglazoff JM, Cheav T, Baroudi G, Berthet M, Denjoy I, Cauchemez B, Extramiana F, Chahine M, Guicheney P. Homozygous SCN5A mutation in long QT syndrome with functional two-to-one atrioventricular block. Circ Res
2001;89:e16-e21.
9. Niu DM, Hwang B, Hwang HW, Wang NH, Wu JY, Lee PC, Chien JC, Shieh RC, Chen YT. A common SCN5A polymorphism attenuates a severe cardiac phenotype caused by a nonsense SCN5A mutation in a Chinese family with an inherited cardiac conduction defect. J Med Genet 2006;43:817-821.
Figure 1
Figure legend: In this four-generation Chinese family, we investigated 25 members; little is known about I-1,I-2, II-1, II-2 since they died long ago. Blood-related family members are 18. EKGs of 21 are available; DNAs of 21 are available. Numbers characterize individuals in each generation. ↑ indicates the proband. Individuals with diagnosed cardiac conduction defects are marked in black. II-6 without exact EKG record is marked in lines. #, prolonged or borderline QTc; ?, QTc unknown; +, R1193Q carriers; -, R1193Q non-carriers; NA, DNA sample not ailable.
We write in response to a number of very specific criticisms of the Human Gene Mutation Database (HGMD) made in the recently published article of George et al. [PMID: 17893115]. All seven claims made were amenable to empirical testing. Having tested these claims, we find all of them to be either false or highly misleading. In the text that follows, we refute or rebut each claim in turn.
We write in response to a number of very specific criticisms of the Human Gene Mutation Database (HGMD) made in the recently published article of George et al. [PMID: 17893115]. All seven claims made were amenable to empirical testing. Having tested these claims, we find all of them to be either false or highly misleading. In the text that follows, we refute or rebut each claim in turn.
HGMD represents an attempt to collate known (published) gene lesions responsible for human inherited disease. HGMD comprises various types of germ-line mutation within the coding, splicing and regulatory regions of human nuclear genes. HGMD currently (1st October 2007) contains 73,411 different mutations in 2,768 human genes.
Claim 1 – 143 genes are present in OMIM but have no corresponding HGMD entry.
Response – This claim is wholly misleading. OMIM records many types of gene mutation which HGMD does not, such as somatic lesions, neutral polymorphisms and mitochondrial mutations. It is therefore to be expected that there will be some entries in OMIM that do not have a corresponding HGMD entry. We received the list of 143 genes from George et al. and performed our own analysis. After careful comparison with OMIM, we found the following;
• 33 genes (23.1%) contain only somatic allelic variants (e.g. LEF1).
• 29 genes (20.3%) contain variants exclusively from the mitochondrial genome (e.g. MTCO2).
• 8 genes (5.6%) contain exclusively normal polymorphic protein variants with no known disease association (e.g. GPT).
• 13 genes (9.1%) were actually present in HGMD at the time of the study, but, for whatever reason, had not been found by George et al. (e.g. CD2AP).
• 12 genes (8.4%) were misidentified by George et al. as having allelic variants in OMIM when they did not (or no longer have) (e.g. FUZ).
• 5 genes (3.5%) contained ‘disease-associated variants’ whose accompanying information was deemed to be in some way of insufficient quality to allow these to be entered into HGMD (e.g. GABRA2).
• 43 genes (30%) were entered into HGMD after the George et al. study was performed (e.g. SAMD9).
George et al. could legitimately have claimed that HGMD was missing 43 (not 143) genes on the basis of their study data. However, it should be noted that all but 3 of these 43 genes were entered into HGMD at the latest by the end of February 2007 (within 4 months of the stated date of the George et al. study). The remaining 3 genes were entered more recently. Thus, far from being an indictment of HGMD content, the analysis of George et al. would appear to confirm what we believe to be HGMD’s very high degree of efficiency in incorporating pathological mutations responsible for causing human genetic disease.
Claim 2 – 226 genes in OMIM contain more mutation entries than HGMD.
Response – This claim is false. George et al. provided HGMD with a list of the 226 genes which we have carefully reviewed. As 143 of these genes were present in this list simply due to their initial inclusion in the previous list (reviewed in Claim 1), we discounted these for the purposes of this analysis. We were therefore left with 83 genes to check. With respect to these 83 genes, we found the following;
• 23 (27.7%) entries contained additional somatic allelic variants (e.g. AXIN2).
• 10 (12%) entries contained additional polymorphic variants or haplotypes (e.g. CCR5).
• 5 (6%) entries (all globin genes) contained additional non-disease associated variants (e.g. HBA1).
• 17 (20.5%) entries actually had an equal number or fewer mutations than HGMD (e.g. HAL).
• 18 (21.7%) entries were added to HGMD after the George et al. study was completed (e.g. OTOF).
• 10 (12.1%) entries contained data which were indeed missing from HGMD (e.g. CFD).
Consequently, George et al. could, on the basis of their study data, legitimately have claimed that, at the time of writing, there were 28 (not 226) genes present in OMIM with more allelic variants than HGMD. The mutations from 18 of these genes were however added very shortly after the study of George et al. was concluded. The remaining 10 genes contained around 18 mutations which were inadvertently omitted from HGMD. Thanks, however, to George et al. and the prior efforts of the OMIM curators, the missing mutation data for these 10 genes have now been included in HGMD.
In their analysis, George et al. ignored several categories of mutation present in HGMD (small and gross deletions, insertions and indels, complex rearrangements and repeat variations). These categories contain significant (23,570 in HGMD Professional release 7.3) numbers of mutations. To ignore them in the published analysis was highly misleading and would have inevitably led to erroneous conclusions being drawn (due to an apparent failure to compare like with like). A good example of the type of error made is provided by the C6 gene. This gene currently has 4 allelic variants listed in OMIM (plus one neutral polymorphism). The HGMD entry for C6 has 9 mutations listed (6 at the time of the published study), yet according to George et al., HGMD had fewer mutation entries than OMIM for this gene.
Claim 3 – Many mutations are missing from HGMD that were published in the journal Human Mutation.
Response – This claim is highly misleading. These ‘missing’ mutations are listed in Supplementary Table 2 of the George et al. paper. We have carefully reviewed the data in this table and have concluded that HGMD is not missing any of the mutations that the authors claim. All but 4 of the disease-causing inherited lesions listed with either “no”, “not in website” or “unable to determine” had been entered into HGMD within 1-2 months of their publication in the Human Mutation issue cited in the table. Four others were entered later, but would have certainly been present at the time of the study. George et al. had access to HGMD Professional and could easily have obtained data entry dates from this version of HGMD had they been able to locate the listed mutations. Several mutations had already been described in the literature prior to their publication as ‘novel’ in Human Mutation (e.g. PAX6 1410delC). In accordance with HGMD policy, the earlier paper was given priority as the reference to be cited rather than the subsequent report in Human Mutation. George et al. also listed many neutral and somatic variants in their table as if they had expected to find these data in HGMD (e.g. ATM c.185+78A>G and ANP32C g.4870T>C). It is quite apparent to us that George et al. have displayed a complete lack of understanding of the nature of the data that HGMD seeks to collate, a serious inability to interpret published mutation data and/or an inability to undertake basic data searching and retrieval from HGMD.
Claim 4 – R158Q in PAH is in error.
This claim is incorrect. The reference cited by both HGMD and OMIM [Dworniczak et al., Hum. Genet. (1989) 84: 95-6] contained an error, in that the G>A base change reported would have given rise to R158Q and not R158E as described. As part of our curation process, we corrected this error (and the curators of OMIM have done likewise). It is noteworthy that the reference given by George et al. for this mutation [Hennermann et al., Hum. Mutat. (2000) 15: 254-260] does not actually claim that this lesion was novel to their study.
Claim 5 - HGMD is missing two specific genes (COL9A1 and PTCH2).
Response – This claim is incorrect. COL9A1 has been present in HGMD since 2001 with one small insertion mutation logged at that time. Since George et al. elected to utilise only single base-pair substitutions in their analyses (thereby ignoring approximately one third of the HGMD dataset), this entry was missed [a nonsense mutation (R272X) was added to this entry shortly after the George et al. study was concluded]. The question should be again raised as to why the authors chose to ignore HGMD micro-insertions, micro-deletions, indels, gross lesions and repeat variations in their analyses, thereby excluding some 23,570 different human gene lesions and 254 genes logged in HGMD with only these categories of mutation. The second gene that was claimed to be “missing” from HGMD was PTCH2. However, the two allelic variants listed in OMIM for this gene are both somatic and so HGMD did not “miss” this gene at all, since HGMD only includes heritable lesions.
Claim 6 – Patchy coverage of gene and mutation data in HGMD.
Response – This assertion was made on the basis of a study that appears to be deeply flawed, methodologically and statistically. The authors seem to have little appreciation or understanding of the types of mutation data recorded by either OMIM or HGMD. Once again, and for whatever reason, the authors excluded 23,570 mutations (almost one third of HGMD data) from their analysis. They then have the temerity to criticise HGMD for patchy coverage!
Claim 7 – The authors claim no competing interests.
Response – In our opinion, this claim is hard to justify. Several of the authors of the George et al. paper are currently seeking substantial funding to set up from scratch a new and all embracing human variation/mutation database. Since HGMD is in practice the only comprehensive central repository for human gene mutations in existence, their comparative ‘analysis’ of HGMD data should at the very least, in our view, have been accompanied by a clear statement of the potential conflict of interest inherent in their critical conclusions. It is quite disingenuous for the authors to claim otherwise.
In summary, in a deeply flawed study, George et al. have drawn numerous incorrect or misleading conclusions with respect to HGMD, its remit, content and coverage. Their study represents a graphic example of how over-reliance on automated text-mining, a reluctance to attempt any independent verification of their initial findings and an apparent lack of knowledge of the mutation databases they were analysing, can combine together to yield wholly erroneous conclusions. We are not in any way resistant to the idea of data quality assessment, but any such assessment should at the very least adhere to certain basic analytical standards and ought to be carried out in a proper scientific manner. We were not contacted prior to this article being accepted for publication. Had we been asked to comment, we could have easily cleared up the many inaccuracies and misinterpretations that litter the George et al. paper. Having said this, however, it is unclear whether the authors would then have been able to draw any meaningful conclusions other than that HGMD has succeeded in providing fairly comprehensive coverage of its target data viz. mutations in human nuclear genes causing inherited human disease. Thus, it would appear that far from providing evidence for the shortcomings of a central mutation database, George et al. have inadvertently succeeded in demonstrating that HGMD fulfils this role exceptionally well.
In their recent article, Rappold et al. (1) investigated the presence of SHOX defects in a large cohort of 1,608 short stature children, and found 58% of SHOX mutations/deletions in 55 children with Leri-Weill
dyschondrosteosis (LWD) and 2.2% in 1,534 cases considered to have idiopathic short stature. The authors created an evidence-based scoring system based on clinical grounds obtained from the 68 patien...
In their recent article, Rappold et al. (1) investigated the presence of SHOX defects in a large cohort of 1,608 short stature children, and found 58% of SHOX mutations/deletions in 55 children with Leri-Weill
dyschondrosteosis (LWD) and 2.2% in 1,534 cases considered to have idiopathic short stature. The authors created an evidence-based scoring system based on clinical grounds obtained from the 68 patients with SHOX defects to identify the most appropriate children for SHOX gene testing. The following criteria were used: arm span/height ratio < 96.5%, sitting height/height ratio > 55.5%, body–mass index > 50th percentile and the presence of cubitus valgus, short forearm, bowing of the forearm, appearance of muscular hypertrophy and/or dislocation of the ulna. This score system presents some limitations, such as a low positive predictive value (11%) when using the lower cutoff (score of 4) and a lower sensitivity (61%) when using the upper score (score of 7 of a maximum of 24).
To select among children with short stature, those likely to have mutations in SHOX gene, previous studies have already suggested that an extremities-trunk ratio, [(calculated subischial leg length + arm span)/sitting height] (2) and sitting height/height ratio (SH/H),
expressed as standard deviation score for age and sex (SDS) (3). Rappold et al. (1) analyzed the SH/H ratio as absolute values, even though their cohort presented a wide age range, and age is known to strongly influence this ratio (4).
It would be useful if Rappold et al. report the extremities-trunk ratio proposed by Binder et al. (2) and SH/H ratio expressed as SDS (4) in this large cohort of patients with SHOX mutations. These parameters could
also improve the proposed score system.
FOOTNOTES:
Competing interests: none declared
References:
1.Rappold G., Blum W.F., Shavrikova E.P., Crowe B.J., Roeth R., Quigley C.A., Ross J.L., Niesler B. Genotypes and phenotypes in children with short stature: clinical indicators of SHOX haploinsufficiency. J Med Genet (2007) 44:306-13
2.Binder G., Ranke M.B., Martin D.D. Auxology is a valuable instrument for the clinical diagnosis of SHOX haploinsufficiency in school -age children with unexplained short stature. J Clin Endocrinol Metab (2003) 88:4891-6
3.Jorge A.A., Souza S.C., Nishi M.Y., Billerbeck A.E., Liborio D.C., Kim C.A., Arnhold I.J., Mendonca B.B. SHOX mutations in idiopathic short stature and Leri-Weill dyschondrosteosis: frequency and phenotypic variability. Clin Endocrinol (Oxf) (2007) 66:130-5
4.Gerver W.J.M., Bruin R. (2001) Paediatric Morphometrics. A reference manual, 2nd ed. Universitaire Pers Maastricht, Maastricht
We wish to reply to the interesting comments concerning our paper on phenocopies in families positive for mutations in BRCA1/2 genes since its e publication in October 2006 [1]. We understand the reservations about changing practice in reassuring individuals who test negative for a family
mutation based on one largely retrospective analysis of families and clearly there is a need to confirm our results in other l...
We wish to reply to the interesting comments concerning our paper on phenocopies in families positive for mutations in BRCA1/2 genes since its e publication in October 2006 [1]. We understand the reservations about changing practice in reassuring individuals who test negative for a family
mutation based on one largely retrospective analysis of families and clearly there is a need to confirm our results in other large series. We were particularly careful to obviate potential biases in our analyses. We would prefer that the interpretation of our article is based on the final
detailed analysis of type A1 phenocopies which yielded a relative risk of three fold, equivalent to a doubling of lifetime risk. We would not suggest screening before 35 years for individuals in this category and certainly not as early as suggested in one response [2]. We agree that ultimately our study needs to be confirmed in prospective analysis, before widespread change in practice. However, we are convinced that two potential biases do not contribute substantially to our original figures [2-4]. We were also concerned that identification of families for mutation testing could be because of high-risk selection finds more families with chance breast cancers [2,3]. If this were the case the ratio of first- degree relatives (FDR) with breast cancer testing negative for the family mutation before family ascertainment should be higher than afterwards. We have carried out an analysis of our enhanced dataset now containing 52 breast cancer phenocopies. The ratio of phenocopies amongst FDR remains constant at 17% both before family ascertainment, after family ascertainment and after a mutation has been identified in the family. We also do not believe that extra mammography has made a substantial contribution [4]. The majority of phenocopy cancers were not detected by screening mammography and in particular after genetic testing women were
discharged from extra mammographic surveillance which may have had the opposite effect by removing the lead time to diagnosis (if involved in screening there would be a delay to diagnosis if screening is stopped). More detailed analysis is under way in order to help determine which family structures are likely to contain phenocopies and where the extra risk pertains [3].
References 1. Smith A, Moran A, Boyd MC, Bulman M, Shenton A, Smith L, Iddenden I, Woodward E, Lalloo F, Rahman N, Maher ER, Evans DGR. The trouble with phenocopies: are those testing negative for a family BRCA1/2 mutation really at population risk? J Med Genet 2007; 44: 10-15
2. Tilanus-Linthorst M. No screening yet after a negative test for the family mutation. J Med Genet 2006 e
3. Goldgar D, Venne V, Conner T, Buys S BRCA Phenocopies or Ascertainment Bias? J Med Genet 2007e
4. Eisinger F. Phenocopies: actual risk or self-fulfilling prophecy? J Med Genet 2007e
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...
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...
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...
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...
I was most interested to read the paper of Iwaki et al. on ‘SCA16’, in a large ataxia kindred with a deletion of the ITPR1 gene 1.
SCA15 has been a close interest of our group, going from the study of the original family that defined the condition, to the recent discovery of the ITPR1 gene as its basis2 3 4 5.
It is interesting and useful information from Iwaki et al. that the...
Dear Editor
Prevous studies have demonstrated that the prevalence rate of R1195Q in SCN5A gene ranges from 0.2% to 12% and suggested this mutation may be a risk factor for long QT syndrome (LQTS) [1,2]. However, Chen et al showed no association between R1193Q and the disease process or ECG abnormalities in a four-generation Chinese family with cardiac conduction abnormalities and sudden death[1].
We recently id...
We write in response to a number of very specific criticisms of the Human Gene Mutation Database (HGMD) made in the recently published article of George et al. [PMID: 17893115]. All seven claims made were amenable to empirical testing. Having tested these claims, we find all of them to be either false or highly misleading. In the text that follows, we refute or rebut each claim in turn.
HGMD represents an...
Dear Editor
In their recent article, Rappold et al. (1) investigated the presence of SHOX defects in a large cohort of 1,608 short stature children, and found 58% of SHOX mutations/deletions in 55 children with Leri-Weill dyschondrosteosis (LWD) and 2.2% in 1,534 cases considered to have idiopathic short stature. The authors created an evidence-based scoring system based on clinical grounds obtained from the 68 patien...
We wish to reply to the interesting comments concerning our paper on phenocopies in families positive for mutations in BRCA1/2 genes since its e publication in October 2006 [1]. We understand the reservations about changing practice in reassuring individuals who test negative for a family mutation based on one largely retrospective analysis of families and clearly there is a need to confirm our results in other l...
Pages