Dear Editor,

We have read with great interest the excellent review entitled: "Genetics of familial intrahepatic cholestasis syndromes" by van Mil S. W. C. and collaborators, and published in the last issue of Journal of Medical Genetics. [1] In an attempt to complete this very exhaustive review, we wished to make a few comments:

- concerning delta4-3-Oxosteroid-5beta reductase (AKR1D1) deficiency, since the human gene (AKR1D1, also named SRD5B1) was cloned, two recent publications [2,3] report 5 SRD5B1 mutations responsible for delta4-3- Oxosteroid-5beta reductase deficiency in 5 patients. These data confirm that the disease is transmitted in a recessive autosomal pattern, and show that when delta4-3-Oxosteroid-5beta reductase deficiency is suspected on the basis of mass spectrometry analysis of urinary bile acids, diagnosis can be confirmed by molecular biology technology. This new diagnostic tool is important because patients with other severe liver diseases may present an abnormal concentration of bile acids with 3-oxo-delta4 nuclear structure secondary to liver failure and not due to genetically determined enzyme defect.[4] So far it is admitted that only patients with a primary genetic defect may benefit from early primary bile acid therapy in order to try to correct liver failure and to avoid liver transplantation.[2,3]

- concerning HSD3B7 deficiency, in our experience the patients never exhibit pruritus at presentation and during the disease course. Iatrogenic pruritus may occur under cholic acid therapy in case of accidental overdose. We therefore believe that absence of pruritus in presence of cholestasis features is a strong sign indicating a possible primary bile acid synthesis defect.[5,6] Since the first report in 2000 of a patient harbouring homozygous HSD3B7 mutation, additional mutations have been identified in 15 patients.[6]

We hope these additional informations will favourably complete this excellent review.

Emmanuel Gonzales, M. D.
Emmanuel Jacquemin, M. D., Ph. D. Pediatric Hepatology, Bicêtre Hospital, AP-HP, University of Paris XI,
Paris , France

References

1. van Mil SW, Houwen RH, Klomp LW. Genetics of familial intrahepatic cholestasis syndromes. J Med Genet 2005;42(6):449-63.
2. Lemonde HA, Custard EJ, Bouquet J, Duran M, Overmars H, Scambler PJ, Clayton PT. Mutations in SRD5B1 (AKR1D1), the gene encoding delta(4)-3-oxosteroid 5beta-reductase, in hepatitis and liver failure in infancy. Gut 2003;52(10):1494-9
3. Gonzales E, Cresteil D, Baussan C, Dabadie A, Gerhardt MF, Jacquemin E. SRD5B1 (AKR1D1) gene analysis in delta(4)-3-oxosteroid 5beta-reductase deficiency: evidence for primary genetic defect. J Hepatol 2004;40(4):716-8.
4. Clayton PT, Patel E, Lawson AM, Carruthers RA, Tanner MS, Strandvik B et al. 3-oxo-delta4 bile acids in liver disease. Lancet 1988;1:1283-4.
5. Jacquemin E, Setchell KDR, O’Connell NC, Estrada A, Maggiore G, Schmitz J, Hadchouel M, Bernard O. A new cause of progressive intrahepatic cholestasis: 3beta-hydroxy-C27-steroid dehydrogenase/isomerase deficiency. J Pediatr 1994;125:379-84.
6. Cheng JB, Jacquemin E, Gerhardt M, Nazer H, Cresteil D, Heubi JE, Setchell KDR, Russell DW. Molecular genetics of 3beta-hydroxy-delta5-C27- steroid oxidoreductase deficiency in 16 patients with loss of bile acid synthesis and liver disease. J Clin Endocrinol Metab 2003;88:1833-41.

Dear Editor,

In the recently published report "Analysis of RUNX1 Binding Site and RAPTOR Polymorphisms in Psoriasis: No Evidence for Association Despite Adequate Power and Evidence for Linkage"[1] the authors report failure to see association of psoriasis susceptibility to a region of chromosome 17q25. This region was first identified with linkage analysis by our group[2], and we recently reported evidence for association to two unlinked loci from this chromosomal region.[3] In this instance one associated SNP allele leads to loss of a putative RUNX binding site. It is important to address the approach and findings of Stuart et al. (2005)[1] since they omit important factors that may be required for replicating associations between genetic loci and complex traits:

1) The statement about adequate power in the title, and the discussion in the text is misleading. The power these authors report is only accurate for the parameters they considered. They fail to consider the inherent heterogeneity of a disease such as psoriasis and do not incorporate a number of critical parameters into their power analyses. These include: (i) locus heterogeneity, (ii) disequilibrium (r2) less than 1.0, (iii) phenotype and/or genotype misclassification and (iv) the effects and interactions of environmental risk factors with genetic factors (currently unknown for complex traits). All are realistic factors and all can substantially reduce power to detect either linkage and/or association.[4-15]

2) The issue of genetic heterogeneity is of great importance in complex human disease genetics. It has been demonstrated that sample size needed to replicate a positive linkage study exceeds, by a considerable margin, the original sample size, particularly when factors such as heterogeneity are involved.[16] Effect sizes in published positive studies tend to be inflated over what one gets after much more data collection.[17] Such studies are simply more fortunate with respect to the component of the study that leads to publication, but it does not mean that they are false positive results. Since Stuart et al. (2005) did not include heterogeneity into their power calculations they cannot have addressed this issue.

3) Genotype misclassification seems particularly relevant in this work. The authors comment that they reconstructed haplotypes using the methods implemented in Merlin and PHASE (with the exception of FBAT). This reconstruction was done to address issues about inflation in type I error due to SNP markers that are not in linkage equilibrium. However, it has been well documented that haplotype reconstruction methods such as these are prone to misclassification18, and that misclassification probabilities may be large for nuclear families like those studied in this work.[19]

4) It is not clear why the authors did not perform a TDT analysis using all the affected individuals in the pedigrees, i.e. perform a linkage analysis with the tightly linked markers? The authors report that they had 1,285 affected individuals in total. Yet, they chose to perform an association analysis with TDT, therefore using a maximum of 351 trios (Table 1), or less than 1/3 of the available data. The TDT linkage analysis using all affecteds was the analysis performed in our study[3] and so without a corresponding analysis on their part, a direct comparison is not possible. It is also interesting that although the ratios of transmitted to untransmitted alleles are by no means significant in the study of Stuart et al. (2005) there is a trend in all pedigrees in the direction we report: (for SNP9/rs734232 the ratio of the associated A allele in transmitted versus non-transmitted chromosomes is 235:219).

5) Another issue that could be relevant is the pedigree ascertainment. Although the ratio of sampled affected to unaffected individuals in the pedigrees in our study[3] does not appear to be very different from the same ratio in the pedigrees of Stuart et al. (2005)[1], there could also be an effect if there is a difference in the way the pedigrees come to attention in the two studies. It is possible that the complete pedigrees (including unsampled individuals) are larger with more affected individuals in the former study[3] than in the latter.[1] The two samples could then end up with different fractions of a particular risk haplotype. A comparison of haplotype frequencies obtained by Stuart et al. (2005)[1] and Helms et al. (2003)[3] does indeed suggest some systematic difference between the data sets and/or analyses. Stuart et al. (2005)[1] state that the combined frequency for the two most common haplotypes was between .992-.999 for the two regions (depending somewhat on methods of reconstruction). In the study from Helms et al. (2003)[3] , the combined frequency of the two most common haplotypes on non-transmitted chromosomes was 0.94-0.95. This suggests either that the reconstructions are flawed, or that the samples differ. The difference could either lead to difference in power, since if one has more different haplotypes there may be more informative transmissions. Alternatively it could indicate a fundamental sampling difference.

6) Given that we report five SNPs driving association in our families, it is surprising that Stuart et al. (2005)[1] did not attempt to examine the haplotypes determined by more than just three associated SNPs. As we report, in a case/control study, evidence for association with associated haplotypes demarcated by these five driving SNPs was greater than with single SNPs.[3]

7) Stuart et al. (2005)[1] also state that "only one marker in this peak exceeded the p=0.05 level of significance after the most stringent level of correction for multiple testing", making independent confirmation critical. However, our level of correction for multiple testing employed the FDR method[20,21], because employing a Bonferroni correction for association studies with multiple SNPs is considered excessively conservative, generally obliterating any signal in large-scale associations studies. With the FDR method, nine markers in the SLC9A3R1/NAT9 remained significant. There are several other studies reporting that adjusting for multiple testing in studies is less important than other concerns.[22,23]

8) A final general comment is warranted. We believe that chromosome 17q25 may harbor a number of loci for psoriasis susceptibility. The issue of clustering of genes for complex traits has been reported by others[24,25], and is thought to facilitate identification of susceptibility loci with linkage analyses. Stuart et al. (2005) also see linkage of psoriasis to 17q25, in a region harboring the putative RUNX site downstream from SLC9A3R1/ NAT9 and in a region distinct from that seen in two independent studies of large multiplex families[2,26], but where we also see linkage in our large set of nuclear families.[3] Previous studies with simulation data suggest that single major gene analysis of complex traits has good power to localize genes to a specific chromosome, but power to localize beyond the chromosomal level may be significantly compromised.[27] A full understanding of the contribution of different susceptibility factors from this region will be necessary as we seek to understand the genetic complexity of this disease.

C Helms¹
L Cao¹
JG Krueger²
EM Wijsman³
F Chamian²
D Gordon⁴
M Heffernan⁵
JA Wright-Daw¹
J Robarge¹
J Ott⁴
P-Y Kwok⁶
A Menter⁷
AM Bowcock¹

¹Department of Genetics
Washington University School of Medicine
St. Louis
Missouri, 63110, USA.

²Laboratory for Investigative Dermatology
The Rockefeller University
New York
NY 10021, USA.

³Div. of Medical Genetics and Dept. Biostatistics
University of Washington
Seattle
Washington, 98195, USA.

⁴Lab of Statistical Genetics
The Rockefeller University
New York
NY 10021, USA.

⁵Div. Of Dermatology
Washington University School of Medicine
St. Louis
Missouri, 6310, USA.

⁶Department of Dermatology
Cardiovascular Research Institute, and Center for Human Genetics
University of California
San Francisco
CA 94143, USA.

⁷Department of Internal Medicine
Division of Dermatology
Baylor University Medical Center
Dallas
Texas, 75246 USA.

*Correspondence should be addressed to A.M.B. (email: bowcock@genetics.wustl.edu).

References

1. Stuart P, Nair RP, Abecasis GR, Nistor I, Hiremagalore R, Chia NV, Qin ZS, Thompson RA, Jenisch S, Weichenthal M, Janiga J, Lim HW, Christophers E, Voorhees JJ, Elder JT. Analysis of RUNX1 binding site and RAPTOR polymorphisms in psoriasis: No evidence for Association Despite Adequate power and Evidence for linkage. J Med Genet 2005 (online publication).

2. Tomfohrde J, Silverman A, Barnes R, Fernandez-Vina MA, Young M, Lory D, Morris L, Wuepper KD, Stastny P, Menter, A. Gene for familial psoriasis susceptibility mapped to the distal end of human chromosome 17q. Science 1994;264:1141-5.

3. Helms C, Cao L, Krueger JG, Wijsman EM, Chamian F, Gordon D, Heffernan M, Daw J, Robarge J, Ott J, Kwok P-Y, Menter A, Bowcock AM. A putative RUNX1 binding site variant between SLC9A3R1 and NAT9 is associated with susceptibility to psoriasis. Nat Genet 2003;35:349-56.

4. Sillanpaa MJ, Auranen K. Replication in genetic studies of complex traits. Ann Hum Genet 2004;68:646-57.

5. Bross I. Misclassification in 2 x 2 tables. Biometrics 1954;10:478-86.

6. Mote VL, Anderson RL. An investigation of the effect of misclassification on the properties of chisquare-tests in the analysis of categorical data. Biometrika 1965;52:95-109.

7. Cochran WG. Errors of measurement in statistics. Technometrics 1968;10:637-666.

8. Ott J. Analysis of human genetic linkage: Johns Hopkins, Baltimore, 1999.

9. Gordon D, Matise TC, Heath SC, Ott J. Power loss for multiallelic transmission/disequilibrium test when errors introduced: GAW11 simulated data. Genet Epidemiol Suppl 1999;17:S587-S92.

10. Gordon D, Heath SC, Liu X, Ott J. A transmission/ disequilibrium test that allows for genotyping errors in the analysis of single-nucleotide polymorphism data. Am J Hum Genet 2001;69:371-80.

11. Gordon D, Finch SJ, Nothnagel M, Ott J. Power and sample size calculations for case-control genetic association tests when errors are present: application to single nucleotide polymorphisms. Hum Hered 2002;54:22-33.

12. Gordon D, Haynes C, Johnnidis C, Patel SB, Bowcock AM, Ott J. A transmission disequilibrium test for general pedigrees that is robust to the presence of random genotyping errors and any number of untyped parents. Eur J Hum Genet 2004;12:752-61.

13. Zou G, Zhao H. The impacts of errors in individual genotyping and DNA pooling on association studies. Genet Epidemiol 2004;26:1-10.

14. Zheng G, Tian X. The impact of diagnostic error on testing genetic association in case-control studies. Stat Med 2005;24:869- 82.

15. Edwards BJ, Haynes C, Levenstien MA, Finch SJ, Gordon D. Power and sample size calculations in the presence of phenotype errors for case/control genetic association studies. BMC Genet 2005;6:18.

16. Suarez BK, Hampe CL, van Eerdewegh P. Problems of replicating linkage claims in psychiatry. Washington: American Psychiatric Press, 1994.

17 Goring HHH, Terwilliger JD, Blangero J (2001) Large upward bias in estimation of locus-specific effects from genomewide scans Am J Hum Genet 69:1357-1369.

18. Niu T. Algorithms for inferring haplotypes. Genet Epidemiol 2004;27:334-347.

19. Lindholm E, Zhang J, Hodge SE, Greenberg DA. The reliability of haplotyping inference in nuclear families: misassignment rates for SNPs and microsatellites. Hum Hered 2004;57:117-127.

20. Benjamini Y, Yekutieli D. Quantitative Trait Loci Analysis using the False Discovery Rate. Genetics 2005.

21. Benjamini Y, Drai D, Elmer G, Kafkafi N, Golani I. Controlling the false discovery rate in behavior genetics research. Behav Brain Res 2001;125:279-84.

22. Perneger TV. Adjusting for multiple testing in studies is less important than other concerns. BMJ 1999;318:1288.

23. Witte JS, Elston RC, Schork NJ. Genetic dissection of complex traits. Nat Genet 1996;12:355-6.

24. Morel L, Blenman KR, Croker BP, Wakeland EK. The major murine systemic lupus erythematosus susceptibility locus, Sle1, is a cluster of functionally related genes. Proc Natl Acad Sci, USA 2001;98:1787-92.

25. Adeniji OA, Mrug MM, DiPalma JA. Not one but two inflammatory bowel disease susceptibility loci map to chromosome 16. Am J Gastroenterol 2002;97:2464-5.

26. Hwu WL, Yang CF, Fann CS, Chen CL, Tsai TF, Chien YH, Chiang SC, Chen CH, Hung SI, Wu JY, Chen YT. Mapping of psoriasis to 17q terminus. J Med Genet 2005;42:152-8.

27. Gordon, D., Hoh, J., Finch, S.J., Levenstien, M.A., Edington, J., Li, W., Majewski, J. and Ott, J. Two approaches for consolidating results from genome scans of complex traits: selection methods and scan statistics. Genet Epidemiol 2001;21 Suppl 1, S396-402.

Dear Editor,

We are studying the genetic basis of non-syndromic hearing loss in North Indian population and we performed the PCR-RFLP assay described by authors for the detection of W24X mutation in this article. The assay was carried out using the primers (1F and 1R) and the restriction enzyme Alu1, as described by the authors. However, we have observed a distinctly different RFLP pattern for this mutation as compared to that reported by Ramshankar et al, 2003.

The authors have reported that the presence of W24X mutation introduces an Alu1 restriction site. According to them, Alu1 digestion of 286bp PCR amplified product from unaffected subjects produces a single fragment of 286bp, whereas the presence of W24X mutation in homozygous genotype would produce two fragments of 182bp and 104bp and in W24X heterozygotes, it would generate three fragments of 286bp, 182bp and 104bp.

However, we observed that the presence of W24X mutation in homozygous state produced three fragments of 168bp 104bp and 14bp, whereas in W24X heterozygotes we found four fragments of 272bp, 168bp 104bp and 14bp, which suggested that there may be an additional Alu1 site in the 286bp PCR product. An in-silico PCR amplification followed by restriction digestion using REBASE (http://rebase.neb.com) showed that the 286bp fragment amplified by the given primers carries another Alu1 restriction site independent of the one created by the presence of W24X mutation (Fig.1).

Hence, even in the absence of W24X mutation, the Alu1 restriction digestion of 286 amplicon gives two fragments of 272bp and 14bp (Fig.2). Indeed, we have observed these RFLP patterns in control and W24X positive samples. Thus, our results confirm the presence of an additional Alu1 site in the 286bp amplified PCR product giving RFLP pattern different from that reported by these authors.

Figure 1. Alu1 restriction sites in 286bp amplicon (Part of NC_004004).

Figure 2. RFLP patterns for W24X mutation.

Dear Editor

In accordance with the findings reported by Kadakol et al. (1) we found in a population study,(2) done in Malays, two cases of neonatal jaundice (NNJ)with a combination of a mutation in the encoding region of the UGT1A1 gene and the classical Gilbert syndrome mutation.

These two patients had severe early onset NNJ, only slowly responding to intensive phototherapy. Both babies had a normal G6PD status and were feeding well. Their respective mothers had each blood group O positive and each baby had blood group B positive with a negative direct Coombs test. Liver tests other than bilirubin levels were normal. Three mutations in the UGT1A1 gene were tested (the A(TA)7TAA mutation, the G71R mutation which is commonly causing Gilbert Syndrome in Taiwanese and Japanese and the G493R mutation which was recently found in 2 related Malay patients with NNJ)(2). Each baby was found to have two mutations: the A(TA)7TAA mutation and the G71R mutation. None had the G493R mutation.

The cases reported here underline the importance of the findings reported by Kadakol et al.(1). The two patients would have been labeled as having ABO-incompatibility if the genetic testing would have not been performed. Especially in Southeast Asian populations where the incidence of neonatal jaundice is very high, routine screening for mutations in the UGT1A1 gene may be useful. It may help in genetic counseling of the parents and in prevention of kernicterus in coutries with an early neonatal discharge policy.

References: 1. Kadakol A, Sappal BS, Ghosh SS, Lowenheim M, Chowdhury A, Chowdhury S, Santra A, Arias IM, Chowdhury JR, and Chowdhury NR. Interaction of coding region mutations and the Gilbert-type promoter abnormality of the UGT1A1 gene causes moderate degrees of unconjugated hyperbilirubinaemia and may lead to neonatal kernicterus. J Med Genet 2001; 38: 244-249

2.Yusoff S, Van Rostenberghe H, Yusoff NM, Talib NA, Ramli N, Ismail NZ, Ismail WP, Matsuo M, Nishio H. Frequencies of A(TA)(7)TAA, G71R, and G493R Mutations of the UGT1A1 Gene in the Malaysian Population. Biol Neonate. 2005 Oct 6;89(3):171-176 [Epub ahead of print]