Location of a major susceptibility locus for familial schizophrenia on chromosome 1q21-q22

Science

Volumn 288, Issue 5466, 2000, Pages 678-682

  Brzustowicz, Linda M ^a   Hodgkinson, Kathleen A ^a   Chow, Eva W C ^a   Honer, William G ^a   Bassett, Anne S ^a  

^a NONE

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CHROMOSOME 1Q; GENE LOCUS; GENETIC SUSCEPTIBILITY; HUMAN; MOLECULAR CLONING; PRIORITY JOURNAL; SCHIZOPHRENIA;

CHROMOSOME MAPPING; CHROMOSOMES, HUMAN, PAIR 1; COMPUTER SIMULATION; FEMALE; GENES, DOMINANT; GENES, RECESSIVE; GENETIC HETEROGENEITY; GENETIC MARKERS; GENETIC PREDISPOSITION TO DISEASE; HUMANS; LIKELIHOOD FUNCTIONS; LINKAGE (GENETICS); LOD SCORE; MALE; MODELS, GENETIC; PEDIGREE; SCHIZOPHRENIA;

EID: 0034724924     PISSN: 00368075     EISSN: None     Source Type: Journal    
DOI: 10.1126/science.288.5466.678     Document Type: Article

References (44)

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18. Informed consent was obtained from all subjects after an explanation of possible consequences. Protocols were approved by the Institutional Review Boards of Rutgers University and the University of Toronto. Direct interviews conducted with the Structured Clinical Interview from DSM-III-R (SCID-I) for major disorders and the SCID-II for personality disorders, collateral information, and medical records were used for 297 subjects to make consensus diagnoses based on DSM-III-R criteria from American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders: DSM-III-R (American Psychiatric Association, Washington, DC, rev. ed. 3, 1987). Details of the diagnostic and ascertainment methods have been described (16, 17). Seven additional deceased subjects received consensus diagnoses on the basis of medical records and collateral information. The diagnostic classifications "narrow" and "broad" were used, with 79 and 123 affected individuals in each category, respectively. Individuals were considered affected under the narrow diagnostic classification if they were diagnosed with schizophrenia or chronic schizoaffective disorder. Individuals were considered affected under the broad diagnostic classification if they had been diagnosed with one of those disorders or with a nonaffective psychotic disorder, schizotypal personality disorder, or paranoid personality disorder. Two subjects were coded as diagnosis unknown, because mental retardation hindered full assessment. Five of the deceased subjects were coded as affected under the broad diagnostic classification but unknown under the narrow classification, as conclusive narrow diagnostic elements could not be obtained. Full diagnoses were available on the remaining 297 subjects, and all individuals not categorized as affected under a given diagnostic scheme were classified as unaffected.
19. DNA was extracted from blood samples or lymphoblastoid cell lines using the GenePure system (Gentra Systems). DNA from each subject was genotyped by means of 381 markers from the Weber version 6.0 Screening Set. Genotyping was conducted in our laboratory and the laboratories of the Center for Inherited Disease Research (CIDR; Johns Hopkins University, Baltimore, MD). In our laboratory, genotypes were generated by polymerase chain reaction (PCR) amplification incorporating radiolabeled dCTP. Sample handling, PCR amplification, gel electrophoresis, and genotype interpretation procedures have been described [L. M. Brzustowicz et al. Am. J. Hum. Genet. 61, 1388 (1997)]. Genotype generation by CIDR was based on automated fluorescent microsatellite analysis, with further details available at the CIDR Web site [www.cidr.jhmi.edu/].
20. Standard parametric likelihood analysis was performed by means of FASTLINK [R. W. Cottingham Jr., R. M. Idury, A. A. Schaffer, Am. J. Hum. Genet. 53, 252 (1993)] for two-point linkage and VITESSE [J. R. O'Connel and D. E. Weeks, Nature Genet. 11, 402 (1995)] for multipoint linkage analysis. Multipoint analysis has the advantage of utilizing data from multiple linked markers to maximize the information in a given pedigree and may also provide better localization of the linked locus. The admixture test as implemented in HOMOG [41, pp. 220-226] was used to test for genetic heterogeneity. To minimize inaccuracies due to errors in pedigree structure, including undetected nonpaternity, branches of extended pedigrees that were connected through more than one individual without available DNA were removed from the main pedigrees and analyzed as separate pedigrees. This resulted in three small branches (total of 23 individuals) being removed from three pedigrees. After this pruning, 89 individuals with no diagnostic or genotype information were needed to accurately represent the pedigree structures of the entire dataset.
21. Standard parametric likelihood analysis was performed by means of FASTLINK [R. W. Cottingham Jr., R. M. Idury, A. A. Schaffer, Am. J. Hum. Genet. 53, 252 (1993)] for two-point linkage and VITESSE [J. R. O'Connel and D. E. Weeks, Nature Genet. 11, 402 (1995)] for multipoint linkage analysis. Multipoint analysis has the advantage of utilizing data from multiple linked markers to maximize the information in a given pedigree and may also provide better localization of the linked locus. The admixture test as implemented in HOMOG [41, pp. 220-226] was used to test for genetic heterogeneity. To minimize inaccuracies due to errors in pedigree structure, including undetected nonpaternity, branches of extended pedigrees that were connected through more than one individual without available DNA were removed from the main pedigrees and analyzed as separate pedigrees. This resulted in three small branches (total of 23 individuals) being removed from three pedigrees. After this pruning, 89 individuals with no diagnostic or genotype information were needed to accurately represent the pedigree structures of the entire dataset.
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26. A = 0.10, f(AA) = 0.60, f(Aa) = 0.01, and f(aa) = 0.01. For X-linked markers, the same penetrances were used for females, with f(aa) used for f(a) and f(Aa) used for f(A) for males for the dominant models, and f(AA) used for f(A) for the recessive models. Marker allele frequencies were estimated with a set of 30 unrelated subjects from these families.
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30. We generated 2500 unlinked "replicates" (datasets with the pedigree structures and diagnoses of the actual study coupled with genotype data simulated without regard to diagnostic status) of the full genome scan using SIMULATE [J. D. Terwitliger, M. Speer, J. Ott, Genet. Epidemiol. 10, 217 (1993)]. Analysis was as for the actual study data (20), except that only two-point analysis was conducted. Two distributions of maximum lod scores were constructed, using the highest score from each replicate under homogeneity (LOD) and under heterogeneity (HLOD). The highest score obtained was 5.08. The P values corresponding to LODs and HLODs of 3, 4, and 5 were calculated from the distributions and BINOM was used to determine the 95% confidence intervals (Cls) for those values [(41), pp. 48-50]. The P values [95% Cl] for LODs of 3, 4, and 5 were 0.099 [0.087-0.11], 0.012 [0.0078-0.017], and 0.0008 [0.0001-0.0029], respectively. For HLODs of 3, 4, and 5 the P values were 0.16 [0.14-0.17], 0.016 [0.012-0.022], and 0.0008 [0.0001-0.0029], respectively. The estimates for a score of 5 were based on only two observations, producing the wide Cl, and reflecting the difficulty in estimating rare events.
31. Linked replicates were generated using SLINK [J. Ott, Proc. Natl. Acad. Sci. USA 86, 4175 (1999); D. E. Weeks, J. Ott, G. M. Lathrop, Am. J. Hum. Genet. 47, A204 (1990)]. A single marker 5 cM from the disease gene and with four alleles of equal frequency was simulated. Each of the four genetic models (25) was used to generate 250 replicates with 100%, 95%, 90%, 75%, or 50% of families linked. Two-point analysis was conducted on each replicate with all four generating models under homogeneity and heterogeneity. As expected, the highest expected lod (ELOD) scores were obtained when the analysis model matched the generating model. Incorrect mode of inheritance reduced the ELODs much more than incorrect diagnostic model (31). Power to detect linkage at P = 0.05 with the correct model was excellent (>75%) under all models with 90% or more of families linked. With 100% of families linked, even the least powerful model, recessive-narrow, produced an ELOD of 5.6, with 40% of replicates producing a lod of 6 or higher. Power for all models dropped to 50 to 75% when 75% of families were linked. Power to detect linkage was very poor (<35%) when only 50% of families were linked, regardless of the model used.
32. Linked replicates were generated using SLINK [J. Ott, Proc. Natl. Acad. Sci. USA 86, 4175 (1999); D. E. Weeks, J. Ott, G. M. Lathrop, Am. J. Hum. Genet. 47, A204 (1990)]. A single marker 5 cM from the disease gene and with four alleles of equal frequency was simulated. Each of the four genetic models (25) was used to generate 250 replicates with 100%, 95%, 90%, 75%, or 50% of families linked. Two-point analysis was conducted on each replicate with all four generating models under homogeneity and heterogeneity. As expected, the highest expected lod (ELOD) scores were obtained when the analysis model matched the generating model. Incorrect mode of inheritance reduced the ELODs much more than incorrect diagnostic model (31). Power to detect linkage at P = 0.05 with the correct model was excellent (>75%) under all models with 90% or more of families linked. With 100% of families linked, even the least powerful model, recessive-narrow, produced an ELOD of 5.6, with 40% of replicates producing a lod of 6 or higher. Power for all models dropped to 50 to 75% when 75% of families were linked. Power to detect linkage was very poor (<35%) when only 50% of families were linked, regardless of the model used.
33. Supplementary data on the power simulations can be found in Web table 1 at www.sciencemag.org/ feature/data/1047911.shl
34. It is impractical to use simulations to estimate the probability of very rare events, such as obtaining a high lod score by chance. Therefore, the significance of lod scores >5 was determined by statistical methods. Twice the natural logarithm of the likelihood ratio asymptotically approaches the chi-square distribution as sample size increases. The simulation results under no linkage were used to test the adequacy of the chi-square approximation for this study sample. As marker density was less than 8 cM, the 381 markers were treated as independent tests, as were the two modes of inheritance [(41), pp. 75-79]. As the two diagnostic classifications were not independent, bounding P values were calculated from the chi-square with 1 d.f. by considering these as either one or two tests. For a lod of 3, under homogeneity, this produced a range for the P value of 0.077-0.155, which contained the simulation-derived P value estimate of 0.099. Similar results confirming the adequacy of the chi-square were obtained for lods of 4 and 5. Under heterogeneity the appropriate chi-square has >1 but <2 d.f., so the same approach of calculating bounding values for the P value was used, producing similar agreement with the results of the simulations. For a lod of 6.50 under heterogeneity, this produced a range for the P value of 0.00002 to 0.0002. Although the simulation results suggest that the actual P value is much closer to the smaller end of this interval, P values were conservatively reported as less than the calculated upper bound.
35. Supplementary data on all two-point analyses can be found in Web table 2 at www.sciencemag.org/ feature/data/1047911.shl
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44. We would like to thank the participating families, whose contributions have made these studies possible; R. Forsythe and P. Forsythe for years of support; J. Hayter, M. Kahn, D. Little, J. Hogan and D. Hayden for technical assistance; J. Ott and V. Vieland for advice on statistical issues. Supported by the Medical Research Council of Canada (A.S.B., L.M.B., W.G.H.), the EJLB Foundation Scholar Research Programme (L.M.B.), the National Institute of Mental Health grant K08 MH01392 (L.M.B.), the Ontario Mental Health Foundation (A.S.B.), the Bill Jeffries Schizophrenia Endowment Fund (A.S.B.), Nova Scotia Schizophrenia Society (A.S.B.), and the Ian Douglas Bebensee Foundation (A.S.B.). W.G.H. is supported by a Vancouver Hospital Scientist Award. Genotyping services were provided by the Center for Inherited Disease Research (CIDR). CIDR is fully funded through a contract from the National Institutes of Health to Johns Hopkins University, Contract Number N01-HG-65403.