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1.  Klinefelter’s Syndrome, 47,XXY, in Male Systemic Lupus Erythematosus Supports a Gene Dose Effect from the X Chromosome 
Arthritis and rheumatism  2008;58(8):2511-2517.
Background
Systemic lupus erythematosus (SLE) is a systemic autoimmune disease that predominantly affects women. Despite Klinefelter's syndrome (47,XXY) and SLE coexisting in isolated cases, no association has been established with SLE or any other autoimmune disease. Methods: Sex chromosome genotyping was performed in 981 SLE patients (213 were men). A first group of 843 SLE patients from 378 multiplex families and a second group of 138 men with non-familial SLE were evaluated. Fluorescent in situ hybridization (FISH) and karyotyping in transformed B cell lines enumerated chromosomes for selected cases.
Results
Of 213 men with SLE, five had Klinefelter's syndrome (or 1 in 43). Four of them were heterozygous at X markers. FISH and karyotyping confirmed Klinefelter’s syndrome in the fifth. An overall rate of 235 47,XXY per 10,000 male SLE patients (95%CI: 77 to 539) was found, a dramatic increase over the known prevalence of Klinefelter's syndrome in an unselected population (17 per 10,000 live male births). Asking men with SLE about fertility was highly sensitive (100%) for Klinefelter’s syndrome. All 768 SLE women were heterozygous at X.
Conclusions
47,XXY Klinefelter's syndrome, often subclinical, is increased in men with SLE by ~14-fold, compared to its prevalence in men without SLE. Diagnostic vigilance for 47,XXY males in SLE is warranted. These data are the first to associate Klinefelter's syndrome with an autoimmune disease found predominantly in women. The risk of SLE in Klinefelter's syndrome is predicted to be similar to the risk in normal 46,XX women and ~14-fold higher than in 46,XY men, consistent with SLE susceptibility being partly explained by a X chromosome gene dose effect.
doi:10.1002/art.23701
PMCID: PMC2824898  PMID: 18668569
2.  Genome-wide Linkage Screen for Stature and Body-mass Index in 3.032 Families - Evidence for Sex- and Population-specific Genetic Effects 
Stature (adult body height), and body mass index (BMI) have a strong genetic component explaining observed variation in human populations, however, identifying those genetic components has been extremely challenging. It seems obvious that sample size is a critical determinant for successful identification of quantitative trait loci (QTL) that underlie the genetic architecture of these polygenic traits. The inherent shared environment and known genetic relationships in family studies provide clear advantages for gene mapping over studies utilizing unrelated individuals. To these ends, we combined the genotype and phenotype data from four previously performed family-based genome-wide screens resulting in a sample of 9.371 individuals from 3.032 African-American and European-American families and performed variance-components linkage analyses for stature and BMI. To our knowledge, this study represents the single largest family-based genome-wide linkage scan published for stature and BMI to date. This large study sample allowed us to pursue population-and sex-specific analyses as well. For stature we found evidence for linkage in previously reported loci on 11q23, 12q12, 15q25 and 18q23 as well as 15q26 and 19q13 which have not been linked to stature previously. For BMI we found evidence for two loci: one on 7q35 and another on 11q22 both of which have been previously linked to BMI in multiple populations. Our results show both the benefit of 1) combining data to maximize the sample size and 2) minimizing heterogeneity by analyzing subgroups where within-group variation can be reduced and suggest that the latter may be a more successful approach in genetic mapping.
doi:10.1038/ejhg.2008.152
PMCID: PMC2628452  PMID: 18781184
Body Height; Body Mass Index; Linkage mapping; Quantitative Trait Loci
3.  Genome-wide linkage screen for stature and body mass index in 3.032 families: evidence for sex- and population-specific genetic effects 
Stature (adult body height) and body mass index (BMI) have a strong genetic component explaining observed variation in human populations; however, identifying those genetic components has been extremely challenging. It seems obvious that sample size is a critical determinant for successful identification of quantitative trait loci (QTL) that underlie the genetic architecture of these polygenic traits. The inherent shared environment and known genetic relationships in family studies provide clear advantages for gene mapping over studies utilizing unrelated individuals. To these ends, we combined the genotype and phenotype data from four previously performed family-based genome-wide screens resulting in a sample of 9.371 individuals from 3.032 African-American and European-American families and performed variance-components linkage analyses for stature and BMI. To our knowledge, this study represents the single largest family-based genome-wide linkage scan published for stature and BMI to date. This large study sample allowed us to pursue population- and sex-specific analyses as well. For stature, we found evidence for linkage in previously reported loci on 11q23, 12q12, 15q25 and 18q23, as well as 15q26 and 19q13, which have not been linked to stature previously. For BMI, we found evidence for two loci: one on 7q35 and another on 11q22, both of which have been previously linked to BMI in multiple populations. Our results show both the benefit of (1) combining data to maximize the sample size and (2) minimizing heterogeneity by analyzing subgroups where within-group variation can be reduced and suggest that the latter may be a more successful approach in genetic mapping.
doi:10.1038/ejhg.2008.152
PMCID: PMC2628452  PMID: 18781184
body height; body mass index; linkage mapping; quantitative trait loci

Results 1-3 (3)