Obesity is an increasingly serious health problem in the world. Body mass index (BMI), percentage fat mass, and body fat mass are important indices of obesity. For a sample of pedigrees that contains 110,000 relative pairs (including 1,249 sib pairs) that are useful for linkage analyses, we performed a whole-genome linkage scan, using 380 microsatellite markers to identify genomic regions that may contain quantitative-trait loci (QTLs) for obesity. Each pedigree was ascertained through a proband who has extremely low bone mass, which translates into a low BMI. A major QTL for BMI was identified on 2q14 near the marker D2S347 with a LOD score of 4.04 in twopoint analysis and a maximum LOD score (MLS) of 4.44 in multipoint analysis. The genomic region near 2q14 also achieved an MLS 12.0 for percentage of fat mass and body fat mass. For the putative QTL on 2q14, as much as 28.2% of BMI variation (after adjustment for age and sex) may be attributable to this locus. In addition, several other genomic regions that may contain obesity-related QTLs are suggested. For example, 1p36 near the marker D1S468 may contain a QTL for BMI variation, with a LOD score of 2.75 in two-point analysis and an MLS of 2.09 in multipoint analysis. The genomic regions identified in this and earlier reports are compared for further exploration in extension studies that use larger samples and/or denser markers for confirmation and fine-mapping studies, to eventually identify major functional genes involved in obesity.

Collagen type Ia2 (COL1A2) and parathyroid hormone (PTH)/PTH-related peptide receptor (PTHR1) are two prominent candidate genes for bone mineral density (BMD). To test their importance for BMD variation in Chinese, we recruited 388 nuclear families composed of both parents and at least one healthy daughter with a total of 1,220 individuals, and simultaneously analyzed population stratification, total-family association, and within-family association between BMD at the spine and hip and the (GT)n marker in the intron 1 of the COL1A2 gene and the (AAAG)n marker in the P3 promoter of PTHR1 gene. We also performed these association analyses with haplotypes of the MspI and (GT)n polymorphisms in the COL1A2 gene. Significant within-family association was found between the M(GT)12 haplotype and trochanter BMD (P<0.001). Individuals with this haplotype have, on average, 9.53% lower trochanter BMD than the non-carriers. Suggestive evidence of the within-family association was detected between the (GT)17 allele and BMD at the spine (P=0.012), hip (P=0.011), femoral neck (P=0.032), trochanter (P=0.023), and intertrochanter (P=0.034). The association was confirmed by subsequent permutation tests. For the association, the proportion of phenotypic variance explained by the detected markers ranged from 1.2 to 3.9%, with the highest 3.9% at the trochanter for the M(GT)12 haplotype. This association indicates that there is strong linkage disequilibrium between the polymorphisms (MspI and GT repeat polymorphism) in the COL1A2 gene and a nearby quantitative trait locus (QTL) underlying BMD variation in Chinese, or the markers themselves may have an important effect on the variation of BMD. On the other hand, no significant within-family association, population stratification and total-family association between the PTHR1 polymorphism and BMD were found in our Chinese population.

Bone size is an important determinant of osteoporotic fractures. For a sample of 53 pedigrees that contains more than 10,000 relative pairs informative for linkage analyses, we performed a whole-genome linkage scan using 380 microsatellite markers to identify genomic regions that may contain QTLs of bone size (two-dimensional measurement by dual energy X-ray absorptiometry). We conducted two- and multi-point linkage analyses. Several potentially important genomic regions were identified. For example, the genomic region 17q23 may contain a QTL for wrist (ultra distal) bone size variation; a LOD score of 3.98 is achieved at D17S787 in two-point analyses and a maximum LOD score (MLS) of 3.01 is achieved in multi-point analyses in 17q23. 19p13 may contain a QTL for hip bone size variation; a LOD score of 1.99 is achieved at D19S226 in two-point analyses and a MLS of 2.83 is achieved in 19p13 in multi-point analyses. The genomic region identified on chromosome 17 for wrist bone size seems to be consistent with that identified for femur head width variation in an earlier wholegenome scan study. The genomic regions identified in this study and an earlier investigation on one-dimensional bone size measurement by radiography are compared. The two studies may form a basis for further exploration with larger samples and/or denser markers for confirmation and fine mapping studies to eventually identify major functional genes and the associated causes for osteoporosis.

To efficiently manipulate large amounts of genotype data generated with fluorescently labeled dinucleotide markers, we developed a Microsoft Access database management system, named GenoDB. GenoDB offers several advantages. First, it accommodates the dynamic nature of the accumulations of genotype data during the genotyping process; some data need to be confirmed or replaced by repeat lab procedures. By using GenoDB, the raw genotype data can be imported easily and continuously and incorporated into the database during the genotyping process that may continue over an extended period of time in large projects. Second, almost all of the procedures are automatic, including autocomparison of the raw data read by different technicians from the same gel, autoadjustment among the allele fragment-size data from cross-runs or cross-platforms, autobinning of alleles, and autocompilation of genotype data for suitable programs to perform inheritance checkin pedigrees. Third, GenoDB provides functions to track electrophoresis gel files to locate gel or sample sources for any resultant genotype data, which is extremely helpful for double-checking consistency of raw and final data and for directing repeat experiments. In addition, the user-friendly graphic interface of GenoDB renders processing of large amounts of data much less labor-intensive. Furthermore, GenoDB has built-in mechanisms to detect some genotyping errors and to assess the quality of genotype data that then are summarized in the statistic reports automatically generated by GenoDB. The GenoDB can easily handle>500,000 genotype data entries, a number more than sufficient for typical whole-genome linkage studies. The modules and programs we developed for the GenoDB can be extended to other database platforms, such as Microsoft SQL server, if the capability to handle still greater quantities of genotype data simultaneously is desired.

Transmission disequilibrium test (TDT) is a nuclear family-based analysis that can test linkage in the presence of association. It has gained extensive attention in theoretical investigation and in practical application; in both cases, the accuracy and generality of the power computation of the TDT are crucial. Despite extensive investigations, previous approaches for computing the statistical power of the TDT are neither accurate nor general. In this paper, we develop a general and highly accurate approach to analytically compute the power of the TDT. We compare the results from our approach with those from several other recent papers, all against the results obtained from computer simulations. We show that the results computed from our approach are more accurate than or at least the same as those from other approaches. More importantly, our approach can handle various situations, which include (1) families that consist of one or more children and that have any configuration of affected and nonaffected sibs; (2) families ascertained through the affection status of parent(s); (3) any mixed sample with different types of families in (1) and (2); (4) the marker locus is not a disease susceptibility locus; and (5) existence of allelic heterogeneity. We implement this approach in a user-friendly computer program: TDT Power Calculator. Its applications are demonstrated. The approach and the program developed here should be significant for theoreticians