WO2003008562A2

WO2003008562A2 - Methods for detecting genes associated with bone properties, height, and/or body mass properties

Info

Publication number: WO2003008562A2
Application number: PCT/US2002/023293
Authority: WO
Inventors: Robert R. Recker; Hong-Wen Deng
Original assignee: Creighton University
Priority date: 2001-07-20
Filing date: 2002-07-22
Publication date: 2003-01-30
Also published as: WO2003008562A3; AU2002322584A1

Abstract

Disclosed are methods for detecting the presence in a subject of a polymorphism linked to a gene associated with one or more bone properties, such as spine bone mineral density, hip bone mineral density, wrist bone mineral density, spine bone size, hip bone size, and wrist bone size. The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near various specified regions of the subject's genome and which is linked to the gene associated with the bone property of interest. The presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant bone properties. Also disclosed are methods for detecting the presence in a subject of a polymorphism linked to a gene associates with height or with one or more body mass properties, such as body mass index, percentage fat mass, fat mass, and lean mass. The methods can be used, for example, to screen for a subject's having or being susceptible to conditions such as osteoporosis and obesity.

Description

METHODS FOR DETECTING GENES ASSOCIATED WITH BONE PROPERTIES, HEIGHT, AND/OR BODY MASS PROPERTIES

The present invention claims the benefit of

U.S. Provisional Patent Application Serial No. 60/306,690, filed July 20, 2001, and U.S. Provisional Patent Application Serial No. 60/336,829, filed October 26, 2001, each which provisional patent applications is hereby incorporated by reference.

The present invention was made with the support of the United States Department of Energy, Grant No. DE- FGO3-OOER63OOO/A00, and with the support of the National Institutes of Health, Grant Nos . K01 AR02170-01, R01 AR45349-01, R01 GM60402-01A1 , and P01 DC01813-07. The Federal Government may have certain rights in this invention.

FIELD OF THE INVENTION

The present invention is directed to genetic testing, and more particularly to methods of detecting the presence of genes associated with spine bone mineral density, hip bone mineral density, wrist bone mineral density, spine bone size variation, hip bone size variation, wrist bone size variation, height, body mass index, percentage fat mass, fat mass variation, or lean mass variation. BACKGROUND OF THE INVENTION

Throughout this application various publications are referenced, many in superscripted parenthesis. Full citations for each of these publications are provided in a section entitled "References" following the Examples. The disclosures of each of these publications, in their entireties, are hereby incorporated by reference in this application. The present application refers to a variety of genes using conventional abbreviations (e.g., the IL-6 gene, the TWIST gene, the HOXC6 gene, etc.) . Further details regarding these and other genes referred to herein can be found in various databases and other sources, such as the skeletal gene database set forth in Ho et al . , "A Skeletal Gene Database," J. Bone Miner. Res. , 15:2095-2122 (2000), which is hereby incorporated by reference; the human obesity gene map set forth in Perusse et al . , "Genotype-Environment Interaction in Human Obesity," Nutr. Rev. , 7:S31-S37 (1999), which is hereby incorporated by reference; "Online Mendelian Inheritance in Man", http://www.ncbi.nlm.nih.gov, which is hereby incorporated by reference; and the "NCBI Map Viewer" , http : //www.ncbi .nlm.nih.gov/PMGigs/Genomes/- humansearch.html, which is hereby incorporated by reference.

Bone Properties and Osteoporosis

Low bone mineral density ("BMD") is an important risk factor for osteoporotic fractures, and osteoporosis is mainly characterized by low BMD. For example, in the US alone in 1995, osteoporosis results in more than 1.3 million osteoporotic fractures a year, with an estimated direct cost of about 14 billion dollars. Extensive data have established that BMD variation is under strong genetic control with heritability estimates ranging from 0.5-0.9. However, the pathogenesis of bone fragility is heterogeneous, and low BMD is not the only important risk factor for osteoporotic fractures . Many studies have suggested that bone size per se may also play an important role that is independent of BMD and bone mineral content ("BMC") in determining bone strength. Loss of bone strength is a main determinant of osteoporosis. BMD is defined as the ratio of BMC to bone size (silhouette size) . Hence, bone size is an important component of BMD. Bone size should also be a relatively simpler phenotype than BMD in terms of the complexity of the factors (whether genetic, environmental factors or their interactions) in determining their variation. This is simply because BMD variation is also determined by all those potential factors that may be only important for BMC but not for bone size.

The importance of bone size as a significant risk factor that may be independent of BMD for the parthenogenesis of osteoporotic fractures is suggested by the following lines of evidence. First, patients with spine fractures often have reduced bone size. The deficit in bone size may partly account for both the increased bone fragility and for the deficit in BMC and BMD compared with age-matched controls. Second, spinal BMD in females is comparable with that in males; however, females suffer a larger incidence of spine fractures than males. This is partially attributable to the fact that female's spine bone sizes are 20-25% smaller than male's after adjusting for body size differences. Third, it is known that while a decrease in bone mass may result in a loss of bone strength, the loss may be offset, at least in part, by an increase in bone size, tending to preserve bone strength. Fourth, it has been demonstrated that a genetically homogenous inbred mouse strain has higher bone mass, but smaller bone size and is less sensitive in adapting to mechanical loading to increase bone strength when compared with another inbred mouse strain.

For these and other reasons, a need exists for methods of detecting the presence in a subject of a polymorphism linked to genes associated with BMD, bone size, and/or other bone properties and the present invention, in part, is directed toward meeting this need.

Stature

Human growth is a highly complicated process. From the formation of a viable zygote until the fusion of the epiphyseal cartilage, a host of factors, including genetic factors, maternal and interuterine environment, endocrine status, diseases, socioeconomic condition, and even psychologic well-being, interact to influence and determine the final height that an individual will achieve .

Early studies on height identified a strong familial aggregation of this trait, manifested by a high correlation among relatives, and this has been corroborated by a series of more recent studies. Generally, the heritability of height is well above 50% and is among the highest in all the complex human traits studied.

Association studies have identified an array of growth-related candidate genes, such as VDR (vitamin D receptor) , DRD2, Collagen I Al, ER (estrogen receptor) , LH beta (luteinizing hormone beta) , and the recently isolated SHOX/PHOG gene. Against a polygenic background, the existence of a putative major gene, determining 37-53% variation of height, has been posited by a segregation analysis.

Yet the search for such major genes, with the approach of genomewide linkage analysis, has yielded generally inconsistent results. Genomic regions suggestive of linkage to height, according to the limited few studies, encompassed 6q24-25, 7q31.3-36, 12pll.2-ql4, 13q32-33, 164cM from 7pter, 159cM from the 9pter, and the region bracketing D20S98 and D20S66 on the chromosome 20, with the only agreement achieved on chromosome 7.

Despite the limited success of these studies is identifying genomic regions having linkages to height, identification of such regions is important in that it would enable one to determine the genetic factors which contribute to the final height that an individual will achieve or has achieved. Such a determination can be valuable, for example, in predicting the height of an individual from a sample of the individual's DNA (e.g., in criminal investigations or in the search for missing persons) . For these and other reasons, a need exists for methods of detecting the presence in a subject of a polymorphism linked to a gene associated with height variation, and the present invention, in part, is directed toward meeting this need.

Obesity Obesity is a disease condition with excess body fat that adversely affects health. Obesity is associated with many diseases such as type 2 diabetes mellitus, hypertension, coronary heart disease, and some cancers. Body mass index ("BMI"), which is equal to the ratio of weight/height² (typically expressed in units of kg/m²) , is an important measure for obesity. Typically, a higher BMI is associated with higher mortality. About 250 million adults suffer obesity (7%. of the adult population, defined as having a BMI greater than 30 kg/m²) in the world and 2-3 times as many may be considered overweight (defined as having a BMI of 25-30 kg/m²) . In the United States, 59.4% of men and 50.7% of women are overweight or obese. The direct costs associated with obesity are estimated to be approximately $100 billion per year and represent 5.7% of national health expenditure in the United States in 1995. A more recent analysis shows that the health care cost of obesity in the United States is most likely between 0.89% and 4.32%. Obesity is a complex trait that is determined by multiple genetic and environmental factors (including physiological, behavior, and socio-cultural factors). Numerous studies have been conducted to characterize the heritability of obesity-related phenotypes, most on BMI, a few on fat mass and body percentage fat mass ("PFM") and few on lean mass. The estimates of heritability (h²) of BMI have ranged from 0.05 to 0.90. For fat mass, h² estimates have ranged from 20% to 65%. For PFM, h² estimates have ranged from 62% to 80%. For lean mass, h² estimates have ranged from 0.52 to 0.80. In one of our earlier studies (Deng et al . , "Characterization of Genetic and Life-style Factors for Determining Variation of BMI, Fat Mass, Percentage Fat Mass, and Lean Mass," _ Clinical Densitometrv. 4:353-362 (2001)), after adjusting for age, sex, and life style factors, h² estimates of BMI, fat mass, PFM, and lean mass ranged from 0.52 to 0.57. For these and other reasons, a need exists for methods of detecting the presence in a subject of a polymorphism linked to a gene associated with obesity- related phenotypes, and the present invention, in part, is directed toward meeting this need.

SUMMARY OF THE INVENTION

The present invention relates to a method for detecting the presence in a subject of a polymorphism linked to a gene associated with one or more bone properties. The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with one or more bone properties. The presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant bone properties, and the particular region is selected from the group consisting of: a VDR gene of the subject's genome; a BGP gene of the subject's genome; an IL-6 gene of the subject's genome; between about 120 cM and about 180 cM from pter on chromosome 4 of the subject's genome; between about 0 cM and about 20 cM from pter on chromosome 7 of the subject's genome; between about 120 cM and about 175 cM from pter on chromosome 12 of the subject's genome; between about 80 cM and about 115 cM from pter on chromosome 13 of the subject's genome; between about 140 cM and about 172 cM from pter on chromosome 10 of the subject's genome; between about 60 cM and about 90 cM from pter on chromosome 12 of the subject's genome; between about 30 cM and about 80 cM from pter on chromosome 17 of the subject's genome; between about 0 cM and about 20 cM from pter on chromosome 3 of the subject's genome; between about 0 cM and about 60 cM from pter on chromosome 9 of the subject's genome; between about 0 cM and about 52 cM from pter on chromosome 17 of the subject's genome; between about 5 cM and about 55 cM from pter on chromosome 2 of the subject's genome; between about 10 cM and about 55 cM from pter on chromosome 19 of the subject's genome; between about 0 cM and about 40 cM from pter on chromosome 14 of the subject's genome; between about 30 cM and about 100 cM from pter on chromosome 17 of the subject's genome; between about 0 cM and about 40 cM from pter on chromosome 4 of the subject's genome; between about 240 cM and about 265 cM from pter on chromosome 2 of the subject's genome; and between about 40 cM and about 85 cM from pter on chromosome 9 of the subject's genome.

The present invention also relates to a method for detecting the presence in a subject of a polymorphism linked to a gene associated with one or more body mass properties . The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with one or more body mass properties. The presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant body mass properties, and the particular region is selected from the group consisting of: an IL-6 gene of the subject's genome; between about 0 cM and about 25 cM from pter on chromosome 1 of the subject's genome; between about 80 cM and about 170 cM from pter on chromosome 2 of the subject's genome; between about 40 cM and about 100 cM from pter on chromosome 4 of the subject's genome; between about 150 cM and about 192 cM from pter on chromosome 6 of the subject's genome; between about 230 cM and about 250 cM from pter on chromosome 2 of the subject's genome; between about 140 cM and about 150 cM from pter on chromosome 8 of the subject's genome; between about 160 cM and about 192 cM from pter on chromosome 6 of the subject's genome; between about 0 cM and about 60 cM from pter on chromosome 8 of the subject's genome; between about 50 cM and about 100 cM from pter on chromosome 20 of the subject's genome; between about 55 cM and about 100 cM from pter on chromosome 12 of the subject's genome; between about 30 cM and about 100 cM from pter on chromosome 5 of the subject's genome; between about 10 cM and about 60 cM from pter on chromosome 17 of the subject's genome; and between about 0 cM and about 20 cM from pter on chromosome 7 of the subj ect ' s genome .

The present invention also relates to a method for detecting the presence in a subject of a polymorphism linked to a gene associated with height. The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with height. The presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant height, and the particular region is selected from the group consisting of: between about 10 cM and about 70 cM from pter on chromosome 4 of the subject's genome; between about 70 cM and about 200 cM from pter on chromosome 5 of the subject's genome; between about 0 cM and about 45 cM from pter on chromosome 8 of the subject's genome; between about 60 cM and about 135 cM from pter on chromosome 17 of the subject's genome; between about 100 cM and about 150 cM from pter on chromosome X of the subject's genome; and between about 0 cM and about 35 cM from pter on chromosome X of the subject's genome.

BRIEF DESCRIPTION OF THE DRAWINGS

Figures 1A, IB, 1C, ID, and IE are graphs showing LOD scores for bone mineral density at three skeletal sites (spine, hip, and wrist) as a function of chromosome position for chromosomes 4, 7, 10, 12, and 13, respectively. Figures 2A, 2B, 2C, 2D, 2E, 2F, 2G, 2H, 21, 2J,

2K, 2L, 2M, 2N, 20, 2P, 2Q, and 2R are graphs showing LOD scores for bone mineral density at three skeletal sites (spine, hip, and wrist) as a function of chromosome position for chromosomes 1, 2, 3, 5, 6, 8, 9, 11, 14, 15, 16, 17, 18, 19, 20, 21, 22, and X, respectively.

Figures 3A, 3B, 3C, and 3D are graphs showing LOD scores for bone size at three skeletal sites (spine, hip, and wrist) as a function of chromosome position for chromosomes 2, 9, 17, and 19, respectively. Figures 4A, 4B, 4C, 4D, 4E, 4F, 4G, 4H, 41, 4J,

4K, 4L, 4M, 4N, 40, 4P, 4Q, 4R, and 4S are graphs showing LOD scores for bone mineral density at three skeletal sites (spine, hip, and wrist) as a function of chromosome position for chromosomes 1, 3, 4, 5, 6, 7, 8, 10, 11, 12, 13, 14, 15, 16, 18, 20, 21, 22, and X, respectively.

Figures 5A, 5B, and 5C are graphs showing LOD scores for body mass index, percentage fat mass, fat mass, and lean mass as a function of chromosome position for chromosomes 1, 2, and 4, respectively.

Figures 6A, 6B, 6C, 6D, 6E, 6F, 6G, 6H, 61, 6J, 6K, 6L, 6M, 6N, 60, 6P, 6Q, 6R, 6S, and 6T are graphs showing LOD scores for body mass .index, percentage fat mass, fat mass, and lean mass as a function of chromosome position for chromosomes 3, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, and X, respectively. Figures 7A, 7B, 7C, and 7D are graphs showing

LOD scores for height as a function of chromosome position for chromosomes 5, 8, 17, and X, respectively.

Figures 8A, 8B, 8C, 8D, 8E, 8F, 8G, 8H, 81, 8J, 8K, 8L, 8M, 8N, 80, 8P, 8Q, 8R, and 8S are graphs showing LOD scores for height as a function of chromosome position for chromosomes 1, 2, 3, 4, 6, 7, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20, 21, and 22, respectively. .

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to a methods for detecting the presence in a subject (e.g., a human subject, male or female, born or unborn, etc.) of a polymorphism linked to a gene associated with one or more bone properties, such properties including, for example, spine bone mineral density, hip bone mineral density, wrist bone mineral density, spine bone size, hip bone size, and wrist bone size. The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with the bone property of interest . For example, in the case where the bone property of interest is spine bone mineral density, the method of the present invention can be carried out by analyzing the subject's chromosome 12 and detecting the presence of a polymorphism located in or near the VDR gene linked to the gene associated with spine bone mineral density.

Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with spine bone mineral density.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 4 and detecting the presence of a polymorphism located between about 120 cM and about 180 cM from pter and linked to the gene associated with spine bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between about 130 cM and about 180 cM from pter, between about 140 cM and about 180 cM from pter, between about 150 cM and about 175 cM from pter, between about 155 cM and about 170 cM from pter, and/or between 157 cM and 159 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between D4S406 and D4S415, inclusive; between D4S402 and D4S1539, inclusive; between D4S1575 and D4S1539, inclusive; between D4S424 and D4S1539, inclusive; between D4S424 and

D4S413, inclusive; near D4S413; and/or in or near 4q32.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 12 and detecting the presence of a polymorphism located 120 cM and about 175 cM from pter and linked to the gene associated with spine bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 12 and detecting the presence of such a polymorphism located between about 140 cM and about 175 cM from pter, between about 150 cM and about 175 cM from pter, and/or between 167 cM and 170 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 12 and detecting the presence of such a polymorphism located between D12S79 and D12S1723, inclusive; between D12S86 and D12S1723, inclusive; between D12S324 and D12S1723, inclusive; between D12S1659 and D12S1723, inclusive; near D12S1723; and/or in or near 12q24. The polymorphism can be one which is located in or near the IGF1 gene, the TBX3 gene, or the TBX5 gene; or the polymorphism can be one which is not located in or near the IGF1 gene, the TBX3 gene, or the TBX5 gene. Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 13 and detecting the presence of a polymorphism located 80 cM and about 115 cM from pter . and linked to the gene associated with spine bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 13 and detecting the presence of such a polymorphism located between about 85 cM and about 113 cM from pter, between about 90 cM and about 105 cM from pter, between 112 cM and 113 cM from pter, and/or between 102 cM and 104 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 13 and detecting the presence of such a polymorphism located between D13S158 and D13S285, inclusive; between D13S173 and D13S285, inclusive; between D13S1265 and D13S285, inclusive; near D13S285; and/or in or near 13q33 and/or 13q34. The polymorphism can be one which is located in or near the COLA1 gene or the C0LA2 gene; or the polymorphism can be one which is not located in or near the COLA1 gene or the COLA2 gene .

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located 0 cM and about 20 cM from pter and linked to the gene associated with spine bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 7 and detecting the presence of such a polymorphism located between about 0 cM and about 10 cM from pter and/or between 7 cM and 8 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 7 and detecting the presence of such a polymorphism located between D7S531 and D7S513 inclusive; between D7S531 and D7S517, inclusive; near D7S531;^' and/or in or near 7p22. The polymorphism can be one which is located in or near the TWIST gene; or the polymorphism can be one which is not located in or near the TWIST gene.

In the case where the bone property of interest is hip bone mineral density, the method of the present invention can be carried out by analyzing the subject's chromosome 1 and detecting the presence of a polymorphism located in or near the BGP gene linked to the gene associated with hip bone mineral density. Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with hip bone mineral density.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 10 and detecting the presence of a polymorphism located between about 140 cM and about 172 cM from pter and linked to the gene associated with hip bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 10 and detecting the presence of such a polymorphism located between about 150 cM and about 172 cM from pter, between about 155 cM and about 172 cM from pter, between about 160 cM and about 172 cM from pter, and/or between 178 cM and 179 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 10 and detecting the presence of such a polymorphism located between D10S587 and D10S212, inclusive; located between D10S217 and D10S212, inclusive; between D10S1651 and D10S212, inclusive; near D10S1651; and/or in or near 10q26. The polymorphism can be one which is located in or near the FGFR2 gene; or the polymorphism can be one which is not located in or near the FGFR2 gene.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 12 and detecting the presence of a polymorphism located between about 60 cM and about 90 cM from pter and linked to the gene associated with hip bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 12 and detecting the presence of such a polymorphism located between about 65 cM and about 80 cM from pter, between about 65 cM and about 75 cM from pter, and/or between 69 cM and 70 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 12 and detecting the presence of such a polymorphism located between D12S345 and D12S326, inclusive; located between D12S85 and D12S368, inclusive; near D12S368; and/or in or near 12ql3. The polymorphism can be one which is located in or near the COL2A1 gene, the ITGA7 gene, the HOXC4 gene, the HOXC5 gene, the H0XC6 gene, the HOXC8 gene, the HOXC9 gene, the HOXC10 gene, the HOXC11 gene, the HOXC12 gene, or the HOXC13 gene; or the polymorphism can be one which is not located in or near the COL2A1 gene, the ITGA7 gene, the HOXC4 gene, the HOXC5 gene, the H0XC6 gene, the HOXC8 gene, the HOXC9 gene, the HOXC10 gene, the HOXC11 gene, the HOXC12 gene, or the HOXC13 gene.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 17 and detecting the presence of a polymorphism located between about 30 cM and about 80 cM from pter and linked to the gene associated with hip bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between about 35 cM and about 70 cM from pter, between about 40 cM and about 65 cM from pter, between about 45 cM and about 60 cM from pter, and/or between 43 cM and 45 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between D17S799 and D17S787, inclusive; located between D17S921 and D17S1868, inclusive; located between D17S1857 and D17S798, inclusive; near D17S1857; and/or in or near

17pll.

In the case where the bone property of interest is wrist bone mineral density, the method of the present invention can be carried out by analyzing the subject's chromosome 4 and detecting the presence of a polymorphism located between about 120 cM and about 180 cM from pter and linked to the gene associated with wrist bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between about 130 cM and about 180 cM from pter, between about 140 cM and about 180 cM from pter, between about 150 cM and about 175 cM from pter, between about 155 cM and about 170 cM from pter, and/or between 157 cM and 159 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between D4S406 and D4S415, inclusive; located between D4S402 and D4S1539, inclusive; between D4S1575 and D4S1539, inclusive; between D4S424 and D4S1539, inclusive; between D4S424 and D4S413, inclusive; near D4S413; and/or in or near 4q32.

Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 3 and detecting the presence of a polymorphism located between about 0 cM and about 20 cM from pter and linked to the gene associated with wrist bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 3 and detecting the presence of such a polymorphism located between about 0 cM and about 15 cM from pter, between about 0 cM and about 10 cM from pter, between about 0 cM and about 5 cM from pter, and/or between 2 cM and 3 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 3 and detecting the presence of such a polymorphism located between D3S1297 and D3S1304, inclusive; near D3S1297; and/or in or near 3p26.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 9 and detecting the presence of a polymorphism located between about 0 cM and about 60 cM from pter and linked to the gene associated with wrist bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 9 and detecting the presence of such a polymorphism located between about 0 cM and about 35 cM from pter, between about 0 cM and about 10 cM from pter, between about 5 cM and about 30 cM from pter, between about 10 cM and about 25 cM from pter, between 27 cM and 28 cM from pter, and/or between 15 cM and 17 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 9 and detecting the presence of such a polymorphism located between D9S288 and D9S175, inclusive; between D9S288 and D9S273, inclusive; between D9S288 and D9S1817, inclusive; between D9S288 and D9S161, inclusive; between D9S288 and D9S171, inclusive; between D9S288 and D9S157, inclusive; between D9S286 and D9S285, inclusive; near D9S285; and/or in or near 9p22, 9p24, or both. Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 17 and detecting the presence of a polymorphism located between about 0 cM and about 52 cM from pter and linked to the gene associated with wrist bone mineral density. Illustratively, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between about 15 cM and about 45 cM from pter, between about 15 cM and about 25 cM from pter, and/or between 23 cM and 24 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between D17S849 and D17S798, inclusive; between D17S831 and D17S1957, inclusive; between D17S938 and D17S921, inclusive; between D17S938 and D17S799, inclusive; between D17S938 and D17S1852, inclusive; between D17S1852 and D17S799, inclusive; near D17S1852; and/or in or near 17pl3.

In the case where the bone property of interest is spine bone size, the method of the present invention can be carried out by analyzing the subject's chromosome 2 and detecting the presence of a polymorphism located between about 5 cM and about 55 cM from pter and linked to the gene associated with spine bone size. Illustratively, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between about 20 cM and about 40 cM from pter, between about 30 cM and about 40 cM from pter, between 30 cM and 32 cM from pter, and/or between 38 cM and 40 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between D2S2211 and D2S367, inclusive; between D2S2211 and D2S165, inclusive; between D2S162 and D2S165, inclusive; between D2S168 and D2S165, inclusive; between D2S168 and D2S305, inclusive; between D2S305 and D2S165, inclusive; near D2S305; and/or in or near 2p21, 2p25, or both.

In the case where the bone property of interest is hip bone size, the method of the present invention can be carried out by analyzing the subject's chromosome 19 and detecting the presence of a polymorphism located between about 10 cM and about 55 cM from pter and linked to the gene associated with hip bone size. Illustratively, the method can be carried out by analyzing the subject's chromosome 19 and detecting the presence of such a polymorphism located between about 20 cM and about 55 cM from pter, between about 25 cM and about 50 cM from pter, between about 35 cM and about 45 cM from pter, between 37 cM and 39 cM from pter, and/or between 41 cM and 43 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 19 and detecting the presence of such a polymorphism located between D19S884 and D19S420, inclusive; between D19S221 and D19S220, inclusive; between D19S226 and D19S220, inclusive; between D19S226 and D19S414, inclusive; near D19S226; and/or in or near 9pl3. The polymorphism can be one which is located in or near the PRTN3 gene; or the polymorphism can be one which is not located in or near the PRTN3 gene. Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 14 and detecting the presence of a polymorphism located between about 0 cM and about 40 cM from pter and linked to the gene associated with hip bone size. Illustratively, the method can be carried out by analyzing the subject's chromosome 14 and detecting the presence of such a polymorphism located between about 0 cM and about 30 cM from pter, between about 0 cM and about 25 cM from pter, between about 5 cM and about 20 cM from pter, between about 10 cM and about 20 cM from pter, and/or between 15 cM and 17 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 14 and detecting the presence of such a polymorphism located between D14S261 and D14S70, inclusive; between D14S261 and D14S275, inclusive; between D14S283 and D14S275, inclusive; between D19S226 and D19S414, inclusive; and/or in or near 14qll. In the case where the bone property of interest is wrist bone size, the method of the present invention can be carried out by analyzing the subject's chromosome 17 and detecting the presence of a polymorphism located between about 30 cM and about 100 cM from pter and linked to the gene associated with wrist bone size.

Illustratively, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between about 40 cM and about 90 cM from pter, between about 50 cM and about 90 cM from pter, between about 60 cM and about 90 cM from pter, between about 65 cM and about 85 cM from pter, between about 70 cM and about 85 cM from pter, between about 70 cM and about 80 cM from pter, between 74 cM and 76 cM from pter and/or between 76 cM and 78 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between D17S799 and D17S944, inclusive; between D17S921 and D17S944, inclusive; between D17S1857 and D17S944, inclusive; between D17S798 and D17S944, inclusive; between D17S1868 and D17S787, inclusive; near D17S787; and/or in or near 17q23. The polymorphism can be one which is located in or near the TBX2 gene; or the polymorphism can be one which is not located in or near the TBX2 gene. Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 4 and detecting the presence of a polymorphism located between about 0 cM and about 40 cM from pter and linked to the gene associated with wrist bone size. Illustratively, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between about 0 cM and about 30 cM from pter, between about 0 cM and about 20 cM from pter, between about 0 cM and about 10 cM from pter, between about 3 cM and about 7 cM from pter, and/or between 4 cM and 5 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between D4S412 and D4S419, inclusive; between D4S412 and D4S403, inclusive; between D4S412 and D4S2935, inclusive; near D4S412; and/or in or near 4pl6. The polymorphism can be one which is located in or near the FGFR3 gene, the IDA gene, the IDUA gene, the MSV1 gene, or the HOX7 gene; or the polymorphism can be one which is not located in or near the FGFR3 gene, the IDA gene, the IDUA gene, the MSV1 gene, or the H0X7 gene . Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 2 and detecting the presence of a polymorphism located between about 240 cM and about 265 cM from pter and linked to the gene associated with wrist bone size. Illustratively, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between about 240 cM and about 263 cM from pter, between about 250 cM and about 263 cM from pter, between about 255 cM and about 263 cM from pter, between about 260 cM and about 263 cM from pter, between 262 cM and 264 cM from pter, and/or between 259 cM and 261 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between D2S396 and D2S125, inclusive; between D2S206 and D2S125, inclusive; between D2S338 and D2S125, inclusive; near D2S125; and/or in or near 2q37. The polymorphism can be one which is located in or near the C0L6A3 gene; or the polymorphism can be one which is not located in or near the C0L6A3 gene.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 9 and detecting the presence of a polymorphism located between about 40 cM and about 85 cM from pter and linked to the gene associated with wrist bone size. Illustratively, the method can be carried out by analyzing the subject's chromosome 9 and detecting the presence of such a polymorphism located between about 50 cM and about 75 cM from pter, between about 55 cM and about 70 cM from pter, between about 60 cM and about 70 cM from pter, between 62 cM and 64 cM from pter, and/or between 69 cM and 71 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 9 and detecting the presence of such a polymorphism located between D9S161 and D9S167, inclusive; between D9S1817 and D9S167, inclusive; between D9S273 and D9S167, inclusive; between D9S273 and D9S175, inclusive; between D9S175 and D9S167, inclusive; near D9S175; and/or in or near 9qll, 9ql2 , and/or 9q21. The polymorphism can be one which is located in or near the C0L15A1 gene; or the polymorphism can be one which is not located in or near the C0L15A1 gene. The present invention, in another aspect thereof, relates to a methods for detecting the presence in a subject of a polymorphism linked to a gene associated with one or more body mass properties, such properties including, for example, body mass index, percentage fat mass, fat mass, and lean mass. The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with the body mass property of interest .

For example, in the case where the body mass property of interest is body mass index, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with aberrant body mass index.

Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 1 and detecting the presence of a polymorphism located between about 0 cM and about 25 cM from pter and linked to the gene associated with body mass index. Illustratively, the method can be carried out by analyzing the subject's chromosome 1 and detecting the presence of such a polymorphism located between about 0 cM and about 20 cM from pter, between about 0 cM and about 15 cM from pter, between about 0 cM and about 10 cM from pter, between about 0 cM and about 5 cM from pter, and/or between 4 cM and 5 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 1 and detecting the presence of such a polymorphism located between D1S468 and D1S2667, inclusive; between D1S468 and D1S450, inclusive; between D1S468 and D1S214, inclusive; near D1S468; and/or in or near lp36. The polymorphism can be one which is located in or near the PGD gene, the TNFR2 gene, or the NR0B2 gene; or the polymorphism can be one which is not located in or near the PGD gene, the TNFR2 gene, or the NR0B2 gene .

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 2 and detecting the presence of a polymorphism located between about 90 cM and about 170 cM from pter and linked to the gene associated with body mass index. Illustratively, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between about 100 cM and about 160 cM from pter, between about 105 cM and about 155 cM from pter, between about 110 cM and about 150 cM from pter, between about 115 cM and about 150 cM from pter, between about 120 cM and about 145 cM from pter, between about 125 cM and about 140 cM from pter, between about 130 cM and about 140 cM from pter, between about 120 cM and about 130 cM from pter, between about 125 cM and about 130 cM from pter, between 122 cM and 124 cM from pter, between 127 cM and 129 cM from pter, and/or between 131 cM and 132 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between D2S286 and D2S2330, inclusive; between D2S2333 and D2S142, inclusive; between D2S160 and D2S112,. inclusive; between D2S160 and D2S347, inclusive; near D2S347; and/or in or near 2ql2 , 2ql4, or both.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 4 and detecting the presence of a polymorphism located between about 40 cM and about 100 cM from pter and linked to the gene associated with body mass index. Illustratively, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between about 45 cM and about 95 cM from pter, between about 55 cM and about 90 cM from pter, between about 60 cM and about 80 cM from pter, between about 65 cM and about 75 cM from pter, between 67 cM and 69 cM from pter, and/or between 69 cM and 70 cM from pter. For example, the method can be carried out by analyzing the subj ect ' s chromosome 4 and detecting the presence of such a polymorphism located between D4S391 and D4S1534, inclusive; between D4S405 and D4S964, inclusive; between D4S405 and D4S392, inclusive; between D4S405 and D4S1592, inclusive; between D4S1592 and D4S392, inclusive; near D4S1592; and/or in or near 4ql2. Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 6 and detecting the presence of a polymorphism located between about 150 cM and about 192 cM from pter and linked to the gene associated with body mass index. Illustratively, the method can be carried out by analyzing the subject's chromosome 6 and detecting the presence of such a polymorphism located between about 160 cM and about 191 cM from pter, between about 170 cM and about 191 cM from pter, between about 180 cM and about 191 cM from pter, between 187 cM and 189 cM from pter, and/or between 190 cM and 191 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 6 and detecting the presence of such a polymorphism located between D6S1581 and D6S281, inclusive; between D6S264 and D6S281, inclusive; between D6S446 and D6S281, inclusive; near D6S281; and/or in or near 6q27. In the case where the body mass property of interest is percentage fat mass, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with aberrant percentage fat mass. Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 2 and detecting the presence of a polymorphism located between about 230 cM and about 250 cM from pter and linked to the gene associated with percentage fat mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between about 235 cM and about 245 cM from pter and/or between 240 cM and 241 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between D2S396 and D2S338, inclusive; between D2S396 and D2S206, inclusive; between

D2S206 and D2S338, inclusive; near D2S206; and/or in or near 2q36.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 2 and detecting the presence of a polymorphism located .between about 80 cM and about 150 cM from pter and linked to the gene associated with percentage fat mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between about 85 cM and about 140 cM from pter, between about 100 cM and about 140 cM from pter, between about 120 cM and about 140 cM from pter, between about 125 cM and about 135 cM from pter, between 127 cM and 129 cM from pter, and/or between 131 cM and 132 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between D2S337 and D2S142, inclusive; between D2S368 and D2S142, inclusive; between D2S286 and D2S142, inclusive; between D2S2333 and D2S142, inclusive; between D2S2216 and D2S142, inclusive; between D2S160 and D2S112, inclusive; between D2S160 and D2S347, inclusive; between D2S347 and D2S112, inclusive; near D2S347; and/or in or near 2ql4.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 8 and detecting the presence of a polymorphism located between about 140 cM and about 150 cM from pter and linked to the gene associated with percentage fat mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 8 and detecting the presence of such a polymorphism located between about 145 cM and about 150 cM from pter and/or between 148 cM and 150 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 8 and detecting the presence of such a polymorphism located between D8S284 and D8S272, inclusive and/or in or near 8q24.

In the case where the body mass property of interest is fat mass, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with aberrant fat mass .

Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 2 and detecting the presence of a polymorphism located between about 80 cM and about 150 cM from pter and linked to the gene associated with fat mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between about 85 cM and about 140 cM from pter, between about 100 cM and about 140 cM from pter, between about 120 cM and about 140 cM from pter, between about 125 cM and about 135 cM from pter, between 127 cM and 129 cM from pter, and/or between 131 cM and 132 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 2 and detecting the presence of such a polymorphism located between D2S337 and D2S142, inclusive; between D2S368 and D2S142, inclusive; between D2S286 and D2S142, inclusive; between D2S2333 and D2S142, inclusive; between D2S2216 and D2S142, inclusive; between D2S160 and D2S112, inclusive; between D2S160 and D2S347, inclusive; between D2S347 and D2S112, inclusive; near D2S347; and/or in or near 2ql4.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 6 and detecting the presence of a polymorphism located between about 160 cM and about 192 cM from pter and linked to the gene associated with fat mass^'. Illustratively, the method can be carried out by analyzing the subject's chromosome 6 and detecting the presence of such a polymorphism located between about 170 cM and about 191 cM from pter, between about 180 cM and about 191 cM from pter, between 187 cM and 189 cM from pter, and/or between 190 cM and 191 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 6 and detecting the presence of such a polymorphism located between D6S264 and D6S281, inclusive; between D6S446 and D6S281, inclusive; near D6S281; and/or in or near 6q27.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 8 and detecting the presence of a polymorphism located between about 0 cM and about 60 cM from pter and linked to the gene associated with fat mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 8 and detecting the presence of such a polymorphism located between about 10 cM and about 50 cM from pter, between about 20 cM and about 40 cM from pter, between about 25 cM and about 35 cM from pter, and/or between 31 cM and 32 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 8 and detecting the presence of such a polymorphism located between D8S264 and D8S258, inclusive; between D8S277 and D8S258, inclusive; between D8S550 and D8S258, inclusive; between D8S550 and D8S549, inclusive; between D8S549 and D8S258, inclusive; near D8S549; and/or in or near 8p22.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 20 and detecting the presence of a polymorphism located between about 50 cM and about 100 cM from pter and linked to the gene associated with fat mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 20 and detecting the presence of such a polymorphism located between about 60 cM and about 90 cM from pter, between^' about 60 cM and about 80 cM from pter, between about 65 cM and about 75 cM from pter_> and/or between 68 cM and 70 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 20 and detecting the presence of such a polymorphism located between D20S195 and D20S171, inclusive; between D20S119 and D20S173, inclusive; between D20S119 and D20S100, inclusive; between D20S119 and D20S196, inclusive; between D20S119 and D20S178, inclusive; between D20S178 and D20S196, inclusive; and/or in or near 20ql3. The polymorphism can be one which is located in or near the ASIP gene, the MC3R gene, the MC4R gene, the CEBPB gene, or the GNAS1 gene; or the polymorphism can be one which is not located in or near the ASIP gene, the MC3R gene, the MC4R gene, the CEBPB gene, or the GNAS1 gene.

In the case where the body mass property of interest is lean mass, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with aberrant lean mass.

Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 12 and detecting the presence of a polymorphism located between about 55 cM and about 100 cM from pter and linked to the gene associated with lean mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 12 and detecting the presence of such a polymorphism located between about 65 cM and about 90 cM from pter, between about 70 cM and about 85 cM from pter, between 75 cM and 76 cM from pter, and/or between 81 cM and 83 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 12 and detecting the presence of such a polymorphism located between D12S345 and D12S326, inclusive; between D12S85 and D12S326, inclusive; between D12S368 and D12S326, inclusive; between D12S83 and D12S326, inclusive; near D12S83; and/or in or near 12ql4. Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 5 and detecting the presence of a polymorphism located between about 30 cM and about 100 cM from pter and linked to the gene associated with lean mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 5 and detecting the presence of such a polymorphism located between about 50 cM and about 90 cM from pter, between about 60 cM and about 80 cM from pter, between about 60 cM and about 70 cM from pter, and/or between 64 cM and 65 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 5 and detecting the presence of such a polymorphism located between D5S419 and D5S428, inclusive; between D5S419 and D5S641, inclusive; between D5S426 and D5S424, inclusive; between D5S418 and D5S647, inclusive; between D5S407 and D5S647, inclusive; near D5S407; and/or in or near 5qll.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 17 and detecting the presence of a polymorphism located between about 10 cM and about 60 cM from pter and linked to the gene associated with lean mass^'. Illustratively, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between about 20 cM and about 50 cM from pter, between about 25 cM and about 40 cM from pter, between about 30 cM and about 35 cM from pter, and/or between 32 cM and 34 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between D17S938 and D17S798, inclusive; between D17S1852 and D17S1857, inclusive; between D17S799 and D17S921, inclusive; near D17S799; and/or in or near 17pl2. Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 7 and detecting the presence of a polymorphism located between about 0 cM and about 20 cM from pter and linked to the gene associated with lean mass. Illustratively, the method can be carried out by analyzing the subject's chromosome 7 and detecting the presence of such a polymorphism located between about 0 cM and about 10 cM from pter, between about 3 cM and about 7 cM from pter, and/or between 4 cM and 6 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 7 and detecting the presence of such a polymorphism located between D7S531 and D7S507, inclusive; between D7S531 and D7S513, inclusive; between D7S531 and D7S517, inclusive; between D7S517 and D7S513, inclusive; and/or in or near 7p22. The present invention, in another aspect thereof, relates to a methods for detecting the presence in a subject of a polymorphism linked to a gene associated with height . The method includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with height.

For example, the method of the present invention can be carried out by analyzing the subject's chromosome 4 and detecting the presence of a polymorphism located between about 10 cM and about 70 cM from pter and linked to the gene associated with height. Illustratively, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between about 20 cM and about 60 cM from pter, between about 20 cM and about 50 cM from pter, between about 30 cM and about 50 cM from pter, between about 35 cM and about 50 cM from pter, between about 35 cM and about 45 cM from pter, and/or between 43 cM and 44 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 4 and detecting the presence of such a polymorphism located between D4S2935 and D4S405, inclusive; between D4S403 and D4S391, inclusive; between D4S419 and D4S391, inclusive; near D4S391; and/or in or near 4pl5. Additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 5 and detecting the presence of a polymorphism located between about 70 cM and about 200 cM from pter and linked to the gene associated with height. Illustratively, the method can be carried out by analyzing the subject's chromosome 5 and detecting the presence of such a polymorphism located between about 115 cM and about 160 cM from pter, between about 130 cM and about 155 cM from pter, between about 135 cM and about 150 cM from pter, between about 135 cM and about 140 cM from pter, and/or between 138 cM and 139 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 5 and detecting the presence of such a polymorphism located between D5S647 and D5S408, inclusive; between D5S644 and D5S436, inclusive; between

D5S2027 and D5S436, inclusive; between D5S471 and D5S2115, inclusive; near D5S2115; and/or in or near 5q31. The polymorphism can be one which is located in or near the SMAP gene; or the polymorphism can be one which is not located in or near the SMAP gene .

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 8 and detecting the presence of a polymorphism located between about 0 cM and about 45 cM from pter and linked to the gene associated with height. Illustratively, the method can be carried out by analyzing the subject's chromosome 8 and detecting the presence of such a polymorphism located between about 0 cM and about 30 cM from pter, between about 10 cM and about 25 cM from pter, between about 15 cM and about 25 cM from pter, between about 18 cM and about 22 cM from pter, and/or between 20 cM and 21 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 8 and detecting the presence of such a polymorphism located between D8S264 and D8S1771, inclusive; between D8S264 and D8S549, inclusive; between D8S277 and D8S549, inclusive; between D8S277 and D8S550, inclusive; between D8S550 and D8S549, inclusive; near D8S550; and/or in or near 8p22, 8p23, or both. The polymorphism can be one which is located in or near the EGR3 gene; or the polymorphism can be one which is not located in or near the EGR3 gene. Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome 17 and detecting the presence of a polymorphism located between about 60 cM and about 135 cM from pter and linked to the gene associated with height. Illustratively, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between about 75 cM and about 135 cM from pter, between about 80 cM and about 135 cM from pter, between about 100 cM and about 135 cM from pter, between about 100 cM and about 130 cM from pter, between about 105 cM and about 125 cM from pter, between about 105 cM and about 120 cM from pter, between about 105 cM and about 115 cM from pter, and/or between 106 cM and 107 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome 17 and detecting the presence of such a polymorphism located between D17S1868 and D17S928, inclusive; between D17S944 and D17S928, inclusive; between D17S949 and D17S784, inclusive; between D17S785 and D17S784, inclusive; near D17S785; and/or in or near 17q25. The polymorphism can be one which is located in or near the GRB2 gene or the ZNF179 gene; or the polymorphism can be one which is not located in or near the GRB2 gene or the ZNF179 gene.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome X and detecting the presence of a polymorphism located between about 100 cM and about 150 cM from pter and linked to the gene associated with height. Illustratively, the method can be carried out by analyzing the subject's chromosome X and detecting the presence of such a polymorphism located between about 110 cM and about 145 cM from pter, between about 120 cM and about 145 cM from pter, between about 120 cM and about 140 cM from pter, and/or between 139 cM and 140 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome X and detecting the presence of such a polymorphism located between DXS1106 and DXS1227, inclusive; between DXS8055 and DXS1047, inclusive; between DXS8055 and DXS1001, inclusive; between DXS1001 and DXS1047, inclusive; near DXS1001; and/or in or near Xq25.

Still additionally or alternatively, the method of the present invention can be carried out by analyzing the subject's chromosome X and detecting the presence of a polymorphism located between about 0 cM and about 35 cM from pter and linked to the gene associated with height. Illustratively, the method can be carried out by analyzing the subject's chromosome X and detecting the presence of such a polymorphism located between about 0 cM and about 25 cM from pter, between about 0 cM and about 20 cM from pter, and/or between 10 cM and 11 cM from pter. For example, the method can be carried out by analyzing the subject's chromosome X and detecting the presence of such a polymorphism located between DXS1060 and DXS1226, inclusive; between DXS1060 and DXS987, inclusive; between DXS1060 and DXS8051, inclusive; near DXS1060; and/or in or near Xp22.The polymorphism can be one which is located in or near the SEDL gene or the SHOX gene; or the polymorphism can be one which is not located in or near the SEDL gene or the SHOX gene .

The methods of the present invention can be used to screen individuals or to otherwise identify an individual having the gene associated with the phenotype of interest (e.g., with aberrant spine bone mineral density, with aberrant hip bone mineral density, with aberrant wrist bone mineral density, with aberrant spine bone size, with aberrant hip bone size, wrist bone size, with aberrant body mass index, with aberrant percentage fat mass, with aberrant fat mass, with aberrant lean mass, and/or with aberrant height) . The methods of the present invention can also be used to determine whether a nucleic acid sample (e.g., blood from an unknown source) is derived from an individual having a having the gene associated with a particular phenotype. Furthermore, the methods of the present invention can be used

Moreover, applicants discovery of the markers linked to the gene for the various phenotypes discussed in the present application (such as those identified above and with reference to the data supplied in the Examples which follow) will enable researchers to focus future analysis on small chromosome regions and will accelerate the sequencing of the gene. Illustratively, linkage analysis (such as the linkage analysis techniques described in the Examples which follow) can be used to find the location of a gene causing a hereditary "disorder" and does not require any knowledge of the biochemical nature of the disorder (i.e. a mutated protein that is believed to cause the disorder does not need to be known) . Traditional approaches depend on assumptions concerning the disease process (or other phenotypes of interest, including ones generally viewed as positive, such as high lean mass) that might implicate a known protein as a candidate to be evaluated. The genetic localization approach using linkage analysis and the markers provided herein (i.e., those linked to the gene for the various phenotypes) can be used to gradually reduce the size of the region in order to determine the location of the specific mutated gene as precisely as possible. After the gene itself is discovered within the candidate region, the messenger RNA and the protein can be identified and, along with the DNA, can be checked for mutations using conventional biochemical methods.

Further details regarding linkage analysis are provided in the Examples which follow and in, for example, U.S. Patent No. 5,691,153 to Recker et al . , which is hereby incorporated by reference.

This latter approach has practical implications since knowing the general location of the gene (for example, as disclosed above and in the Examples which follow) can be used for prenatal diagnosis even before the gene for the phenotype of interest (e.g., which causes high body mass index) is identified. Thus, linkage analysis using the markers disclosed herein can enable families to know whether they are carriers of a gene for the phenotype of interest .

As indicated above, the detection method of the present invention includes analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a specified region of the subject's genome and which is linked to the gene associated with the bone property of interest . As used herein, "polymorphism" is meant to encompass any DNA sequence which is linked to the gene associated with the phenotype of interest, such as those which are located within such gene and those which are located sufficiently near such gene such that the gene and the polymorphic marker are linked, for example, as evidenced by a sufficiently high LOD score (e.g., an LOD score greater than or equal to 0, such as greater than or equal to 0.5, greater than or equal to 1, greater than or equal to 1.5, greater than or equal to 2 , greater than or equal to 2.5, greater than or equal to 3, greater than or equal to 3.5, and/or greater than or equal to 4) or other acceptable statistical linkage determination.

The polymorphism can be detected by a variety of methods. One method uses radioactive nucleotides in PCR amplification of the polymorphism, but other detection methods such as ligase chain reaction ("LCR") can also be used. The polymorphism can be detectably labeled by a radioisotope or by chemical modification enabling direct detection of the polymorphism. Fluorescent or colorimetric means, can also be used. Detection of the polymorphism can be indirect, e.g. a radioactive complementary strand of DNA, resulting from incorporation of radioactive nucleotides in a polymerase chain reaction. The polymorphism can also be detected by comparing the molecular weight of the protein (or peptide) encoded thereby to the molecular weight of the protein encoded by the wild-type DNA. Such detection involves gel electrophoresis and detecting of bands corresponding to particular molecular weights. For example, in the case where the method of the present invention is used to gradually reduce the size of the region in order to determine the location of the specific mutated gene (or other genetic cause of the phenotype of interest) as precisely as possible, analysis can be carried out by amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with the phenotype of interest by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism. Further details regarding this process are provided in the Examples which follow and in, for example, U.S. Patent No. 5,691,153 to Recker et al . , which is hereby incorporated by reference.

The present invention is further illustrated by the following examples. EXAMPLES

Example 1 -- Linkage and/or Association of Genes for the VDR, BGP, and Parathyroid Hormone ("PTH") with Bone Mineral Density

Subjects : The study subjects came from an expanding database being created for a whole genome linkage study aimed at searching for genes underlying bone mineral density ("BMD") variation and osteoporotic fracture risk. Only healthy people (defined by the exclusion criteria to be detailed below) were included in the analyses. All the study subjects were Caucasians of European origin. 53 pedigrees with 630 subjects (248 males and 382 females) from 2-4 generations were analyzed. The pedigrees vary in size from 3 to 99 individuals, with a mean of 11.7 (±SE=2.4). Each pedigree was identified through a proband having BMD Z- scores <. -1.28 at the hip or spine so that the probands were selected from the bottom 10 percent of the population BMD variation with the purpose of achieving higher statistical power than random sampling. BMD values are expressed as Z-scores that adjust for age, gender, and ethnic difference in general referent healthy populations. The exclusion criteria for the study subjects were a history of (1) serious residuals from cerebral vascular disease; (2) diabetes mellitus, except for easily controlled, non-insulin dependent diabetes mellitus; (3) chronic renal disease; (4) chronic liver disease or alcoholism; (5) significant chronic lung disease; (6) corticosteroid therapy at pharmacologic levels for more than 6 months duration; (7) treatment with anticonvulsant therapy for more than 6 months duration; (8) evidence of other metabolic or inherited bone disease such as hyper- or hypoparathyroidism, Paget ' s disease, osteomalacia, osteogenesis imperfecta or others; (9) rheumatoid arthritis or collagen disease; (10) recent major gastrointestinal disease (within the past year) such as peptic ulcer, .malabsorption, chronic ulcerative colitis, regional enteritis, or any significant chronic diarrhea state; (11) significant disease of any endocrine organ that would affect bone mass; (12) hyperthyroidism; (13) any neurologic or musculoskeletal condition that would be a non-genetic cause of low bone mass; and (14) any disease, treatment, or condition that would be a non-genetic cause for low bone mass. The exclusion criteria were assessed by nurse-administered questionnaires and/or medical records. Genotvping: For each subject, blood (20cc) was drawn into lavender cap (EDTA containing) tubes by certified phlebotomists and stored chilled (~4°C) until DNA extraction that was normally completed within the next five calendar days . DNA was extracted by employing a kit (Gentra Systems, Inc; Puregene DNA Isolation Kit; Cat# D-5000; Minneapolis, MN) following the procedures detailed in the kit . DNA was genotyped for the restriction fragment length polymorphism ("RFLP") at the following markers, respectively: the Apal RFLP (in intron 8) and Fokl RFLP (in exon 2) inside the VDR gene,⁽¹⁾ the Hindi11 RFLP (in the promoter region) of the BGP gene, ⁽²⁾ and the BstBI RFLP (in intron 2) of the PTH gene.^t3)

Our genotyping procedures for these markers were modified from those of Tokita et al . ⁽⁴⁾ and Uitterlinden et al . ⁽⁵⁾ for the Apal RFLP, Harris et al . ^(s) for the Fokl RFLP, Dohi et al . ⁽²⁾ for the Hindi11 RFLP, and Mullersman et al . ⁽³⁾ for the BstBI RFLP. Briefly, for the Apal RFLP inside the VDR gene, the forward primer in intron 8 (5' -CAG AGC ATG GAC AGG GAG CAA G-3') and the reverse primer in exon 9 (5'-GCA ACT CCT CAT GGC TGA GGT CTC A-3') were used in PCR to produce a 745 bp DNA fragment. For the FoΛ:I RFLP inside the VDR gene, the forward primer in intron 1 (5' -AGC TGG CCC TGG CAC TGA CTC TGC TCT-3') and the reverse primer in intron 2 (5'- ATG GAA ACA CCT TGC TTC TTC TCC CTC-3') were used in PCR to generate a DNA fragment of 265bp. For the HindiII RFLP inside the BGP gene, the forward primer in promoter region (5'-CCG CAG CTC CCA ACC ACA ATA AGC T-3') and the reverse primer in exon 1 (5' -CAA TAG GGC GAG GAG T-3') were used in PCR to generate a DNA fragment of 253 b . For the BstBI RFLP inside the PTH gene, the forward primer in intron 1 (5' -CAT TCT GTG TAC TAT AGT TTG-3') and the reverse primer in 3' flank region (5' -GAG CTT TGA ATT AGC AGC ATG-3') were used in PCR to generate a DNA fragment of 600 bp. The PCR amplification was all conducted in reaction mixtures each containing 10.08μl ddH₂0, 2μl lOx PCR buffer, 1.5mM MgCl₂, dNTP (200μM each), 0.6 U Taq Polymerase (AMPLITAQ GOLD with GENEAMP^Φ, Applied Biosystems, NJ, USA), 0.4μM each of the two primers for each marker, and lμl (~50ng/μl) of genomic DNA. The PCR was performed on PE 9700 thermocyclers (GENEAMP PCR System 9700_; Applied Biosystems Foster City, CA, USA) . PCR cycling conditions for the four markers were as follows. For the VDR Apal marker, they were 94°C lmin, 60°C lmin, and 72°C lmin each, 35 cycles. For the VDR Fokl marker, they were 94°C 30s, 60°C 30s, and 72°C 30s each, 35 cycles. For the PTH BstBI marker, they were 94°C lmin, 50°C lmin, and 72°C 2min each, 35 cycles. For the PTH Hindi11 marker, they were 94°C 30s, 53°C 30s, and 72°C lmin each, 35 cycles. These cycling conditions were preceded by 10 minutes at 94°C for denaturing and followed by 10 minutes at 72°C for extension. After PCR amplification, 8 μL of the respective PCR products were removed and digested with the following restriction endonucleases respectively at their respective temperatures (5U Apal at 25 °C, 4U Fokl at 37 °C, 5U BstBI at 65 °C, 5U Hindi11 at 37 °C) (Life Technologies, Grand Island, NY) , all for 3h. Uncut and digested samples were electrophoresed in 2% METAPHOR™ agarose gels (FMC Inc., Rockland, ME, USA) in IX TBE buffer and 0.3μg/ml ethidium bromide. Gels were then visualized on a transilluminator under UV light and photographed. The absence and presence of the Apal, Fokl , BstBI, and Hindlll restriction sites in the three candidate genes were designated as A and a alleles, F and f alleles, B and b alleles, and H and h alleles, respectively. The program PedCheck (available at http://watson.hgen.pitt.edu/- register/soft_doc .html) was employed for verifying Mendelian inheritance of all the marker alleles. ⁽⁷⁾ Measurement : BMDs of spine and hip were measured by a Hologic 1000, 2000+, or 4500 scanner

(Hologic corporation, Waltham MA) . All machines were calibrated daily, and long term precision was monitored with external spine and hip phantoms . Hip and spine were chosen because they are the most common osteoporotic fracture sites. Short-term precision in humans is 0.7% for ^'spine BMD and 1.0% for hip BMD. Constant quality assurance procedures and surveillance were maintained. For the spine, our quantitative phenotype was combined BMD of L.₄. For the hip, it was combined BMD of the femoral neck, trochanter, and intertrochanteric region. Weight was measured at the same visit when the BMD measurements were taken. Data obtained from different machines were transformed to a compatible measurement/ and members of the same pedigree were usually measured on the same type of machine.

Statistical Analyses: We performed statistical analyses to test for association, linkage, and association and linkage (transmission disequilibrium test ("TDT")) between each of the markers and BMD at the spine and hip. An association test between a marker and a quantitative trait was developed by Abecasis et al . ^(8> for pedigree data, and the TDT in pedigrees was developed by Abecasis et al . ⁽⁹⁾ . Both of these types of analyses have been implemented in a program QTDT (for quantitative trait locus transmission disequilibrium test) which is available on the internet (http://www.well.ox.ac.uk/- asthma/QTDT) . These tests were all developed under a variance component framework. The permutation procedure built in the QTDT may yield significance levels (p- values) of the tests that are not biased by (and thus robust to) the ascertainment schemes of pedigrees as in this study. In the QTDT program, population stratification can also be tested. Only when the result for population admixture is not significant, is the test for population association of a marker with BMD variation warranted. The linkage test was also performed by the variance component linkage analyses for quantitative traits . ^(10"12) The variance component analysis is based on specifying the expected genetic covariances between arbitrary relatives as a function of the identity by descent at a given marker locus. The analysis considered the phenotypic and genetic information from all pedigree members simultaneously. The analysis assumed multivariate normality of phenotypic values, additive genetic effects, and no interaction between genes and the residual. The common familial environmental effects were assumed to be negligible, which is reasonable and supported by previous studies . ^C13"15) The QTDT also provides a module for linkage testing; however, this module does not have the capacity to account for ascertainment of pedigrees via extreme probands as in this study. Hence, we also tested linkage using the program SOLAR (for Sequential Oligogenic Linkage Analysis Routines) ⁽¹²⁾ , which is available on the internet (http : //www. sfbr.org/sfbr/public/software/solar/- solar.html) . The ascertainment scheme of pedigrees based on the low BMD values of probands was accounted for in analyses with SOLAR by identifying to the program the probands for each pedigree. The conditional likelihood models built in the program then will account for the ascertainment by the proband status and the cutoff BMD values for the probands .

In all the statistical analyses, age, sex, and weight were adjusted as covariates (if having significant effects in our sample) to adjust for raw BMD values (not the Z-scores) . These factors can affect BMD variation significantly. Analyses were also performed without adjusting for these covariates. Adjustment for significant covariates in genetic analyses can generally increase the genetic signal to noise ratio (i.e., h² estimates) by decreasing the proportion of the residual phenotypic variation attributable to random environmental factors . This can improve statistical power in our association and/or linkage analyses. The BMD data were tested by graphical methods and found not to deviate from normal distributions . ^{(1S)' '} Marker allele frequencies were obtained by maximum likelihood estimation in SOLAR. Hypothesis testing was conducted by the maximum likelihood method. The method compares the maximum likelihoods obtained in the full model (with association, or linkage, or both association and linkage) and the nested null model (without association, or linkage, or without either association or linkage) . The QTDT program generates p-values for various tests (asymptotic χ²-tests or permutation tests) . The SOLAR program generates LOD scores that can be converted to approximate p-values through a χ²-distribution. ⁽¹⁷⁾

Results : The basic characteristics of the study subjects stratified by age and sex are summarized in Table 1. Some information about the family structure of the study pedigrees is summarized in Table 2.

TABLE 1. Basic characteristics of the study subjects stratified by age of each decade.

Note, w thn each cell of the second to sixth columns with three numbers, data are the mean, the standard deviation (the number within the parentheses) , and the sample size (the number within the brackets) . For each age strata, F and M indicate data from females and males, respectively. There are a total of 673 subjects from the 53 pedigrees summarized for this table. Forty-three of these subjects cannot be amplified for the markers (probably due to poor quality or degradation of the DNA extracted) employed or do not have DNA in our archive and only have phenotype data. However, since the genotypes of these 43 subjects can be unambiguously inferred from their relatives, their phenotype data are useful in linkage analyses. Therefore, their phenotype data are also included in the summary for the above table. Analyses (not shown) without inclusion of the phenotype data of these 43 subjects do not yield qualitatively different results. TABLE 2. Relationships used in linkage analyses by SOLAR.

It can be seen in Table 2 that there are about 1,380 parent offspring pairs, 1,249 sibling pairs, 1,098 grandparent-grandchild pairs, 2,589 first cousin pairs, etc., reflecting the richness of the genetic information for linkage analyses in our sample. The frequencies of genotypes and alleles, together with the genotype data missing rate, are summarized in Table 3. Missing genotype data include those that failed to be amplified in PCR reaction even after three times of repeated experiments and those that did not pass a Mendelian inheritance check within pedigrees with the PedCheck program. The missing rate for genotype data is generally less than 1% except at the VDR Apal marker where it is 7.7%. Except for the PTH BstBI marker, the genotypes do not generally deviate from Hardy-Weinberg equilibrium despite the fact that the data are from 53 pedigrees and not from random and unrelated population samples.

We found significant (p<0.05) or marginally significant (p<0.07) associations when testing relationships of the marker genotypes with BMD variation by regular analyses of variance ( "ANOVA" ) , which is commonly used in association studies and which ignores relatedness of the subj ects in our sample (Table 3 ) . None of the tests for population admixture is significant for the four markers (Table 4 ) in the study population . For association tests with the QTDT, BGP Hindi I I marker genotypes are significantly associated with spine BMD variation (Table 5 ) .

TABLE 3 . Allele and genotype frequencies and genotype data missing rates .

H. -W . (Hardy-Weinberg) test is through the regular χ²-test . The genotype data missing rate was determined by sample replication and repetition experiments of at least three times and data analyses by PedCheck. p-value of the H. -W. test conveys information about the extent to which genotype frequencies deviate from H. -W. equilibrium that may be due to population stratification/ admixture at individual loci . The smaller a p-value is , the larger the deviation is expected to be , with p-values less than 0 . 05 being considered significant .

TABLE 4 . Phenotype distribution among the genotypes

The reported means (SD) are for unadjusted BMD values . ANOVA tests for equality of mean BMD values among various genotypes at each candidate gene marker after accounting for significant covariate effects of age, sex, and weight .

TABLE 5 . Results of tests of population stratification, association, linkage , and linkage and association .

VDR Apal VDR Fokl BGP Hindi11 PTH BstBI

Tests of population stratification

Spine BMD 0.84 1.00 0.50 0.70 Hip BMD 0.16 0.57 1.00 0.74

Association tests

Spine BMD 0.37 0.89 0.15 0.22 Hip BMD 0.84 0.38 0.05 0.09

Linkage tests with QTDT

Spine BMD 0.042 0.036 0.19 0.44 Hip BMD 0.093 0.086 0.0005 1.00

Linkage tests with Solar

Spine BMD 0.033 0.026 0.092 0.43 Hip BMD 0.13 0.24 0.0005 1.00

TDT (tests of association and linkage)

Spine BMD 0.028 0.042 0.35 0.19 Hip BMD 0.11 0.093 0.0019 1.00

Interesting and compatible results emerge (Table 5) in tests for linkage with both the QTDT and SOLAR programs . It is notable that both the VDR Apal and Fokl markers are linked to spine BMD variation, but not to hip BMD variation. The BGP Hin iII marker is linked to hip BMD variation but not to the spine BMD variation. More interestingly, when testing for both linkage and association by TDT with the QTDT, we find significant results for linkage and association between spine BMD variation and the VDR Apal and Fokl markers and between hip BMD variation and the BGP HindiII marker.

Data not shown indicate that analyses not adjusting for other covariates such as age, sex, and weight showed qualitatively the same results with significance strengthened in several cases. For example, the p-values of linkage tests for the VDR Apal and Fokl markers with QTDT changed to 0.0070 and 0.0094 respectively, and those with SOLAR changed to 0.0014 and 0.040 respectively. The TDT for linkage and association with QTDT changed to 0.0038 and 0.0075 respectively for the VDR Apal and Fokl markers . These results render the significance of our tests of linkage and TDT unchanged even after we apply Bonferroni correction for the multiple markers tested in our study. Therefore, the linkage results and the TDT results for linkage and association seem to be robust.

For those markers with significant association (either by regular ANOVA or QTDT) , linkage (by QTDT and SOLAR) , and linkage and association (by TDT in the QTDT program) , the allele a of the VDR Apal marker and the allele F of the VDR Fokl marker are associated with larger spine BMD values; the allele h of the BGP HindiII marker is associated with larger hip BMD values. The different effects of the VDR and BGP genes on spine and hip BMD values are noteworthy. The apparent discrepancy of the p-values of various tests for linkage alone, association alone, or linkage and association (Tables 4 and 5) may reflect the different power associated with different tests and/or the different sensitivities of various tests to confounding effects such as potential population admixture.

Further details with regard to this Example 1 can be found in Deng et al . , "Tests of Linkage and

Association of Vitamin D Receptor Gene, Osteocalcin Gene, and Parathyroid Hormone Gene to Bone Mineral Density in Caucasian Pedigrees," J. Bone Miner. Res., 17:678-686 (2002), which is hereby incorporated by reference.

Example 2 -- Identification of Genomic Regions Linked and/or Associated with Spine, Hip, and Wrist Bone Mineral Density

Sub ects : All the study subjects were Caucasians of European origin as ascertained by questionnaires administered by research nurses. Only healthy people (defined by the exclusion criteria set forth below) were included in the analyses. 53 pedigrees with 630 subjects (248 males and 382 females) from 2-4 generations were analyzed. There were more female than male subjects, largely due to the higher propensity to volunteer in a genetic study of this type among females. Among the study pedigrees, one are two-, forty-one are three-, and eleven are four-generation pedigrees. The pedigrees vary in size from 3 to 99 individuals, with a mean of 11.7 (±SE=2.4) . The pedigrees were identified through a proband having BMD Z-scores <. -1.28 at the hip or spine. Hence, the probands were selected from the bottom 10 percent of the population BMD variation with the intended purpose of achieving higher statistical power than random sampling. BMD values expressed as Z- scores adjust for age, gender, and ethnic difference in general referent healthy populations. The exclusion criteria for the study subjects were a history of (including past as well as current disease conditions, unless otherwise specified) the medical conditions that were detailed in Example 1. The exclusion criteria were assessed by nurse-administered questionnaires and/or medical records and applied most rigorously to potential subjects contacted between ages 25-50. About 5.1% of the total people screened were excluded from our recruitment due to their meeting at least one of the exclusion criteria.

Genotyping-. For each subject, blood (20cc) was drawn into lavender cap (EDTA containing) tubes by certified phlebotomists. DNA was extracted by employing a kit (Gentra Systems, Inc; Puregene DNA Isolation Kit; Cat# D-5000; Minneapolis, MN) following the procedures detailed therein. DNA was genotyped using fluorescently labeled markers commercially available through Perkin Elmer Applied Biosystems (ABI PRISM Linkage Mapping Sets Version 2, Norwalk, CT) , as previously described. ^(18~19) A genetic database management system (GenoDB) ⁽²⁰⁾ was employed to manage the genotype data for linkage analyses . PedCheck was employed for checking the conformation to Mendelian inheritance pattern at all the marker loci and for checking the relationships of family members within pedigrees. The genotyping error rate, determined by the procedures described earlier'^19"21' , was about 0.3%. 380 markers (including 362 on autosomes) were successfully genotyped. These markers have an average population heterozygosity of -0.79.

Measurement : BMDs of spine, hip, and wrist were measured by a Hologic 1000, 2000+, or 4500 DXA (dual energy X-ray absorptiometry) scanner (Hologic corporation, Waltham MA) . All machines were calibrated daily, and long term precision was monitored with external spine and hip phantoms. Short-term precision in humans, as determined by the method of Glύer et al . ⁽²²⁾ with repeated measurements on at least 27 subjects for a single type of machine, is 0.8% for spine BMD, 0.6% for hip BMD, 1.1% for wrist BMD on Hologic 1000; and 0.8% for spine BMD, 1.0% for hip BMD, 2.6% for wrist BMD on Hologic 2000+; and 0.9% for spine BMD, 1.4% for hip BMD, and 2.3% for wrist BMD on Hologic 4500. For the spine, our quantitative phenotype was combined BMD of L_1-4. For the hip, it was total BMD of the femoral neck, trochanter, and intertrochanteric region provided by the instruments. For the wrist, it was ultra distal BMD. All DXA machines report BMD in g/cm². Weight was measured at the same visit when the BMD measurements were taken. Data obtained from different machines were transformed to a compatible measurement, and members of the same pedigree were usually measured on the same type of machine.

Statistical Analyses: A variance component linkage analysis^(10~12) for quantitative traits was performed. Briefly, the analysis was based on specifying the expected genetic covariances between arbitrary relatives as a function of the identity by descent at a given marker locus . The analysis considers the phenotypic and genetic information from all pedigree members simultaneously. The analysis assumed joint multivariate normality of phenotypic values, additive genetic effects, and no interaction between genes and the residual variation. The common familial environmental effects were assumed to be negligible, which is reasonable and supported by previous studies . ^{(13~15,23~24)} The SOLAR program'¹²' was employed. The ascertainment scheme of pedigrees based on the low BMD values of probands was accounted for in the analyses by identifying to the program the probands and their BMD values for each pedigree. The built-in modules of the SOLAR program can account for the ascertainment scheme by using cut-off BMD values of the probands and conditional likelihoods in LOD score computation.

In linkage analysis, age, sex, and weight were adjusted as covariates for raw BMD values (not the Z- scores) , as these generally affect BMD variation and tested to be significant in our sample in a statistical screen for important covariates. Z-scores of BMD reported by the Hologic machines adjust for age and sex (but not weight) effects in referent populations provided by the manufacture of the scanners and our BMD phenotype data for linkage analyses are those adjusting the raw BMD data for age, sex, and weight according to their effects in our own sample. Analyses were also performed without adjusting for some or any of these covariates.

Adjustment for significant covariates in genetic analyses can generally increase the genetic signal to noise ratio in linkage detection by decreasing the proportion of the residual phenotypic variation attributable to random environmental factors . ^<1S) Comparison of the analyses with and without adjustment for a significant covariate may shed light on the genomic regions identified as to their direct importance for the trait per se or indirect importance via the influence on the covariates only. The BMD data were tested by graphical methods^(1S) and found not to deviate from normal distributions . The variance component analyses implemented in SOLAR are quite robust to reasonable violations of normality of the data.^(2S) Using SOLAR, two-point and multi-point linkage analyses were performed. When a putative QTL is suggested, the proportion of phenotypic variation attributable to this QTL can be estimated by SOLAR. The estimate is usually an upper bound of the genetic effect due to the locus. ⁽²⁷⁾ Results : Detailed information about the family structure of the study pedigrees has been summarized elsewhere. ⁽¹⁹⁾ Mainly, there are 1,249 sibling pairs, 1,098 grandparent-grandchild pairs, and 2,589 first cousin pairs, etc. The average Z-scores (±SE) of spine, hip, and wrist BMD are -0.12+0.05, -0.22+0.04, and 0.09+0.05, respectively, for all the subjects in the sample, reflecting the sampling scheme of our pedigrees which were ascertained through probands of extremely low BMD values at spine and/or hip.

The results for the chromosomes that had maximum LOD scores ("MLS") close to or greater than 2.0 in multipoint linkage analyses at any one of the three skeletal sites are summarized in Figure 1, and the results for the other chromosomes are summarized in Figure 2. In Figures 1 and 2, the solid line is for spine BMD, the dashed line is for hip BMD, and the dot dashed line is for wrist BMD. Since the current version of SOLAR does not handle multipoint analyses for X chromosome, we plotted two-point LOD score results for the X chromosome and presented them in Figure 2 to convey the linkage signal pattern. For the results presented, BMD were -adjusted with multiple regression for significant covariates of age, sex, weight, and height. The results (not shown) for the linkage analyses for BMD values that were not adjusted for the covariates showed similar pattern in LOD scores and qualitatively the same results, suggesting the importance (if indeed exists) of the genomic regions identified here is direct on BMD rather than indirect through a covariate analyzed. In fact, our whole genome linkage scan results (described in Example 4 and elsewhere^Cl9) for BMI (revealed genomic regions for BMI different from those revealed here for BMD.

For the spine BMD, four genomic regions were identified that may contain putative QTLs . Specifically, a MLS of 3.08 at 152 cM from pter on chromosome 4 in multipoint linkage analyses and a LOD score of 2.12 at the marker D4S413 in two-point linkage analyses were achieved in the genomic region 4q31-32. A MLS of 2.96 at 169 cM from pter on chromosome 12 in multi-point analyses and a MLS of 2.17 at D12S1723 in two-point analyses were achieved in 12q24. A MLS of 2.43 at 103 cM from pter on chromosome 13 in multipoint analyses and a LOD score of 1.77 at D13S285 in two-point analyses were achieved in 13q33-34. A MLS of 1.93 at 0.0 cM from pter on chromosome 7 in multi-point analyses and a LOD score of 2.28 at D7S531 in two-point analyses were achieved in

7p22. In addition, in two-point analyses, a LOD score of 1.6 was achieved at D15S165 in 15pll; the MLS is 0.76 in the genomic region (14cM from pter on chromosome 15) . At the spine, for the putative QTL with the strongest evidence of linkage on 4q31, -30.3% of BMD variation

(after adjusting for age, sex, weight, and height) may be attributable to this locus. For the hip BMD, three genomic regions were identified that may contain putative QTLs. A MLS of 2.29 at 170 cM from pter on chromosome 10 in multipoint analyses and a LOD score of 1.97 at D10S1651 in two-point analyses were achieved in 10q26. In addition, in two- point linkage analyses, a LOD score of 1.69 was achieved at D12S368 on 12ql3 and a LOD score of 1.58 was achieved at D17S1857 on 17pll, with corresponding multipoint MLSs being 0.99 and 1.2 respectively. At the hip, for the putative QTL with the strongest evidence of linkage on 10q26, -29.2% of BMD variation (after adjusting for age, sex, weight, and height) may be attributable to this locus .

For the wrist BMD, four genomic regions were identified that may contain putative QTLs. A MLS of 2.26 in multi-point analyses at 158 cM from pter on chromosome 4 and a LOD score of 2.53 at D4S413 in two-point analyses were achieved in 4q32. A MLS of 1.87 in multi-point analyses at 16 cM from pter on chromosome 9 and a LOD score of 1.74 in two-point analyses at D9S285 were achieved in 9p22-24. A LOD score of 1.99 was achieved at D17S1852 in 17pl3, and a LOD score of 1.82 in two-point analyses was achieved at D3S1297 in 3p26, with corresponding MLSs of 1.48 and 1.25 achieved in multi- point analyses in the respective genomic regions. At the wrist, for the putative QTL with the strongest evidence of linkage on 4q32, -25.5% of BMD variation (after adjusting for age, sex, weight, and height) may be attributable to this locus. Markers and genomic regions with LOD scores greater than 1.5 in two- or multi-point analyses are summarized in Table 6. TABLE 6. Markers and genomic regions with LOD scores > 1.5 in two- or multi-point analyses.

Two-point analyses

Multi-point analyses

Further details regarding the experiments described in this Example 2 can be found in Recker et al . , "Role of Genetics in Osteoporosis," Endocrine , 17(l):55-66 (2002), which is hereby incorporated by reference .

Example 3 -- Identification of Genomic Regions Linked and/or Associated with Spine, Hip, and Wrist Bone Size Sub ects: The study was carried out with a group of study subjects substantially similar to the group used in Example 1.

Genotyping; Genotyping procedures and the statistics associated with replication and repeated genotyping procedures were substantially the same as set forth in Example 1. 380 markers (including 362 on autosomes) were successfully genotyped. These markers have an average population heterozygosity of -0.79 and spaced on average ~8.6cM between adjacent markers throughout the human genome.

Measurement : Bone sizes of spine, hip, and wrist were measured by dual energy X-ray absorptiometry ("DXA") with a Hologic 1000, 2000+, or 4500 scanner (Hologic Corporation, Waltham, MA) . Height and weight were measured on the visit at which the bone size measurements were taken. All machines were calibrated daily, and long-term precision was monitored with external spine, hip, and wrist phantoms. Constant quality assurance procedures and surveillance were maintained. For the spine, our quantitative phenotype was combined bone projected area of L^^ . For the hip, it was combined bone projected area of the femoral neck, trochanter, and intertrochanteric region. For the wrist, it was the area of the ultra-distal forearm site. All DXA machines report bone size as area measurements in units of cm². Usually, for the hip and wrist, the non- dominant body side was measured. The coefficient of variation ("CV") of the measurement was determined on the Hologic 2000+ scanner for 121 random subjects. The CV of bone size measurement was 1.11%, 1.94%, and 2.87%, respectively, at the spine, hip, and wrist. CV was similar for those measurements obtained on Hologic 1000 and 4500 scanners. Bone size measurements by different scanners in our center are highly compatible with one another and are well within the precision limits. In addition, when treating scanner type as a covariate in analyses, its effect is not significant. Members of the same pedigrees were generally measured by the same type - Sl ¬

ot DXA machines. Therefore, combined analyses of the pedigrees measured by different scanners are warranted. Statistical Analyses: The variance component linkage analysis'¹⁰"¹²' for quantitative traits was performed. The analysis is based on specifying the expected genetic covariances between arbitrary relatives as a function of the identity by descent at a given marker locus . The analysis considers the phenotypic and genetic information from all pedigree members simultaneously. The analysis assumed joint multivariate normality of phenotypic values, additive genetic effects, and no interaction between genes and the residual. The common familial environmental effects were assumed to be negligible, as discussed in Examples 1 and 2. The program employed was SOLAR.'¹²' The ascertainment scheme of pedigrees based on the low BMD values of probands leads to lower than average bone size values (see Results) . The ascertainment scheme was accounted for in the analyses by identifying to the program the probands and their phenotypic values for each pedigree. The built-in modules of the SOLAR program will then be able to account for the ascertainment scheme by using conditional likelihoods in LOD score computation.

In linkage analysis, age, sex, and height were adjusted as covariates to adjust for bone size values, as these generally affect bone size variation significantly. Analyses were also performed without adjusting for some of these covariates. Adjustment for significant covariates in genetic analyses can generally increase the genetic signal to noise ratio (i.e., h² estimates) in linkage detection by decreasing the proportion of the residual phenotypic variation attributable to random environmental factors. This may thus improve statistical power in our linkage analyses. Comparison of the analyses with and without adjustment for a significant covariate may shed light on the genomic regions identified as to their direct importance for the trait per se or indirect importance via the influence on the covariate only. The bone size data were tested by graphical methods'¹⁶' and found not to deviate from normal distributions. The variance component analyses implemented in SOLAR are quite robust to reasonable violations of normality of the data.'²⁹' Marker allele frequencies were obtained by maximum likelihood estimation in SOLAR. Hypothesis testing for linkage was conducted by the maximum likelihood method by investigating the relationship of genetic covariances and the identical by descent between arbitrary relatives.

The method compares the maximum likelihoods obtained in the full model (with linkage so that the locus is a QTL and accounts for some additive genetic variance) and the nested null model (without linkage and the locus is not a QTL) . The difference between the two log₁₀ likelihoods yields a LOD score. Twice the difference of the log_e of the likelihoods of these two models is asymptotically distributed as a 1/2:1/2 mixture of a χ² variable and a point mass at zero'¹²' with 1 degree of freedom. Using SOLAR, two-point and multi-point linkage analyses were performed, respectively, for bone size at hip, spine, and wrist. LOD scores may be converted to approximate p- values (not accounting for multiple testing in whole genome scans) commonly employed in statistical testing through a χ²-distribution. ⁽¹⁷⁾ When a putative QTL is suggested, the^' proportion of phenotypic variation attributable to this QTL can be estimated by SOLAR. Results : The basic characteristics of the study subjects stratified by age and sex are summarized in Table 7. The bone size dynamics with aging in our sample was largely consistent with earlier studies. ⁽²⁸⁾ Some information about the family structure of the study pedigrees is summarized in Table 2 of Example 1.

It can be seen from Table 2 that there are more than 10,000 relative pairs informative for linkage analyses (including 1,249 sibling pairs, 1,098 grandparent-grandchild pairs, 1,993 avuncular pairs,

2,589 first cousin pairs, etc.), reflecting the richness of the genetic information for linkage analyses in our sample. In all the subjects in our sample, the mean (SE) of bone sizes adjusted for age, sex, and height at spine, hip, and wrists are, respectively, 61.39 (0.23), 36.92 (0.13), and 4.00 (0.02). In the probands, the mean (SE) of bone sizes adjusted for age, sex, and height at spine, hip, and wrists are, respectively, 53.67 (0.63), 33.63 (0.45), and 3.61 (0.04). The bone sizes are significantly (p<0.002) smaller at all the three sites in the probands, reflecting our sampling scheme through low BMD values and the correlation between BMD and bone size.

TABLE 7. Basic characteristics of the study subjects stratified by age of each decade.

Note, with n each cell with three numbers, data are the mean, the standard deviation (the number within the parentheses) , and the sample size (the number within the brackets) . Subjects without age information but with other phenotype information were not included in this table. There are a total of 673 subjects from the 53 pedigrees summarized for this table. Forty-three of these subjects cannot be amplified for the markers (probably due to poor quality or degradation of the DNA extracted) employed or do not have DNA in our archive and only have phenotype data. However, since the genotypes of these 43 subjects can be unambiguously inferred from their relatives, their phenotype data are useful in linkage analyses. Therefore, their phenotype data are also included in the summary for this table.

The results for the chromosomes that had a maximum LOD score greater than 2.0 in multipoint linkage analyses for bone size at any one of the three skeletal sites are summarized in Figure 3, and the results for the other chromosomes are summarized in Figure 4. In Figures 3 and 4, the solid line is for spine bone size, the dashed line is for hip bone size, and the dot dashed line is for wrist bone size. Since the currently available version of SOLAR does not handle multipoint linkage analyses for X chromosome, to convey the linkage signal patterns on the X chromosome, we plotted two-point LOD score results for the X chromosome and presented them in Figure 4. For the analysis results presented, bone size was adjusted with multiple regression for significant covariates of age, sex, and height. The results (not shown) for the linkage analyses for bone size that was not adjusted for covariates showed similar pattern in LOD scores and qualitatively the same results, suggesting the importance (if indeed exists) of the genomic regions identified here is direct on bone size rather than via the covariates. A few genomic regions were identified with LOD scores close to or greater than 1.50 in either multi-point linkage analyses and/or two-point linkage analyses (Figures 3 and 4 and Table 8) that can harbor QTLs for bone size variation.

TABLE 8. Markers and genomic regions with LOD scores > 1.5 in two- and multi-point analyses for bone size variation.

Two-point analyses

Multi-point Analyses

For the wrist bone size variation, four genomic regions were identified/suggested for putative QTLs. Specifically, the genomic region 17q23 may contain a QTL with a MLS of 3.01 (p=0.000098) at 77 cM from pter on chromosome 17 in multi-point linkage analyses and a LOD score of 3.98 (p=0.0000093) at the marker D17S787 in two- point linkage analyses. 2q37 may contain another QTL with a MLS of 2.28 (p=0.00060) at 263 cM from pter on chromosome 2 in multi-point linkage analyses and a LOD score of 1.77 (p=0.0022) at the marker D2S125. 9ql2 may contain a QTL with a MLS of 2.23 (p=0.0007) at 63 cM from pter on chromosome 9 in multi-point analyses and a LOD score of 1.56 (p=0.0037) in two-point analyses at the marker D9S175 on 9q21. The fourth noteworthy genomic region is the marker D4S412 on 4pl6 with a LOD score of 2.00 (p=0.0012) in two-point linkage analyses and a MLS of 1.18 (p=0.0098) at 5 cM from pter on chromosome 4 in multi-point analyses. For the putative QTL with the strongest evidence of linkage on 17q23 , up to 31.4% of the wrist bone size variation (after adjusting for age, sex, and height) may be attributable to this locus. The genetic effect estimated by SOLAR due to a putative QTL is generally over estimated and thus can be regarded as an estimate of the upper bound.'³⁰'

For the hip bone size variation, two genomic regions are suggested/noteworthy. 19pl3 may contain a QTL with a MLS of 2.83 (p=0.00016) at 38 cM from pter on chromosome 19 in multi-point analyses and a LOD score of 1.99 (p=0.0013) at the marker D19S226 in two-point analyses. 14qll achieved a MLS of 1.65 (p=0.0030) at 16 cM from the pter on chromosome 14. For the putative QTL with the strongest evidence of linkage on 19pl3, up to 36.4% of the hip bone size variation (after adjusting for age, sex, and height) may be attributable to this locus.

For the spine bone size variation, 2p25 may contain a QTL with a MLS of 1.54 (p=0.0039) at 31 cM from pter on chromosome 2 in multi-point analyses and a LOD score of 2.15 (p=0.0009) at the marker D2S305 on chromosome 2p21 in two-point analyses. For the putative QTL on 2p25, a maximum of 17.7% of the spine bone size variation (after adjusting for age, sex, and height) may be attributable to this locus. Example 4 -- Identification of Genomic Regions Linked and/or Associated with Obesity Phenotypes

Sub ects : The study was carried out with a group of study subjects substantially similar to the group used in Example 1. About 5.1% of the total people screened were excluded from our recruitment due to their meeting at least one of the exclusion criteria. The exclusion criteria applied might render the allele frequencies and thus the genetic effects of potential obesity QTLs different from those in our general population. This may be the case when some of the above disease status are genetically correlated with obesity, for which there is generally no evidence at present.

Genotyping: Except as noted below, genotyping procedures and the statistics associated with replication and repeated genotyping procedures were substantially the same as set forth in Example 1. PCR cycling conditions followed those suggested in the ABI PRISM Linkage Mapping Sets Version 2. Genotyping was performed using Applied Biosystems automated DNA sequencing systems (Models 377 and 310; Perkin Elmer-ABI ; Foster City, CA) running the GENESCAN™ and GENOTYPER™ softwares for allele identification and sizing. A genetic database management system (GenoDB) ⁽²⁰⁾ was employed to manage the phenotype and genotype data for linkage analyses. GenoDB was also employed for allele bining (including setting up allele bining criteria and converting allele sizes to distinct allele numbers), data quality control, and data formatting for PedCheck"' and linkage analyses by SOLAR. PedCheck was employed for checking the conformation to Mendelian inheritance pattern at all the marker loci and for checking the relationships of family members within pedigrees. The genotyping error rate, determined by at least three rounds of sample replication in experiments and data analyses by PedCheck, was about 0.3%. 380 markers (including 362 on autosomes) were successfully genotyped. These markers have an average population heterozygosity of -0.79 and spaced on average ~8.6cM between adj acent markers throughout the human genome .

Measurement : Fat mass and lean mass were measured by DXA with a Hologic 2000+, or 4500 scanner (Hologic Corporation, Waltham MA) . For the measurements from the two types of machines, the BMD measurements agreed within 1%, but the body mass measurements differed in an unsystematic way. For 24 people with scans on the same day on the two types of machines, the percentage difference in whole body mass is about 3%. All machines were calibrated daily. The body composition bar was used on every whole body scan on the Hologic 2000+ . On the Hologic 4500, the bar was not needed for the body scans; instead, it was scanned every week. In the early stage of the study, the subjects were recruited for studying osteoporosis only. Thus, we did not install the hardware and software to perform the "Body Composition Assessment" until later in the recruitment for the project. Therefore, only 289 subjects from 38 pedigrees had the data of fat mass, PFM, and lean mass. Softwares and hardware were constantly kept up-to-date during the implementation of the project. For the Hologic 2000+ scanner that was in service during 1994 to 1999, the software was updated from Version 5.67a to Version 5.71a. For the Hologic 4500 scanner that has been in service since 1997, the software has been updated from Version

8.19a to Version 8.26a. The PFM is the ratio of fat mass divided by body weight (i.e., the sum of fat mass + lean mass + bone mineral content) . The measurement precision of BMI as reflected by coefficient of variation ("CV") was 0.2%. The CV's for fat mass, PFM, and lean mass were 2.2%, 2.2%, and 1.0%, respectively, for measurements obtained on the Hologic 2000+ and 1.2%, 1.1%, and 0.7%, respectively, for measurements obtained on the Hologic 4500. Members of the same pedigree were usually measured on the same type of machine .

Statistical Analyses: A variance component linkage analysis'^10"12' for quantitative traits was performed. The analysis is based on specifying the expected genetic covariances between relatives as a function of the identity by descent at a given marker locus. The analysis considers the phenotypic and genetic information from all pedigree members simultaneously. The analysis assumed joint multivariate normality of phenotypic values, additive genetic effects, and no interaction between genes and the residual . The program employed was SOLAR. ⁽¹²⁾ The ascertainment scheme of pedigrees based on the low BMD values of probands leads to lower than average BMI values (see Results) . The ascertainment scheme was accounted for in the analyses by identifying to the program the probands and their phenotypic values for each pedigree. The built-in modules of the SOLAR program will then be able to account for the ascertainment scheme by using conditional likelihoods in LOD score computation. The statistical properties of the variance component analyses after the ascertainment correction have been preliminarily investigated. ^(29_31) In linkage analysis, age and sex were adjusted as covariates for the obesity phenotypic values, as these generally affect the variation of obesity phenotypes significantly in our study population. Analyses were also performed without adjusting for one or both of these covariates. Adjustment for significant covariates in genetic analyses can generally increase the genetic signal to noise ratio in linkage detection by decreasing the proportion of the residual phenotypic variation attributable to random environmental factors . ⁽²⁵⁾ This may thus improve statistical power in our linkage analyses. Comparison of the analyses with and without adjustment for a significant covariate may shed light on the genomic regions identified as to their direct importance for the trait per se or indirect importance via the influence on the covariate only. The variance component analyses implemented in SOLAR are generally robust to violations of normality of the data.^(2S) However, some types of nonnormality of the data may inflate the type one error rate in excess of specified nominal levels. ⁽³²⁾ The phenotype data were tested by graphical methods^(1S) and found not to deviate from normal distributions. Marker allele frequencies were obtained by maximum likelihood estimation in SOLAR. Hypothesis testing for linkage was conducted by the maximum likelihood method by investigating the relationship of genetic covariances and the identical by descent between relatives . The method compares the maximum likelihoods obtained in the full model (with linkage so that the locus is a QTL and accounts for some additive genetic variance) and the nested null model (without linkage and the locus is not a QTL) . The difference between the two log₁₀ likelihoods yields a LOD score. Twice the difference of the log_e of the likelihoods of these two models is asymptotically distributed as a 1/2:1/2 mixture of a χ² variable and a point mass at zero'¹²¹ with 1 degree of freedom. Using SOLAR, two-point and multi-point linkage analyses were performed, respectively, for the obesity phenotypes . LOD scores may be converted to approximate p-values (prior to accounting for multiple testing) commonly employed in statistical testing through a χ²~distribution. ^!17) When a putative QTL is suggested, the proportion of phenotypic variation attributable to this QTL can be estimated by SOLAR. The estimate is usually an upper bound of the genetic effect due to the locus.'²⁷'

Results : The basic characteristics of the study subjects stratified by age and sex are summarized in Table 9. Some information about the family structure of the study pedigrees is summarized in Table 10.

TABLE 9. Basic characteristics of the study subjects for BMI, fat mass, lean mass, and PFM, stratified by sex and age of each decade.

Note:' the numbers within each cell are the mean, the standard deviation (within parenthesis) , and the sample size (within brackets) . For each age stratum, F and M indicate data from females and males, respectively. For the BMI, the total sample size summarized is 658 and more than the 630 subjects genotyped. This is because, twenty-eight of these subjects cannot be amplified for the markers (probably due to poor quality or degradation of the DNA extracted) employed or do not have DNA in our archive and only have phenotype data. However, since the genotypes of these 28 subjects can often be unambiguously inferred from their relatives, their phenotype data are useful in linkage analyses. Therefore, their phenotype data are also included in the summary for the above table. TABLE 10. Relationships used in analyses by SOLAR.

It can be seen in Table 10 that, for the analyses for BMI, there are more than 10,000 informative relative pairs (including 1,249 sibling pairs, 1,098 grandparent- grandchild pairs, 1,993 avuncular pairs, and 2,589 first cousin pairs, etc.) . For the analyses for fat mass, lean mass, and PFM, there are nearly 6,000 informative relative pairs (including 744 sibling pairs, 710 grandparent-grandchild pairs, 1,148 avuncular pairs, and 1,500 first cousin pairs, etc.) . These large numbers of informative relative pairs reflect the richness of the genetic information for linkage analyses in our sample. The 'Correlations between BMI and spine and hip BMD are, respectively, 0.27 and 0.44, both significant at p<0.01. The mean (SE) of BMI adjusted for age and sex for all the subjects and probands in our sample are, respectively, 26.45 (0.21), 23.97 (0.63). The BMI value is significantly smaller (p<0.01) in the probands, reflecting our sampling scheme through low BMD values.

The results for the chromosomes that had a maximum LOD score greater than 2.0 in multipoint linkage analyses for any one of the four obesity phenotypes are summarized in Figure 5, the results for the other chromosomes are summarized in Figure 6. In Figures 5 and 6, the black solid line is for BMI, the grey dashed line is for PFM, the grey dot dashed line is for fat mass, and the black dash line is for lean mass . Since the current version of SOLAR does not handle multipoint linkage analyses for X chromosome, to convey the linkage signal pattern on the X chromosome, we plotted two-point LOD score results for the X chromosome and presented it in Figure 6. The results are also presented in Table 11.

TABLE 11. Markers and genomic regions with LOD scores greater than 1.5 in two- or multi-point linkage analyses for obesity phenotype variation

Two-point analyses

Multi-point analyses

For the analysis results presented, obesity phenotypes were adjusted with multiple regression for significant covariates of age and sex. The results (not presented) for the linkage analyses for obesity phenotypes that were not adjusted for covariates showed similar pattern in LOD scores and qualitatively the same results, suggesting the importance (if indeed exists) of the genomic regions identified here is direct on obesity phenotypes rather than through a covariate.

Notably (Figure 5 and Table 11), for BMI, a major QTL on 2ql4 is identified with a maximum LOD score (MLS) of 4.44 (p=0.000003) at 128 cM from pter on chromosome 2 in multipoint linkage analyses. In two- point linkage analyses, a LOD score of 4.04 (p=0.000008) is achieved at the marker D2S347 on 2ql4. For this putative major QTL for BMI, up to 28.2% of BMI variation (after adjusting for age and sex) may be attributable to this locus. In addition, the importance of this genomic region is also manifested for PFM and body fat mass. For PFM, 2ql4 may contain a QTL with a MLS of 2.10 (p=0.00093) at 128 cM from pter on chromosome 2 in multipoint analyses, and a LOD score of 1.91 (p=0.0015) is achieved at the marker D2S347 on 2ql4 in two-point analyses. For body fat mass, 2ql4 achieved a MLS of 2.21

(p=0.0007) at 128 cM from pter on chromosome 2 in multipoint analyses, and in two-point analyses, a LOD score of 2.03 (p=0.0011) is achieved at D2S347 on 2ql4. In addition to the genomic region 2ql4, a few other genomic regions were identified with LOD scores greater than 1.5 that may harbor QTLs for the obesity phenotypes under study (Figure 5 and Table 11) . For BMI, four additional genomic regions were identified or suggested. Ip36 may contain a QTL with a MLS of 2.09 (p=0.00095) at the terminal end of short arm on chromosome 1 in multipoint analyses. In two-point analyses, a LOD score of 2.75 (p=0.00019) is achieved at D1S468 on lp36. 4ql2 may contain a QTL with a MLS of 2.09 (p=0.00096) at 68 cM from pter on chromosome 4 in multipoint analyses. In two-point analyses, a LOD score of 2.29 (p=0.00058) is achieved at D4S1592 on 4ql2. Two genomic regions with LOD scores greater than 1.50 in either multi- or two-point linkage analyses (Figure 6, Table 11) are also noticeable. The genetic signals manifested in these genomic regions may deserve further close examination in extended samples and/or denser molecular markers. These noteworthy genomic regions include 6q27 with a MLS of 1.61 (p=0.0032) in multipoint analyses at 188 cM from pter on chromosome 6 in multipoint analyses, and those at the marker D6S281 on 6q27 with a LOD score of 1.77 (p=0.0021), the marker D2S160 on 2ql2 with a LOD score of 2.56 (p=0.00030), in two-point analyses.

For PFM, in two-point analyses, a LOD score of 1.95 (p=0.0014) is achieved at D2S206 on 2q36. 8q24 achieved a MLS of 1.54 (p=0.0039) in multi-point analyses . For fat mass, 6q27 achieved a MLS of 1.59

(p=0.0034) at 188cM from pter on chromosome 6 in multipoint analyses. In two-point analyses, a LOD score of 2.02 (p=0.0011) is achieved at D6S281 on 6q27. The other noteworthy genomic regions are 20ql3 that achieved a MLS of 1.64 (p=0.0030) at 69 cM from the pter in multipoint analyses, and the marker D8S549 on 8p22 that achieved a LOD score of 1.95 (p=0.0014) in two-point analyses .

For lean mass, we did not detect any genomic region showing a LOD score greater than 2.0 in multipoint or two-point linkage analyses. Some genomic regions with LOD scores greater than 1.50 are noteworthy. In multipoint analyses, these genomic regions include 12ql4 with a MLS of 1.64 (p=0.0030) at 82 cM from pter on chromosome 12, 17pl2 with a MLS of 1.63 (p=0.0031) at 33 cM from the pter on chromosome 17, and 7p22 with a MLS of 1.52 (p=0.0041) at 5 cM from pter on chromosome 7. In two- point analyses, a LOD score of 1..79 (p=0.0020) is achieved at D12S83 on 12ql4, a LOD score of 1.59 is achieved at D5S407 on 5qll.

Since the pedigree size varies dramatically from 3 to 99, we performed additional linkage analyses for the largest pedigree and for the rest of the pedigrees . We found that the evidence from the two independent sub-samples generally provide support for each other for the major significant results presented for the combined sample, although the significance is weaker in the sub-samples.

Further details with regard to this Example 4 can be found in Deng et al . , "A Genomewide Linkage Scan for Quantitative Trait Loci for Obesity Phenotypes," Am. J. Hum. Genet. , 70:1138-1151 (2002), which is hereby incorporated by reference.

Example 5 -- Linkage and/or Association of Polymorphism of the IL-6 Gene with Bone Mineral Density and Obesity- Related Phenotypes , Sub ects: All the study subjects were

Caucasians of European origin. Only healthy people were included in the analyses. The exclusion criteria were similar to those set forth in Example 1 and are detailed in Deng et al . ⁽³³⁾ The study included two groups of subjects. The first group of subjects was composed of 1,816 individuals from 79 multigenerational pedigrees. Each pedigree was identified through a proband with BMD Z-scores either < -1.28 or > +1.28 at the hip or spine so that the probands were selected from the bottom or top 10 percent of the population BMD variation with the purpose of achieving higher statistical power than with random sampling. In total, there were 3,393 sibling pairs, 316 grandparent-grandchild pairs, and 10,060 first cousin pairs . The second group was a randomly ascertained set of 636 individuals from 157 nuclear families, in which 62 families have one child, 43 families 2 children, 34 families 3 children, and the remainder 4 or more children.

Genotyping: DNA was extracted from whole blood using a commercially isolation kit (Gentra Systems, Inc., Minneapolis, MN, USA) following the procedures detailed in the kit. The dinucleotide (CA) repeat polymorphism of the IL-6 gene locus was genotyped. PCR primers were IL- 6-CAF, 5 ' -TTCTACATGACAGCAGAACAC-3 ' , and IL-6-CAR, 5 ' - TCTGTGGGAAAGTATATGTGC-3' ) . The forward primer was labelled at the 5' terminus with a fluorescent tag. PCRs were performed in a final volume of 8 μl containing lx PCR buffer, 1.5mM MgCl₂, 200μM each dNTP, 0.06 U Taq

Polymerase (Applied Biosystems, NJ, USA), 0.4μM each of the two primers, ~50ng of genomic DNA. Amplification conditions were 10 cycles at 95°C for 15 sees, 55°C for 15 sees, and 72 °C for 30 sec, followed by 20 cycles of 89°C for 15 sees, 55°C for 15 sees, and 72°C for 30 sec. Prior to the first cycle, initial denaturation was performed at 94 °C for 10 minutes and the last cycle was followed by an extension step of 10 minutes at 72 °C. PCR products were separated by electrophoresis on an ABI 3700 (Applied Biosystems, NJ, USA) . Gels were analyzed using

GENESCAN™ and GENOTYPER™ Analysis software (Applied Biosystems, NJ, USA) . The program PedCheck'⁷' was employed for verifying Mendelian inheritance of all the marker alleles and for checking the relationships of family members within pedigrees.

Phenotvping: BMD at the spine (L_x.₄) and hip (femoral neck, trochanter, and intertrochanter) , fat mass, and lean mass were measured by dual-energy x-ray absorptiometry ("DEXA") (Hologic, Waltham, MA) . The measurement precision as reflected by coefficients of variation for spine BMD, hip BMD, fat mass, and lean mass of 0.7%, 1.0%, 1.2%, and 0.7%, respectively. Weight and height were measured at the same visit when the BMD measurements were taken. BMI and PFM were calculated as described in Example 4.

Statistical Analyses: We performed testing for population stratification, association alone, linkage alone, and both association and linkage between the CA repeat polymorphism of the IL-6 gene, and BMD at the spine and hip, obesity-related phenotypes including BMI, fat mass, lean mass, and PFM using the program QTDT'^8"9-³⁴' , which is available on the internet (http://www.well.ox.ac.uk/asthma/QTDT) . Age and sex were used as covariates to adjust for BMI, fat mass, lean mass, and PFM, whereas age, sex, height, and weight were used as covariates to adjust for raw BMD values (not the Z-scores) . These factors generally affect BMD and obesity-related phenotype variation significantly. ⁽³⁵⁾

Results : The basic characteristic of the study subjects stratified by age and sex are summarized in Tables 12 and 13. TABLE 12. Basic characteristics of 1816 subjects from 79 multigenerational pedigrees.

Age Sex Ages Height Weight Spine Hip BMI Fat Lean PFM groups BMD BMD mass mass

(years) (years) (m) (kg) (g/m²) (g/m²) (kg/m²) (kg) (kg) (%)

20- M 25.0 1.81 85.8 1.10 1.10 26.2 18.7 66.5 21.0

29.99 (2.8) (0.07) (15.7) (0.13) (0.15) (4.5) (9.4) (9.2) (7.1)

[851 [84] [83] [85] [85] [83] [82] [82] [82]

F 25.6 1.66 66.9 1.06 0.97 24.3 22.0 44.5 32.2

(2.9) (0.06) (13.5) (0.18) (0.13) (5.0) (8.5) (5.8) (7.2)

[126] [126] [126] [125] [126] [126] [121] [121] [121]

30- M 35.5 1.79 89.0 1.08 1.06 27.6 21.3 67.3 23.4

39.99 (2.8) (0.07) (14.3) (0.13) (0.13) (4.0) (8.2) (8.2) (6.1) ri37] [1341 [134] ri371 [137] [134] [127} ri27] [127]

F 35.8 1.67 70.7 1.07 0.97 25.5 24.8 46.2 33.9

(2.7) (0.07) (14.4) (0.13) (0.14) (5.1) (9.7) (6.6) (7.4)

[210] [210] [2081 [210] [210] [208] [201] [201] [201]

40- M 45.1 1.79 90.3 1.08 1.06 28.2 22.9 67.3 24.9

49.99 (2.9) (0.07) (13.5) (0.15) (0.15) (3.8) (7.3) (8.0) (5.2) ri841 N821 [1821 [1841 ri841 ri821 [1761 ri761 [176]

F 44.7 1.65 72.7 1.05 0.94 26.8 26.6 45.6 35.8

(2.9) (0.06) (16.1) (0.14) (0-14) (5.5) (10.1) (6.7) (6.8)

[222] [222] [222] [222] [220] [221] [210] [210] [210]

50- M 54.2 1.77 90.7 1.09 1.04 28.8 24.2 66.5 26.

59.99 (3.0) (0.11) (13.4) (0.15) (0.13) (4.0) (7.5) (8.2) (5.1)

[102] [102] [102] [102] [102] [101] [99] [99] [99]

F 54.2 1.64 76.2 1.01 0.94 ^• 28.4 30.1 46.3 38.

(3.1) (0.05) (15.9) (0.15) (0.14) (5.5) (9.9) (6.7) (6.0)

[120] [120] [120] [120] [120] [120] [115] [115] [115]

60- M 65.0 1.77 90.6 1.09 1.00 29.0 23.9 66.1 26.0

69.99 (2.8) (0.07) (14.9) (0.20) (0.15) (4.4) (7.4) (8.3) (4.9)

T521 T521 T521 [511 T521 T52] T50] T501 [501

F 64.9 1.62 77.4 0.96 0.88 29.3 31.5 46.0 39.7

(3.0) (0.06) (17.4) (0.19) (0.17) (6.4) (10.8) (7.7) (6.4)

[87] [87] [85] [87] [86] [85] [79] [79] [79]

70- M 74.1 1.74 87.3 1.14 1.00 28.7 24.8 61.6 28.2

79.99 (2.7) (0.06) (12.5) (0.22) (0.14) (4.0) (7.9) (6.5) (5.7)

[53] rs3] T53] [53] T531 [53] T52] [52] [521

F 74.3 1.60 74.9 0.96 0.86 29.0 29.9 44.4 39.6

(2.9) (0.06) (13.6) (0.21) (0.17) (5.4) (8.6) (5.7) (5.2)

[54] [54] .511 [54] [54] [51] [52] [52] [52]

80- M 83.1 1.71 83.6 1.14 0.92 28.5 23.6 59.7 28.2

89.99 (2.5) (0.08) (11.8) (0.25) (0.10) (3.6) (4.8) (7.4) (3.5) ri4i ri4i ri4i T141 ri3i [141 ri3i ri3i ri3i

F 83.1 1.56 73.3 1.03 0.79 30.3 30.0 43.1 39.9

(2.5) (0.07) (15.3) (0.22) (0.13) (6.2) (9.7) (5.9) (6.2) ri8i ri8i ri8i [18] rπ] [18] N81 risi [18] TABLE 13 . Basic characteristics of 636 subj ects from 157 nuclear families .

Age Sex Ages Height Weight Spine Hip BMI Fat Lean PFM groups BMD BMD mass mass

(years) (years) (m) (kg) (g/m²) (g/m²) (kg/m²) (kg) (kg) (%)

19-30 M 23.4 1.79 83.0 1.06 1.12 25.9 18.0 63.1 21.0

(3.2) (0.05) (13.4) (0.12) (0.16) (4.1) (7.8) (7.6) (6-1)

[52] r52] T521 T521 [521 [521 T52] r521 T521

F 24.5 1.66 68.3 1.06 0.98 24.8 23.0 44.0 32.3

(3.8) (0.06) (17.6) (0.13) (0.12) (5.9) (12.0) (8.7) (7.6)

[75] [74] [74] [75] [74] [74] [73] [73] [73]

31-40 M 35.5 1.81 94.4 1.09 1.08 28.9 21.4 67.2 22.5

(3.0) (0.07) (20.8) (0.10) (0.12) (6.6) (10.2) (7.9) (6.9)

[22] [22] [221 T21] [21] [22] [21 } T2H [21]

F 35.8 1.66 69.3 1.03 0.93 25.1 24.2 43.2 33.6

(2.8) (0.06) (17.2) (0.12) (0.12) (5.9) (11.3) (7.0) (7.7)

[611 [611 [61] [61] [ 1] [61] [601 [601 [60]

41-50 M 46.3 1.80 90.5 1.10 1.06 28.1 23.2 65.1 25.0

(3.0) (0.06) (13.9) (0.19) (0.15) (4.2) (9.3) (7.5) (6.9)

[401 [401 T401 [391 [401 [40] [401 r401 T401

F 45.8 1.66 71.6 1.06 0.95 26.0 25.8 43.8 35.0

(2.8) (0.06) (15.7) (0.13) (0.14) (5.4) (9.8) (5.9) (6.5)

[98] [98] [98] [98] [98] [98] [98] [98] [98]

51-60 M 55.3 1.76 91.4 1.06 1.04 29.4 23.7 63.8 26.0

(2.8) (0.07) (16.9) (0.19) (0.16) (5.3) (7.2) (8.6) (4.7)

[54] T54] [541 T531 [53] [54] [52] T521 [521

F 54.7 1.63 73.8 0.99 0.90 27.7 28.7 43.4 38.0

(3.0) (0.06) (14.5) (0.14) (0.13) (5.0) (9.6) (6.3) (6.1)

[661 T661 [66] [66] [65] [66] [65] [65] [65]

61-70 M 64.9 1.77 92.1 1.05 1.02 ^' 29.3 25.9 62.2 27.9

(2.8) (0.05) (16.2) (0.18) (0.12) (4.5) (9.1) (6.7) (5.8)

[361 [361 T361 [351 T351 [361 T35] r351 [351

F 65.4 1.64 72.7 0.95 0.85 27.0 28.4 42.7 38.0

(2.9) (0.05) (16.2) (0.18) (0.13) (5.5) (10.7) (6-3) (7.0)

[46] [46] [46] [46] [46] [46] [46] [46] [46]

71-80 M 74.9 1.75 86.6 1.07 0.98 28.1 23.8 59.4 26.9

(2.7) (0.06) (15.7) (0.19) (0.16) (4.4) (7.3) (7.7) (4.2)

[30] T301 T301 [30] [301 [30] poi [30] [301

, F 75 (2.9) 1.61 67.6 0.91 0.77 26.1 26.3 39.8 38.3

[34] (0.07) (2-6) (0.19) (0.14) (4.5) (7.1) (5.8) (4.6)

[34] [34] [34] [34] [34] [34] [34] P4]

81-90 M 82.9 1.73 81.9 1.17 1.00 27.2 21.0 56.5 25.0

(2.2) (0.09) (17.4) (0.32) (0.17) (5.3) (9.5) (8.8) (7.8) ri2i ri2i [121 [121 ri2i ri2i n il mi [111

F 83.6 1.56 66.5 0.92 0.76 27.3 26.1 38.8 37.6

(2.0) (0.06) (16.0) (0.23) (0.22) (6.2) (11.4) (5.4) (9.4) rsi [81 rsi [8] m rsi [81 Ϊ81 [81

In Tables 12 and 13 , within each cell of the third to eleventh columns with three numbers , data are the mean, SD (the number within the parentheses) , and the sample size (the number within the brackets) . For each age strata, M and F indicate data from males and females, respectively. The statistics obtained from QTDT analysis of the IL-6 gene and BMD are set forth in Table 14, in which italicized numbers represent a p<0.10, * represents a p<0.05, and ** represents a p<0.01.

TABLE 14. χ² statistics obtained from QTDT analysis of the IL-6 gene and BMD.

IL-δ Multigenerational Nuclear Families

(bp) Pedigrees

Spine BMD Hip BMD Spine BMD Hip BMD

Tests of population stratification

116 1.41 0.56 - -

118 0.21 0.00 2.24 1.42

120 0.00 1.57 0.63 0.54

122 0.00 2 . 78 0.72 1.79

124 - - - -

126 0.13 0.30 0.04 1.98

128 0.18 1.66 - -

130 0.73 0.18 - -

132 - - - -

134 - -

Association tests

116 0.22 0.93 0.05 0.09

118 0.22 0.70 1.26 0.73

120 0.19 1.91 3 . 08 1.15

122 0.03 0.21 0.88 1.67

124 3 . 66 1.22 0.09 1.52

126 0.06 0.00 0.66 0.49

128 0.03 1.32 0.22 1.08

130 0.02 0.55 11.61** 3.9*

132 0.12 0.00 0.06 2 . 76

134 0.02 0.93

Linkage tests

3 . 30 1.58 1.08 0.18

Tests of association and linkage

116 2 . 92 1.47 - -

118 3 . 06 1.23 0.99 0.22

120 3 . 03 0.37 1.18 0.29

122 2 . 91 1.37 1.18 0.11

124 - - - -

126 2 . 91 1.25 0.92 0.15

128 2 . 91 1.08 - -

130 3 . 02 1.30 - -

132 - - - -

134 - - Briefly, for the multigenerational pedigrees, ten different alleles were found. Their sizes ranged from 116 to 134bp (9-18 CA repeats) . The 13 -repeat allele (124bp) is weakly associated with the spine BMD (p=0.055). The seventeen subjects who possessed this allele had higher BMD than those participants who did not carry an allele of that size. The CA repeat polymorphism of the IL-6 gene is also linked to spine BMD (p=0.069) . Moreover, we found marginally significant results for linkage and association between spine BMD and the CA repeat polymorphism of the IL-6 gene (p=-0.08) .

For the sample of nuclear families, the 11- repeat allele (120bp) and the 16-repeat allele (130bp) were associated with higher spine BMD (p=0.079 and 0.0007, respectively), while the 16-repeat allele (130bp) and the 17-repeat allele (132bp) were associated with higher hip BMD (p=0.048 and 0.097, respectively). The results are not significant for population stratification, linkage, and linkage and association.

The statistics obtained from QTDT analysis of the IL-6 gene and obesity-related phenotypes are set forth in Table 15, in which italicized numbers represent a p<0.10, * represents a p<0.05, and ** represents a p<0.,01. TABLE 15: χ² statistics obtained from QTDT analysis of the IL-6 gene and obesity-related phenotypes.

IL-6 Multigenerational Pedigrees Nuclear Families

(bp)

BMI Fat Mass Lean Mass PFM BMI Fat Mass Lean Mass PFM

Tests of population stratification

116 0.17 0.59 0 0.09 - - - -

118 0.03 2.77 0.96 0 0.41 0.5 0 0.03

120 1.64 9.78** 0.96 3.1 0 0 1.85 0.91

122 2.83 12.93** 2.12 3.38 1.01 3.45 0.48 1.81

124 - - - - - - - -

126 0.27 1.31 0.1 0.82 1.06 5.13* 5.71* 0.44

128 2.63 6.96** 0.52 3.82* - - - -

130 1.25 0.06 0.48 0.07 - - - -

132 - - - - - - - -

134 - - - -

Association tests

116 0.19 0.19 0 0.38 0.01 0.39 0.13 0.05

118 0.01 0.01 2.47 0.01 0.44 1.01 0 0.41

120 0.48 0.48 0 0.99 0.14 2.35 1.26 0.37

122 0.1 0.1 0.33 0.06 0.08 0 0.49 0.16

124 0.63 0.63 2.47 3.57 0.2 2.25 0.52 0.69

126 1.11 1.11 7 3** 0.36 0.07 2.42 0.96 1.65

128 1.07 1.07 1.65 2.5 0.39 1.33 3.26 0.01

130 0.67 0.67 1.73 0.06 0.43 0.18 0.09 0.3

132 2.7 2.7 3.14 3.21 5.6* 16.6** 11.24** 3.22

134 0.05 0.05 0 0.61

Linkage tests

0.34 1039** 522** 0.15 7.35** 642.3** 245** 3 **

Tests of association and linkage

116 0.43 826.4** 391.1** 0.19 - - - -

118 0.36 825.3** 390.4** 0.17 7.23** 634.8** 240.7** 7.31**

120 0.15 813** 388.2** 0.03 7.06** 633** 239.4** 6.72**

122 0.39 816.9** 388.6** 0.25 6.58** 631** 240.7** 6.73**

124 - - - - - - - -

126 0.26 816.5** 387.8** 0.09 7 _j7** 629.4** 236.4** 7.24**

128 0.22 810.2** 390.2** 0 - - - -

130 ^■ 0.25 824.2** 389.2** 0.16 - - - -

132 - - - - - - - -

134 - - - -

Briefly, for the sample of the 5 multigenerational pedigrees, tests for linkage, and both linkage and association consistently yielded highly significant results for fat mass and lean mass . When testing for association, the 14-repeat allele (126bp) and the 17-repeat allele (132bp) were associated with low lean mass (p=0.005 and 0.076, respectively) . The 589 subjects who possessed the 14-repeat allele had average lean mass of 53.25 kg, while the 541 subjects who did not carry the allele had average lean mass of 55.19 kg. The 13-repeat allele (124bp) and the 17-repeat allele (132bp) were weakly associated with PFM (p=0.059 and 0.073, respectively) . However, population stratification was detected for the 11, 12, and 17-repeat alleles (p=0.078, 0.066, 0.051, respectively).

Tests for linkage, and both linkage and association consistently yielded highly significant results for BMI, fat mass, lean mass, and PFM (p<0.01) in the sample of nuclear families. The 17-repeat allele (132bp) was consistently associated with higher BMI, higher fat mass, higher lean mass, and higher PFM. However, population stratification was detected for fat mass and lean mass for the 14-repeat allele (126bp) .

Example 6 -- Linkage and/or Association of Several Genomic Regions with Height

Subjects : The study subjects came from an expanding database being created for studies to search for genes underlying the risk to osteoporosis and obesity. Only healthy people (defined by the exclusion criteria detailed below) were included in the analysis. All the study subjects were Caucasians of European origin. 53 pedigrees with 671 subjects (259 males and 412 females) from 2-4 generations were analyzed. The pedigrees vary in size from 3 to 99 individuals, with a mean of 11.7 (±SE=2.4) . Each pedigree was identified through a proband having BMD Z-scores < -1.28 at the hip or spine. Hence, the probands were selected from the bottom 10 percent of the population BMD variation with the intended purpose of achieving higher statistical power than random sampling to identify QTLs for BMD. BMD values are expressed as Z-scores adjusted for age, gender, and ethnic difference in general healthy referent populations. In our sample, BMD and height are significantly correlated. The sex-adjusted correlation between height and BMD is, respectively, 0.120 (p<0.01) and 0.121 (p<0.01), at the spine and hip. Hence, the sampling scheme of our study pedigrees for enhancing the linkage power to detect genomic regions for BMD variation may also have similar effect (if any) on height. In fact, the probands tend to have lower than average height in the pedigrees (see Results) . The exclusion criteria for the study subjects were a history of (1) serious residuals from cerebral vascular disease; (2) diabetes mellitus, except for easily controlled, non-insulin dependent diabetes mellitus; (3) chronic renal disease manifest by serum creatinine >1.9 mg/dl; (4) chronic liver disease or alcoholism; (5) significant chronic lung disease; (6) corticosteroid therapy at pharmacologic levels for more than 6 months duration; (7) treatment with anticonvulsant therapy for more than 6 months duration; (8) evidence of other metabolic or inherited bone disease such as hyper- or hypoparathyroidism,

Paget ' s disease, osteomalacia, osteogenesis imperfecta, or others; (9) rheumatoid arthritis or collagen disease; (10) recent major gastrointestinal disease (within the past year) such as peptic ulcer, malabsorption, chronic ulcerative colitis, regional enteritis, or any significant chronic diarrhea state; (11) significant disease of any endocrine organ that would affect bone mass; (12) hyperthyroidism; (13) any neurologic or musculoskeletal condition that would be a non-genetic cause of low bone mass; and (14) any disease, treatment, or condition that would be a non-genetic cause for low bone mass. The exclusion criteria were assessed by nurse- administered questionnaires and/or medical records.

Genotyping: For each subject, blood (20cc) was drawn into lavender cap (EDTA containing) tubes by certified phlebotomists and stored chilled (~4°C) until DNA extraction that was normally completed within the next five calendar days. DNA was extracted by employing a kit (Gentra Systems, Inc; Puregene DNA Isolation Kit; Cat# D-5000; Minneapolis, MN) following the procedures detailed therein. DNA was genotyped using fluorescently labeled markers as described in Example 1 and elsewhere . ^C3S) The 400 dinucleotide markers we started our genotyping with are commercially available through Perkin Elmer Applied Biosystems (ABI PRISM Linkage Mapping Sets Version 2, Norwalk, CT) . The PCR was performed on PE 9700 thermocyclers (GENEAMP^® PCR System 9700, Applied Biosystems Foster City, CA, USA) . PCR cycling conditions followed those suggested in the ABI PRISM Linkage Mapping Sets Version 2. Genotyping was performed using Applied Biosystems automated DNA sequencing systems (Models 377 and 310; Perkin Elmer-ABI; Foster City, CA) running the GENESCAN™ and GENOTYPER™ softwares for allele identification and sizing. A genetic database management system, GenoDB^t20) , was employed to manage the phenotype and genotype data for linkage analyses. GenoDB was also employed for allele bining (including setting up allele bining criteria and converting allele sizes to distinct allele numbers) , data quality control, and data formatting for PedCheck⁽⁷⁾ and linkage analyses by SOLAR. PedCheck was employed for checking the confirmation to Mendelian inheritance pattern at all the marker loci and for confirming the alleged relationships of family members within pedigrees . ⁽²¹⁾ The genotyping error rate^(20~21), determined by three rounds of sample replication in experiments and data analyses by PedCheck, was about 0.3%. 380 markers (including 362 on autosomes) were successfully genotyped. These markers have an average population heterozygosity of -0.79 and spaced on average ~8.6cM between adjacent markers throughout the human genome .

Statistical Analyses: The variance component linkage analysis'^10"12' for quantitative traits was performed. The analysis is based on specifying the expected genetic covariances between arbitrary relatives as a function of the identity by descent at a given marker locus. The analysis considers the phenotypic and genetic information from all pedigree members simultaneously. The analysis assumed joint multivariate normality of phenotypic values, additive genetic effects, and no interaction between genes and the residual. The program employed was SOLAR. ⁽¹²⁾ The ascertainment scheme of pedigrees based on the low BMD values of probands leads to lower than average height (see Results) . The ascertainment scheme was accounted for in the analyses by identifying to the program the probands and their phenotypic values for each pedigree. The built-in modules of the SOLAR program will then be able to account for the ascertainment scheme by using conditional likelihoods in LOD score computation. The statistical properties of the variance component analyses after the ascertainment correction have been preliminarily investigated. ⁽²⁹"³¹> In linkage analysis, age and sex were adjusted as covariates to adjust for height, as these generally affect human height variation significantly in our study population. Analyses were also performed without adjusting for one or both of these covariates.

Adjustment for significant covariates in genetic analyses can generally increase the genetic signal to noise ratio in linkage detection by decreasing the proportion of the residual phenotypic variation attributable to random environmental factors. This may thus improve statistical power in our linkage analyses. Comparison of the analyses with and without adjustment for a significant covariate may shed light on the genomic regions identified as to their direct importance for the trait per se or indirect importance via the influence on the covariate only. The height data were tested by graphical methods'¹⁶' and found not to deviate from normal distributions. The variance component analyses implemented in SOLAR are generally robust to reasonable violations of normality of the data⁽²⁶⁾ , although some types of nonnormality of the data may inflate the type one error rate in excess of specified nominal levels. ^(32> Marker allele frequencies were obtained by maximum likelihood estimation in SOLAR. Hypothesis testing for linkage was conducted by the maximum likelihood method by investigating the relationship of genetic covariances and the identical by descent between arbitrary relatives. The method compares the maximum likelihoods obtained in the full model (with linkage so that the locus is a QTL and accounts for some additive genetic variance) and the nested null model (without linkage and the locus is not a QTL) . The difference between the two log₁₀ likelihoods yields a LOD score. Twice the difference of the log_e of the likelihoods of these two models is asymptotically distributed as a 1/2:1/2 mixture of a χ² variable and a point mass at zero'¹²¹ with 1 degree of freedom. Using SOLAR, two-point and multi-point linkage analyses were performed, respectively, for height. LOD scores may be converted to approximate p-values commonly employed in statistical testing through a χ²-distribution. ^<17) When a putative QTL is suggested, the proportion of phenotypic variation attributable to this QTL can be estimated by SOLAR. The total heritability of height may also be estimated by SOLAR.

Results : The basic characteristics of the study subjects stratified by age and sex are summarized in Table 16. Some information about the family structure of the study pedigrees is summarized in Table 2 (see Example 1) .

TABLE 16. Basic characteristics of the study subjects for height stratified by sex and age of each decade.

Age groups Sex Mean height Standard Sample (years) (m) deviation size

20-29 M 1.83 0.070 23 F 1.66 0.055 40

30-39 M 1.80 0.092 72

F 1.66 0.076 102

40-49 M 1.78 0.069 65 F 1.64 0.067 112

50-59 M 1.78 0.074 34 F 1.63 0.050 55

60-69 M 1.76 0.083 35 F 1.62 0.060 59

70+ M 1.72 0.067 30 F 1.57 0.072 44

It can be seen from Table 2 that the study included about 1,380 parent offspring pairs, 1,249 sibling pairs, 1,098 grandparent-grandchild pairs, 1,993 avuncular pairs, and 2,589 first cousin pairs, etc., reflecting the richness of the genetic information for linkage analyses in our sample. Although the parent- offspring pairs may not be informative in testing linkage at a putative QTL (because the IBD shared by parent- offspring pairs is invariably one) , the phenotype information between parent-offspring pairs contributes to estimation of the polygenic effects in linkage analysis. Hence, the number of the parent-offspring pairs is relevant. In addition, the number of the parent- offspring pairs also bears some information on the structure of the pedigrees .

With regard to Table 16, the total sample size summarized is 671 and more than the 630 subjects genotyped. This is because, forty-one of these subjects cannot be amplified for the markers (probably due to poor quality or degradation of the DNA extracted) employed or do not have DNA in our archive but only the phenotype data. However, since the genotypes of these 41 subjects can often be unambiguously inferred from their relatives, their phenotype data are still useful in linkage analyses, and therefore are also included in the above table. Hence, the sample size 630 represents the genotyped individuals and the total sample size of 671 represents those whose genotypes are either genotyped or inferred for linkage analyses. (For example, if in a family, at one locus, the father is of the genotype A1A1 and the mother's genotype is not typed, but the genotypes of their three children are respectively, A1A2 , A1A3 , A1A2 , the mother's genotype can be inferred unambiguously as A2A3) .

The sex-adjusted correlations of height with spine and hip BMD are, respectively, 0.120 and 0.121, both significant at p<0.01. The mean (SE) of height adjusted for age and sex for all the subjects including probands in our sample is 1.692m (0.003) . The values of height are significantly smaller (p<0.01) in the probands (mean 1.612m, SD 0.008) reflecting our sampling scheme through low BMD values which translates into significantly low height values in the probands. The heritability of height in our pedigrees is 0.73 (SE=0.06), indicating that about 73 percent of height variation in the sampled pedigrees is attributable to genetic factors.

The results for the chromosomes that had maximum LOD scores greater than 1.5 in multi-point linkage analyses are summarized in Figure 7, and the results for the other chromosomes were summarized in Figure 8. Since the current version of SOLAR does not handle multi-point linkage analyses for X chromosome, to convey the linkage signal pattern on X chromosome, we plotted two-point LOD score results for the X chromosome and presented it in Figure 7. For the analysis results presented, height was adjusted with multiple regression for significant covariates of age and sex. The results (not presented) of the linkage analyses for height not adjusted for covariates showed similar pattern in LOD scores and essentially the same outcome, suggesting that the influences (if indeed exist) of the genomic regions identified here act on height directly rather than via the covariates. Markers and genomic regions with LOD scores greater than 1.5 in two- or multi-point analyses are summarized in Table 17. TABLE 17. Markers and genomic regions of LOD scores greater than 1.5 in two or multi-point linkage analyses for height variation and the identified candidate genes inside or near the genomic regions.

Two-point analyses

Multi-point analyses

It can be seen that a few genomic regions identified with LOD scores greater than or near 2.0 may harbor QTLs for height variation (Figure 7 and Table 17) . These regions include 5q31 at 144cM from pter on chromosome 5 with a maximum LOD score ("MLS") of 2.14 (p=0.00085) in multipoint linkage analyses, as well as Xp22 at marker DXS1060 and Xq25 at marker DXS1001 on X chromosome, and 8p22 at D8S550 on chromosome 8, with LOD scores of 1.95 (p=0.0014), 1.91 (p=0.0015) and 1.93 (p=0.0014), respectively, in two-point linkage analyses. Meanwhile some genomic regions with LOD scores greater than 1.50 in either multi- or two-point linkage analyses (Figures 7 and 8, Table 17) are also noticeable. The genetic signals manifested in these genomic regions deserve further investigation on extended samples and/or with denser molecular markers . These regions include

17q25 at 114cM from pter with a MLS of 1.50 (p=0.0043) in multipoint linkage analyses and with a LOD score of 1.67 (p=0.0028) at 106.9cM from pter in two-point analyses, as well as 5ql4 at D5S2115 and 4pl5 at D4S391, with LOD scores of 1.89 (p=0.0016) and 1.58 (p=0.0035), respectively, in two-point analyses. For the putative QTL with the strongest evidence of linkage to 5q31, it was estimated that -32% of height variation (after adjusting for age and sex) may be attributable to this locus, which is likely an estimate of the upper bound of the genetic effects due to the locus. ^(27>

Since the pedigree size varies dramatically from 3 to 99, we performed additional linkage analyses for the largest pedigree and for the rest of the pedigrees. We found that the evidence from the two independent sub-samples generally provided support for each other for the major significant results presented for the combined sample, although the significance is weaker in the sub-samples.

REFERENCES

1. Audi et al . , "Genetic Determinants of Bone Mass," Horm. Res. , 51:105-23 (1999). 2. Dohi et al . , "A Novel Polymorphism in the

Promoter Region for the Human Osteocalcin Gene: The Possibility of a Correlation with Bone Mineral Density in Postmenopausal Japanese Women, " J. Bone Miner. Res., 13:1633-1639 (1998) . 3. Mullersman et al . , "Characterization of Two

Novel Polymorphisms at the Human Parathyroid Hormone Gene Locus," Hum. Genet . , 88:589-592 (1992).

4. Tokita et al . , "Vitamin D Receptor Alleles, Bone Mineral Density and Turnover in Premenopausal Japanese Women," J. Bone Miner. Res ■ , 11:1003-1009 (1996) .

5. Uitterlinden et al . , "A Large-Scale Population-Based Study of the Association of Vitamin D Receptor Gene Polymorphisms with Bone Mineral Density, " J. Bone Miner. Res. , 11:1241-1248 (1996).

6. Harris et al . , "The Vitamin D Receptor Start Codon Polymorphism (Fok I) and Bone Mineral Density in Premenopausal American Black and White Women, " J . Bone Miner. Res. , 12:1043-1048 (1997). _ 7. O'Connell et al . , "PedCheck: A Program for Identification of Genotype Incompatibilities in Linkage Analysis," Am. J. Hum. Genet. , 63:259-266 (1998).

8. Abecasis et al . , "A General Test of Association for Quantitative Traits in Nuclear Families," Am. J. Hum. Genet. , 66:279-292 (2000).

9. Abecasis et al . , "Pedigree Tests of Transmission Disequilibirum, " European J. Hum. Genet.. 8:545-551 (2000) . 10. Amos, "Robust Variance-Components Approach for Assessing Genetic Linkage in Pedigrees," Am. J . Hum. Genet . , 54:535-543 (1994).

11. Amos et al . , "Assessing Genetic Linkage and Association with Robust Components of Variance

Approaches," Ann. Hum. Genet. , 60:143-160 (1996).

12. Almasy et al . , "Multipoint Quantitative- Trait Linkage Analysis in General Pedigrees," Am. J . Hum. Genet . , 62:1198-1211 (1998). 13. Sowers et al . , "Familiality and

Partitionaing the Variability of Femoral Bone Mineral Density in Woman of Child-Bearing Age," Calcif. Tissue Int. , 50:110-114 (1992) .

14. Gueguen et al . , "Segregation Analysis and Variance Components Analysis of Bone Mineral Density in

Health Families," J. Bone Miner. Res., 10:2017-2022 (1995) .

15. Deng et al . , "Genetic Determination of Peak Bone Mass (PBM) at Hip and Spine and Common Familiar Environmental Effects on Bone Qualities," J. Clinical Densitometrv. 2:251-263 (1999).

,16. Sokal et al . , Biometry, 3rd ed. , New York: W. H. Freeman and Company (1995) .

17. Lander et al, "Genetic Dissection of Complex Traits: Guidelines for Interpretating the

Reporting Results," Nature Genetics, 11:241-247 (1995).

18. Deng et al . , "Product Difference of Multiplex and Singleplex PCR and Its Practical Implications for Human Genetic Studies," BioTechniques . 29:298-308 (2000) .

19. Deng et al . , "A Genome Wide Linkage Scan for QTLs for Obesity Phenotypes," Am. J. Hum, Genet.. 70:1138-1151 (2002) . 20. Li et al . , "Towards High-Throughput Genotyping: A Dynamic and Automatic Software for Manipulating Large-Scale Genotype Data Using Fluorescently Labeled Dinucleotide Markers," Genome Res . , 11:1304-1314 (2001) .

21. Huang et al . , "Mutation Patterns at Dinucleotide Microsatellite Loci in Humans, " Am. J. Hum. Genet .. 70:625-634 (2002).

22. Glύer et al . , "Accurate Assessment of Precision Errors: How to Measure the Reproducibility of Bone Densitometry Techniques," Osteoporosis International, 5:262-270 (1995).

23. Deng et al . , "Evidence of a Major Gene for Bone Mineral Density/Content in Human Pedigrees Identified via Probands with Extreme Bone Mineral Density," Ann. Hum. Genet. , 66:61-74 (2002).

24. Krall et al . , "Heritability and Life-Style Determinants of Bone Mineral Density, " J. Bone Miner. Res. , 8:1-9 (1993) . 25. Deng et al . , "Association of VDR and ER

Genotypes with Bone Mass in Postmenopausal Women: Different Conclusions with Different Analyses," Osteoporosis International, 9:499-507 (1999) .

26. Williams et al . , "Joint Multipoint Linkage Analysis of Multivariate Qualitative and Quantitative

Traits. I. Likelihood Formulation and Simulation Results," Am. J. Hum. Genet. , 65:1134-1147 (1999)

27. Goring et al . , "Large Upward Bias in Estimation of Locus-Specific Effects from Genomewide Scans," Am. J. Hum. Genet.. 69:1357-1369 (2001).

28. Heaney et al . , "Bone Dimensional Change with Age: Interactions of Genetic, Hormonal, and Body- Size Variables," Osteoporosis International, 7:426-431 (1997) .

29. de-Andrade et al . , "Assessing Linkage on Chromosome 5 Using Components of Variance Approach: Univariate Versus Multivariate," Genetic Epidemiology, 14:773-778 (1997) .

30. de-Andrade et al . , "Ascertainment Issues in Variance Components Models," Genetic Epidemiology, 19:333-434 (2000) . 31. Sham et al . , "Variance-Components QTL

Linkage Analysis of Selected and Non-normal Samples: Conditioning on Trait Values," Genetic Epidemiology, 19(Suppl. 1) :S22-S28 (2000).

32. Allison et al . , "Testing the Robustness of the Likelihood-ratio Test in a Variance-Component

Quantitative-Trait Loci Mapping Procedure, " Am. J. Hum. Genet . , 65:531-544 (1999).

33. Deng et al . , "A Genomewide Linkage Scan for Quantitative Trait Loci for Obesity Phenotypes," Am. J. Hum. Genet. , 70:1138-1151 (2002).

34. Rabinowitz, "A Transmission Disequilibrium Test for Quantitative Trait Loci," Hum. Hered. , 47:342- 350 (1997) .

35. Deng et al . , "Characterization of Genetic and Life-Style Factors for Determining Variation of BMI,

Fat Mass, Percentage Fat Mass, and Lean Mass," J. Clinical Densitometry, 4:353-362 (2001).

36. Deng et al . , "Is Population Bone Mineral Density Variation Linked to ^"the Marker D11S987 on Chromosome llql2-13?" Journal of Clinical Endocrinology and Metabolism, 86 (8) : 3735-3741 (2001). Although the invention has been described in detail for the purpose of illustration, it is understood that such detail is solely for that purpose, and variations can be made therein by those skilled in the art without departing from the spirit and scope of the invention which is defined by the following claims .

Claims

WHAT IS CLAIMED IS:

1. A method for detecting the presence in a subject of a polymorphism linked to a gene associated with one or more bone properties, said method comprising: analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with one or more bone properties, wherein the presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant bone properties and wherein the particular region is selected from the group consisting of: a VDR gene of the subject's genome; a BGP gene of the subject's genome; an IL-6 gene of the subject's genome; between about 120 cM and about 180 cM from pter on chromosome 4 of the subject's genome; between about 0 cM and about 20 cM from pter on chromosome 7 of the subject's genome; between about 120 cM and about 175 cM from pter on chromosome 12 of the subject's genome; between about 80 cM and about 115 cM from pter on chromosome 13 of the subject's genome; between about 140 cM and about 172 cM from pter on chromosome 10 of the subject's genome; between about 60 cM and about 90 cM from pter on chromosome 12 of the subject's genome; between about 30 cM and about 80 cM from pter on chromosome 17 of the subject's genome; between about 0 cM and about 20 cM from pter on chromosome 3 of the subject's genome; between about 0 cM and about 60 cM from pter on chromosome 9 of the subject's genome; between about 0 cM and about 52 cM from pter on chromosome 17 of the subject's genome; between about 5 cM and about 55 cM from pter on chromosome 2 of the subject's genome; between about 10 cM and about 55 cM from pter on chromosome 19 of the subject's genome; between about 0 cM and about 40 cM from pter on chromosome 14 of the subject's genome; between about 30 cM and about 100 cM from pter on chromosome 17 of the subject's genome; between about 0 cM and about 40 cM from pter on chromosome 4 of the subject's genome; between about 240 cM and about 265 cM from pter on chromosome 2 of the subject's genome; and between about 40 cM and about 85 cM from pter on chromosome 9 of the subject's genome.

2. A method according to claim 1, wherein the one or more bone properties are selected from the group consisting of spine bone mineral density, hip bone mineral density, wrist bone mineral density, spine bone size, hip bone size, and wrist bone size.

3. A method according to claim 1, wherein the one or more bone properties is spine bone mineral density and wherein said method comprises : analyzing chromosome 12 of the subject and detecting the presence of a polymorphism located in or near the VDR gene linked to the gene associated with spine bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone mineral density.

4. A method according to claim 3, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective'presence or absence of the gene associated with spine bone mineral density by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

5. A method according to claim 1, wherein the one or more bone properties is spine bone mineral density and wherein said method comprises: analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with spine bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone mineral density.

6. A method according to claim 5, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with spine bone mineral density by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

7. A method according to claim 1, wherein the one or more bone properties is spine bone mineral density and wherein said method comprises : analyzing chromosome 4 of the subject and detecting the presence of a polymorphism located between about 120 cM and about 180 cM from pter and linked to the gene associated with spine bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone mineral density.

8. A method according to claim 7, wherein the polymorphism is located between 157 cM and 159 cM from pter.

. ■ 9. A method according to claim 1, wherein the one or more bone properties is spine bone mineral density and wherein said method comprises : analyzing chromosome 12 of the subject and detecting the presence of a polymorphism located between about 120 cM and about 175 cM from pter and linked to the gene associated with spine bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone mineral density.

10. A method according to claim 9, wherein the polymorphism is located between 167 cM and 170 cM from pter.

11. A method according to claim 1, wherein the one or more bone properties is spine bone mineral density and wherein said method comprises: analyzing chromosome 13 of the subject and detecting the presence of a polymorphism located between about 80 cM and about 115 cM from pter and linked to the gene associated with spine bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone mineral density.

12. A method according to claim 11, wherein the polymorphism is located between 112 cM and 113 cM from pter.

13. A method according to claim 11, wherein the polymorphism is located between 102 cM and 104 cM from pter.

14. A method according to claim 1, wherein the one or more bone properties is spine bone mineral density and wherein said method comprises: analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 20 cM from pter and linked to the gene associated with spine bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone mineral density.

15. A method according to claim 14, wherein the polymorphism is located between 7 cM and 8 cM from pter.

16. A method according to claim 1, wherein the one or more bone properties is hip bone mineral density and wherein said method comprises : analyzing chromosome 1 of the subject and detecting the presence of a polymorphism located in or near the BGP gene linked to the gene associated with hip bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone mineral density.

17. A method according to claim 16, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with hip bone mineral density by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

18. A method according to claim 1, wherein the one or more bone properties is hip bone mineral density and wherein said method comprises : analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with hip bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone mineral density.

19. A method according to claim 18, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with hip bone mineral density by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

20. A method according to claim 1, wherein the one or more bone properties is hip bone mineral density and .wherein said method comprises: analyzing chromosome 10 of the subject and detecting the presence of a polymorphism located between about 140 cM and about 172 cM from pter and linked to the gene associated with hip bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone mineral density.

21. A method according to claim 20, wherein the polymorphism is located between 178 cM and 179 cM from pter.

22. A method according to claim 1, wherein the one or more bone properties is hip bone mineral density and wherein said method comprises: analyzing chromosome 12 of the subject and detecting the presence of a polymorphism located between about 60 cM and about 90 cM from pter and linked to the gene associated with hip bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone mineral density.

23. A method according to claim 22, wherein the polymorphism is located between 69 cM and 70 cM from pter.

24. A method according to claim 1, wherein the one or more bone properties is hip bone mineral density and wherein said method comprises: analyzing chromosome 17 of the subject and detecting the presence of a polymorphism located between about 30 cM and about 80 cM from pter and linked to the gene associated with hip bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone mineral density.

25. A method according to claim 24, wherein the polymorphism is located between 43 cM and 45 cM from pter. - I l l -

26. A method according to claim 1, wherein the one or more bone properties is wrist bone mineral density and wherein said method comprises : analyzing chromosome 4 of the subject and detecting the presence of a polymorphism located between about 120 cM and about 180 cM from pter and linked to the gene associated with wrist bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone mineral density.

27. A method according to claim 26, wherein the polymorphism is located between 157 cM and 159 cM from pter.

28. A method according to claim 1, wherein the one or more bone properties is wrist bone mineral density and wherein said method comprises : analyzing chromosome 3 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 20 cM from pter and linked to the gene associated with wrist bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone mineral density.

29. A method according to claim 28, wherein the polymorphism is located between 2 cM and 3 cM from pter.

30. A method according to claim 1, wherein the one or more bone properties is wrist bone mineral density and wherein said method comprises : analyzing chromosome 9 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 60 cM from pter and linked to the gene associated with wrist bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone mineral density.

31. A method according to claim 30, wherein the polymorphism is located between 27 cM and 28 cM from pter.

32. A method according to claim 30, wherein the polymorphism is located between 15 cM and 17 cM from pter.

33. A method according to claim 1, wherein the one or more bone properties is wrist bone mineral density and wherein said method comprises : analyzing chromosome 17 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 52 cM from pter and linked to the gene associated with wrist bone mineral density, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone mineral density.

34. A method according to claim 33, wherein the polymorphism is located between 23 cM and 24 cM from pter.

35. A method according to claim 1, wherein the one or more bone properties is spine bone size and wherein said method comprises : analyzing chromosome 2 of the subject and detecting the presence of a polymorphism located between about 5 cM and about 55 cM from pter and linked to the gene associated with spine bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant spine bone size.

36. A method according to claim 35, wherein the polymorphism is located between 30 cM and 32 cM from pter.

37. A method according to claim 35, wherein the polymorphism is located between 38 cM and 40 cM from pter.

38. A method according to claim 1, wherein the one or more bone properties is hip bone size and wherein said method comprises : analyzing chromosome 19 of the subject and detecting the presence of a polymorphism located between about 10 cM and about 55 cM from pter and linked to the gene associated with hip bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone size.

39. A method according to claim 38, wherein the polymorphism is located between 37 cM and 39 cM from pter.

40. A method according to claim 38, wherein the polymorphism is located between 41 cM and 43 cM from pter.

41. A method according to claim 1, wherein the one or more bone properties is hip bone size and wherein said method comprises : analyzing chromosome 14 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 40 cM from pter and linked to the gene associated with hip bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant hip bone size.

42. A method according to claim 41, wherein the polymorphism is located between 15 cM and 17 cM from pter.

43. A method according to claim 1, wherein the one or more bone properties is wrist bone size and wherein said method comprises: analyzing chromosome 17 of the subject and detecting the presence of a polymorphism located between about 30 cM and about 100 cM from pter and linked to the gene associated with wrist bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone size.

44. A method according to claim 43, wherein the polymorphism is located between 74 cM and 76 cM from pter.

45. A method according to claim 43, wherein the polymorphism is located between 76 cM and 78 cM from pter.

46. A method according to claim 1, wherein the one or more bone properties is wrist bone size and wherein said method comprises : analyzing chromosome 4 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 40 cM from pter and linked to the gene associated with wrist bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone size.

47. A method according to claim 46, wherein the polymorphism is located between 4 cM and 5 cM from pter.

48. A method according to claim 1, wherein the one or more bone properties is wrist bone size and wherein said method comprises : analyzing chromosome 2 of the subject and detecting the presence of a polymorphism located between about 240 cM and about 265 cM from pter and linked to the gene associated with wrist bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone size.

49. A method according to claim 48, wherein the polymorphism is located between 259 cM and 261 cM from pter.

50. A method according to claim 48, wherein the polymorphism is located between 262 cM and 264 cM from pter.

51. A method according to claim 1, wherein the one or more bone properties is wrist bone size and wherein said method comprises: analyzing chromosome 9 of the subj ect and detecting the presence of a polymorphism located between about 40 cM and about 85 cM from pter and linked to the gene associated with wrist bone size, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant wrist bone size.

52. A method according to claim 51, wherein the polymorphism is located between 62 cM and 64 cM from pter.

53. A method according to claim 51, wherein the polymorphism is located between 69 cM and 71 cM from pter.

54. A method for detecting the presence in a subject of a polymorphism linked to a gene associated with one or more body mass properties, said method comprising: analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with one or more body mass properties, wherein the presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant body mass properties and wherein the particular region is selected from the group consisting of: an IL-6 gene of the subject's genome; between about 0 cM and about 25 cM from pter on chromosome 1 of the subject's genome ,- between about 80 cM and about 170 cM from pter on chromosome 2 of the subject's genome; between about 40 cM and about 100 cM from pter on chromosome 4 of the subject ' s genome; between about 150 cM and about 192 cM from pter on chromosome 6 of the subject's genome; between about 230 cM and about 250 cM from pter on chromosome 2 of the subject's genome; between about 140 cM and about 150 cM from pter on chromosome 8 of the subject's genome; between about 160 cM and about 192 cM from pter on chromosome 6 of the subject's genome; between about 0 cM and about 60 cM from pter on chromosome 8 of the subject's genome; between about 50 cM and about 100 cM from pter on chromosome 20 of the subject's genome; between about 55 cM and about 100 cM from pter on chromosome 12 of the subject's genome; ^' between about 30 cM and about 100 cM from pter on chromosome 5 of the subject's genome; between about 10 cM and about 60 cM from pter on chromosome 17 of the subject's genome; and between about 0 cM^" and about 20 cM from pter on chromosome 7 of the subject's genome.

55. A method according to claim 54, wherein the one or more body mass properties are selected from the group consisting of body mass index, percentage fat mass, fat mass, and lean mass.

56. A method according to claim 54, wherein the one or more body mass properties is body mass index and wherein said method comprises : analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with body mass index, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant body mass index.

57. A method according to claim 56, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with body mass index by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

58. A method according to claim 54, wherein the one or more body mass properties is body mass index and wherein said method comprises : analyzing chromosome 1 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 25 cM from pter and linked to the gene associated with body mass index, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant body mass index.

59. A method according to claim 58, wherein the polymorphism is located between 4 cM and 5 cM from pter.

60. A method according to claim 54, wherein the one or more body mass properties is body mass index and wherein said method comprises : analyzing chromosome 2 of the subject and detecting the presence of a polymorphism located between about 90 cM and about 170 cM from pter and linked to the gene associated with body mass index, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant body mass index.

61. A method according to claim 60, wherein the polymorphism is located between 122 cM and 124 cM from pter.

62. A method according to claim 60, wherein the polymorphism is located between 127 cM and 129 cM from pter.

63. A method according to claim 60, wherein the polymorphism is located between 131 cM and 132 cM from pter.

64. A method according to claim 54, wherein the one or more body mass properties is body mass index and wherein said method comprises : analyzing chromosome 4 of the subject and detecting the presence of a polymorphism located between about 40 cM and about 100 cM from pter and linked to the gene associated with body mass index, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant body mass index.

65. A method according to claim 64, wherein the polymorphism is located between 67 cM and 69 cM from pter.

66. A method according to claim 64, wherein the polymorphism is located between 69 cM and 70 cM from pter.

67. A method according to claim 54, wherein the one or more body mass properties is body mass index and wherein said method comprises : analyzing chromosome 6 of the subject and detecting the presence of a polymorphism located between about 150 cM and about 192 cM from pter and linked to the gene associated with body mass index, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant body mass index.

68. A method according to claim 67, wherein the polymorphism is located between 187 cM and 189 cM from pter.

69. A method according to claim 67, wherein the polymorphism is located between 190 cM and 191 cM from pter.

70. A method according to claim 54, wherein the one or more body mass properties is percentage fat mass and wherein said method comprises : analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with percentage fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant percentage fat mass.

71. A method according to claim 70, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with percentage fat mass by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

72. A method according to claim 54, wherein the one or more body mass properties is percentage fat mass and wherein said method comprises : analyzing chromosome 2 of the subject and detecting the presence of a polymorphism located between about 230 cM and about 250 cM from pter and linked to the gene associated with percentage fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant percentage fat mass.

73. A method according to claim 72, wherein the polymorphism is located between 240. cM and 241 cM from pter.

74. A method according to claim 54, wherein the one or more body mass properties is percentage fat mass and wherein said method comprises: analyzing chromosome 2 of the subject and detecting the presence of a polymorphism located between about 80 cM and about 150 cM from pter and linked to the gene associated with percentage fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant percentage fat mass.

75. A method according to claim 74, wherein the polymorphism is located between 127 cM and 129 cM from pter.

76. A method according to claim 74, wherein the 'polymorphism is located between 131 cM and 132 cM from pter.

77. A method according to claim 54, wherein the one or more body mass properties is percentage fat mass and wherein said method comprises : analyzing chromosome 8 of the subject and detecting the presence of a polymorphism located between about 140 cM and about 150 cM from pter and linked to the gene associated with percentage fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant percentage fat mass.

78. A method according to claim 77, wherein the polymorphism is located between 148 cM and 150 cM from pter.

79. A method according to claim 54, wherein the one or more body mass properties is fat mass and wherein said method comprises : analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant fat mass.

80. A method according to claim 79, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with fat mass by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

81. A method according to claim 54, wherein the one or more body mass properties is fat mass and wherein said method comprises: analyzing chromosome 2 of the subject and detecting the presence of a polymorphism located between about 80 cM and about 150 cM from pter and linked to the gene associated with fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant fat mass.

82. A method according to claim 81, wherein the polymorphism is located between 127 cM and 129 cM from pter.

83. A method according to claim 81, wherein the polymorphism is located between 131 cM and 132 cM from pter.

84. A method according to claim 54, wherein the one or more body mass properties is fat mass and wherein said method comprises : analyzing chromosome 6 of the subject and detecting the presence of a polymorphism located between about 160 cM and about 192 cM from pter and linked to the gene associated with fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant fat mass.

85. A method according to claim 84, wherein the polymorphism is located between 187 cM and 189 cM from pter.

86. A method according to claim 84, wherein the polymorphism is located between 190 cM and 191 cM from pter.

87. A method according to claim 54, wherein the one or more body mass properties is fat mass and wherein said method comprises: analyzing chromosome 8 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 60 cM from pter and linked to the gene associated with fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant fat mass.

88. A method according to claim 87, wherein the polymorphism is located between 31 cM and 32 cM from pter.

89. A method according to claim 54, wherein the one or more body mass properties is fat mass and wherein said method comprises : analyzing chromosome 20 of the subject and detecting the presence of a polymorphism located between about 50 cM and about 100 cM from pter and linked to the gene associated with fat mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant fat mass.

90. A method according to claim 89, wherein the polymorphism is located between 68 cM and 70 cM from pter.

91. A method according to claim 54, wherein the one or more body mass properties is lean mass and wherein said method comprises : analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located in or near the IL-6 gene linked to the gene associated with lean mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant lean mass .

92. A method according to claim 91, wherein said analyzing is carried out by: amplifying the polymorphism; separating the amplified polymorphism to generate a polymorphism pattern; and correlating the presence or absence of the polymorphism with the respective presence or absence of the gene associated with lean mass by comparing a corresponding polymorphism pattern for family members showing segregation between the gene and the polymorphism.

93. A method according to claim 54, wherein the one or more body mass properties is lean mass and wherein said method comprises: analyzing chromosome 12 of the subject and detecting the presence of a polymorphism located between about 55 cM and about 100 cM from pter and linked to the gene associated with lean mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant lean mass.

94. A method according to claim 93, wherein the polymorphism is located between 75 cM and 76 cM from pter.

95. A method according to claim 93, wherein the polymorphism is located between 81 cM and 83 cM from pter.

96. A method according to claim 54, wherein the one or more body mass properties is lean mass and wherein said method comprises: analyzing chromosome 5 of the subject and detecting the presence of a polymorphism located between about 30 cM and about 100 cM from pter and linked to the gene associated with lean mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant lean mass.

97. A method according to claim 96, wherein the polymorphism is located between 64 cM and 65 cM from pter.

98. A method according to claim 54, wherein the one or more body mass properties is lean mass and wherein said method comprises: analyzing chromosome 17 of the subject and detecting the presence of a polymorphism located between about 10 cM and about 60 cM from pter and linked to the gene associated with lean mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant lean mass .

99. A method according to claim 98, wherein the polymorphism is located between 32 cM and 34 cM from pter.

100. A method according to claim 54, wherein the one or more body mass properties is lean mass and wherein said method comprises : analyzing chromosome 7 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 20 cM from pter and linked to the gene associated with lean mass, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant lean mass .

101. A method according to claim 100, wherein the polymorphism is located between 4 cM and 6 cM from pter.

102. A method for detecting the presence in a subject of a polymorphism linked to a gene associated with height, said method comprising: analyzing at least a portion of the subject's genome and detecting the presence of a polymorphism which is located in or near a particular region of the subject's genome and which is linked to the gene associated with height, wherein the presence of the polymorphism is indicative of the subject having or being susceptible to having aberrant height and wherein the particular region is selected from the group consisting of: between about 10 cM and about 70 cM from pter on chromosome 4 of the subject's genome; between about 70 cM and about 200 cM from pter on chromosome 5 of the subject's genome; between about 0 cM and about 45 cM from pter on chromosome 8 of the subject's genome; between about 60 cM and about 135 cM from pter on chromosome 17 of the subject's genome; between about 100 cM and about 150 cM from pter on chromosome X of the subject's genome; and between about 0 cM and about 35 cM from pter on chromosome X of the subject's genome.

103. A method according to claim 102, wherein said method comprises : analyzing chromosome 4 of the subject and detecting the presence of a polymorphism located between about 10 cM and about 70 cM from pter and linked to the gene associated with height, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant height .

104. A method according to claim 103, wherein the polymorphism is located between 43 cM and 44 cM from pter.

^' 105. A method according to claim 102, wherein said method comprises: analyzing chromosome 5 of the subject and detecting the presence of a polymorphism located between about 70 cM and about 200 cM from pter and linked to the gene associated with height, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant height .

106. A method according to claim 105, wherein the polymorphism is located between 138 cM and 139 cM from pter.

107. A method according to claim 102, wherein said method comprises : analyzing chromosome 8 of the subject and detecting the presence of a polymorphism located between about 0 cM and about 45 cM from pter and linked to the gene associated with height, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant height.

108. A method according to claim 107, wherein the polymorphism is located between 20 cM and 21 cM from pter.

109. A method according to claim 102, wherein said method comprises : analyzing chromosome 17 of the subject and detecting the presence of a polymorphism located between about 60 cM and about 135 cM from pter and linked to the gene associated with height, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant height.

110. A method according to claim 109, wherein the polymorphism is located between 106 cM and 107 cM from pter.

111 . A method according to claim 102 , wherein said method comprises : analyzing chromosome X of the subject and detecting the presence of a polymorphism located between about 100 cM and about 150 cM from pter and linked to the gene associated with height, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant height.

112. A method according to claim 111, wherein the polymorphism is located between 139 cM and 140 cM from pter.

113. A method according to claim 102, wherein said method comprises: analyzing chromosome X of the subject and detecting the presence of a polymorphism located between about 0 cM and about 35 cM from pter and linked to the gene associated with height, wherein the presence of the polymorphism is indicative of a subject having or being susceptible to having aberrant height.

114. A method according to claim 113, wherein the polymorphism is located between 10 cM and 11 cM from pter.