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- W2091206110 abstract "Abnormal lipid levels are important risk factors for cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing total cholesterol (TC), LDL, HDL and triglyceride in families residing in American Samoa and Samoa as well as in a combined sample from the two polities. We adjusted the traits for a number of environmental covariates, such as smoking, alcohol consumption, physical activity, and material lifestyle. We found suggestive univariate linkage with log of the odds (LOD) scores > 3 for LDL on 6p21-p12 (LOD 3.13) in Samoa and on 12q21-q23 (LOD 3.07) in American Samoa. Furthermore, in American Samoa on 12q21, we detected genome-wide linkage (LODeq 3.38) to the bivariate trait TC-LDL. Telomeric of this region, on 12q24, we found suggestive bivariate linkage to TC-HDL (LODeq 3.22) in the combined study sample. In addition, we detected suggestive univariate linkage (LOD 1.9–2.93) on chromosomes 4p-q, 6p, 7q, 9q, 11q, 12q 13q, 15q, 16p, 18q, 19p, 19q and Xq23 and suggestive bivariate linkage (LODeq 2.05–2.62) on chromosomes 6p, 7q, 12p, 12q, and 19p-q. In conclusion, chromosome 6p and 12q may host promising susceptibility loci influencing lipid levels; however, the low degree of overlap between the three study samples strongly encourages further studies of the lipid-related traits. Abnormal lipid levels are important risk factors for cardiovascular diseases. We conducted genome-wide variance component linkage analyses to search for loci influencing total cholesterol (TC), LDL, HDL and triglyceride in families residing in American Samoa and Samoa as well as in a combined sample from the two polities. We adjusted the traits for a number of environmental covariates, such as smoking, alcohol consumption, physical activity, and material lifestyle. We found suggestive univariate linkage with log of the odds (LOD) scores > 3 for LDL on 6p21-p12 (LOD 3.13) in Samoa and on 12q21-q23 (LOD 3.07) in American Samoa. Furthermore, in American Samoa on 12q21, we detected genome-wide linkage (LODeq 3.38) to the bivariate trait TC-LDL. Telomeric of this region, on 12q24, we found suggestive bivariate linkage to TC-HDL (LODeq 3.22) in the combined study sample. In addition, we detected suggestive univariate linkage (LOD 1.9–2.93) on chromosomes 4p-q, 6p, 7q, 9q, 11q, 12q 13q, 15q, 16p, 18q, 19p, 19q and Xq23 and suggestive bivariate linkage (LODeq 2.05–2.62) on chromosomes 6p, 7q, 12p, 12q, and 19p-q. In conclusion, chromosome 6p and 12q may host promising susceptibility loci influencing lipid levels; however, the low degree of overlap between the three study samples strongly encourages further studies of the lipid-related traits. Noncommunicable diseases, especially cardiovascular diseases (CVDs), have increased worldwide, and while CVDs have been a major cause of death in the established market economies for many decades, CVDs now rank in the top five causes of death globally (1Mathers C.D. Loncar D. Projections of global mortality and burden of disease from 2002 to 2030.PLoS Med. 2006; 3: e442Crossref PubMed Scopus (7441) Google Scholar). There are many risk factors involved in the development of CVD; some of the most prominent ones include abnormal blood lipid levels, obesity, and hypertension, all of which are influenced by genetic as well as environmental factors (2Hawkins M.A. Markers of increased cardiovascular risk: are we measuring the most appropriate parameters?.Obes. Res. 2004; 12: 107-114Crossref Scopus (22) Google Scholar). In addition, environmental factors such as cigarette smoking (3Kannel W.B. Dawber T.R. Kagan A. Revotskie N. Stokes 3rd, J. Factors of risk in the development of coronary heart disease:–six year follow-up experience. The Framingham Study.Ann. Intern. Med. 1961; 55: 33-50Crossref PubMed Scopus (1145) Google Scholar) and lack of physical activity (4Blair S.N. Kampert J.B. Kohl 3rd, H.W. Barlow C.E. Macera C.A. Paffenbarger Jr., R.S. Gibbons L.W. Influences of cardiorespiratory fitness and other precursors on cardiovascular disease and all-cause mortality in men and women.J. Am. Med. Assoc. 1996; 276: 205-210Crossref PubMed Google Scholar) are established CVD risk factors. We have previously studied genetic influences on adiposity-related phenotypes in samples from American Samoa (5Dai F. Keighley E.D. Sun G. Indugula S.R. Roberts S.T. Aberg K. Smelser D. Tuitele J. Jin L. Deka R. et al.Genome-wide scan for adiposity-related phenotypes in adults from American Samoa.Int. J. Obes. (Lond). 2007; 31: 1832-1842Crossref PubMed Scopus (34) Google Scholar) and Samoa (6Dai F. Sun G. Aberg K. Keighley E.D. Indugula S.R. Roberts S.T. Smelser D. Viali S. Jin L. Deka R. et al.A whole genome linkage scan identifies multiple chromosomal regions influencing adiposity-related traits among Samoans.Ann. Hum. Genet. 2008; (Epub ahead of print.)doi: 10.1111/j.1469-1809.2008.00462Crossref PubMed Scopus (24) Google Scholar) as well as in a combined study sample from both polities (our unpublished data). The two polities belong to a single genetic population (7Tsai H.J. Sun G. Smelser D. Viali S. Tufa J. Jin L. Weeks D.E. McGarvey S.T. Deka R. Distribution of genome-wide linkage disequilibrium based on microsatellite loci in the Samoan population.Hum. Genomics. 2004; 1: 327-334Crossref PubMed Scopus (20) Google Scholar) that has been fairly isolated and has a common evolutionary history of ∼3,000 years. During the last several decades, the two polities have been differently influenced by economic modernization, which has resulted in increased differences in dietary intakes, physical activity, and other aspects of the social and behavioral environment (8Galanis D.J. McGarvey S.T. Quested C. Sio B. Afele-Fa'amuli S.A. Dietary intake of modernizing Samoans: implications for risk of cardiovascular disease.J. Am. Diet. Assoc. 1999; 99: 184-190Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar, 9Keighley E.D. McGarvey S.T. Turituri P. Viali S. Farming and adiposity in Samoan adults.Am. J. Hum. Biol. 2006; 18: 112-122Crossref PubMed Scopus (39) Google Scholar, 10McGarvey S.T. Obesity in Samoans and a perspective on its etiology in Polynesians.Am. J. Clin. Nutr. 1991; 53: 1586-1594Crossref Scopus (123) Google Scholar, 11McGarvey S.T. Cardiovascular disease (CVD) risk factors in Samoa and American Samoa, 1990–95.Pac. Health Dialog. 2001; 8: 157-162PubMed Google Scholar). In this study, we investigate the serum lipid profile, including total cholesterol (TC), LDL, HDL, and triglyceride (TG), in the combined study sample and in the polity-specific study samples from the Samoan islands. We apply variance component (VC) analysis, as implemented in the software LOKI (12Heath S.C. Markov chain Monte Carlo segregation and linkage analysis for oligogenic models.Am. J. Hum. Genet. 1997; 61: 748-760Abstract Full Text PDF PubMed Scopus (473) Google Scholar) and SOLAR (13Almasy L. Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees.Am. J. Hum. Genet. 1998; 62: 1198-1211Abstract Full Text Full Text PDF PubMed Scopus (2565) Google Scholar, 14Amos C.I. Robust variance-components approach for assessing genetic linkage in pedigrees.Am. J. Hum. Genet. 1994; 54: 535-543PubMed Google Scholar), to search for genetic linkage to the traits. The studied lipid traits are strongly influenced by genetic components; however, environmental factors are also of great importance (15Garg A. Simha V. Update on dyslipidemia.J. Clin. Endocrinol. Metab. 2007; 92: 1581-1589Crossref PubMed Scopus (84) Google Scholar). In an attempt to adjust for environmental influences on the traits, we include information on physical activity, consumption of alcohol and cigarettes, education, and an index of household possessions as covariates in the genetic model. The study samples are from the Samoan islands of Polynesia, which consist of two polities, the United States territory of American Samoa and the independent nation of Samoa. The total population on the Samoan islands consisted of ∼235,000 habitants in 2000–2001 (16Census of Population and Housing, American Samoa 2000. U. S. Department of Commerce, Washington, DC2004Google Scholar, 17Census of Population and Housing 2001. Government Printing House, Apia, Samoa2003Google Scholar). American Samoa, which has a higher level of education, a higher proportion of adults in wage and salary occupations, and higher economic and material lifestyle indicators than Samoa (8Galanis D.J. McGarvey S.T. Quested C. Sio B. Afele-Fa'amuli S.A. Dietary intake of modernizing Samoans: implications for risk of cardiovascular disease.J. Am. Diet. Assoc. 1999; 99: 184-190Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar, 9Keighley E.D. McGarvey S.T. Turituri P. Viali S. Farming and adiposity in Samoan adults.Am. J. Hum. Biol. 2006; 18: 112-122Crossref PubMed Scopus (39) Google Scholar, 10McGarvey S.T. Obesity in Samoans and a perspective on its etiology in Polynesians.Am. J. Clin. Nutr. 1991; 53: 1586-1594Crossref Scopus (123) Google Scholar, 11McGarvey S.T. Cardiovascular disease (CVD) risk factors in Samoa and American Samoa, 1990–95.Pac. Health Dialog. 2001; 8: 157-162PubMed Google Scholar), contains approximately one-fourth of the total population of the archipelago (17Census of Population and Housing 2001. Government Printing House, Apia, Samoa2003Google Scholar). The two polities have a common evolutionary history (7Tsai H.J. Sun G. Smelser D. Viali S. Tufa J. Jin L. Weeks D.E. McGarvey S.T. Deka R. Distribution of genome-wide linkage disequilibrium based on microsatellite loci in the Samoan population.Hum. Genomics. 2004; 1: 327-334Crossref PubMed Scopus (20) Google Scholar, 18Deka R. McGarvey S.T. Ferrell R.E. Kamboh M.I. Yu L.M. Aston C.E. Jin L. Chakraborty R. Genetic characterization of American and Western Samoans.Hum. Biol. 1994; 66: 805-822PubMed Google Scholar, 19Tsai H.J. Sun G. Weeks D.E. Kaushal R. Wolujewicz M. McGarvey S.T. Tufa J. Viali S. Deka R. Type 2 diabetes and three calpain-10 gene polymorphisms in Samoans: no evidence of association.Am. J. Hum. Genet. 2001; 69: 1236-1244Abstract Full Text Full Text PDF PubMed Scopus (81) Google Scholar), but during the last few decades American Samoa has been influenced by economic modernization to a much greater extent than Samoa (11McGarvey S.T. Cardiovascular disease (CVD) risk factors in Samoa and American Samoa, 1990–95.Pac. Health Dialog. 2001; 8: 157-162PubMed Google Scholar, 20Keighley E.D. McGarvey S.T. Quested C. McCuddin C. Viali S. Maga U.A. Nutrition and health in modernizing Samoans: temporal trends and adaptive perspectives.in: Ohtsuka R. Ulijaszek S.J. Health Changes in the Asia-Pacific Region: Biocultural and Epidemiological Approaches. Cambridge University Press, Cambridge, UK2007: 149-191Crossref Google Scholar). The participating families were selected based on the number of adult family members available. As described previously (5Dai F. Keighley E.D. Sun G. Indugula S.R. Roberts S.T. Aberg K. Smelser D. Tuitele J. Jin L. Deka R. et al.Genome-wide scan for adiposity-related phenotypes in adults from American Samoa.Int. J. Obes. (Lond). 2007; 31: 1832-1842Crossref PubMed Scopus (34) Google Scholar, 6Dai F. Sun G. Aberg K. Keighley E.D. Indugula S.R. Roberts S.T. Smelser D. Viali S. Jin L. Deka R. et al.A whole genome linkage scan identifies multiple chromosomal regions influencing adiposity-related traits among Samoans.Ann. Hum. Genet. 2008; (Epub ahead of print.)doi: 10.1111/j.1469-1809.2008.00462Crossref PubMed Scopus (24) Google Scholar), participants were selected from villages throughout American Samoa and Samoa, and probands and families were not selected based on any specific trait. All participants gave their informed consent, and protocols for this study were approved by the Brown University Institutional Review Board, the American Samoan Institutional Review Board, and the Government of Samoa, Ministry of Health, Health Research Committee. Interviews were used to collect information on pedigree structure. The combined study sample include 71 pedigrees containing 3,016 individuals, age ⩾ 18 years. The American Samoa sample set and the Samoan sample set include 34 families and 46 families, respectively. Twenty of the 71 families in the combined sample set had a mixed origin, containing family members from American Samoa as well as from Samoa. The number of genotyped individuals for each population is shown in Table 1. Each family has at least two genotyped individuals. The largest family has 246 genotyped individuals. Details about the pedigree structures can be found in supplementary Table I.TABLE 1Overview of samples and characteristics of nontransformed phenotypesAmerican SamoaSamoaCombinedCharacteristicMalesFemalesMalesFemalesMalesFemalesGenotyped markersaNumber of autosomal + X chromosomal markers included.368 (377bTotal number of markers genotyped.) + 14 (18)368 (378) + 14 (14)368 + 14Pedigrees344671 (20cPedigrees including individuals from both polities.)Genotyped individuals246332278294534630Phenotyped individuals261334336338597672Age (years)dMean and SD.43.2 (16.5)43 (16.1)41.7 (16.3)45.2 (17.4)42.4 (16.4)44.1 (16.8)SexePercentage of sample. The percentages do not sum to 100 due to missing values.445650504753Education (years)dMean and SD.11.7 (2.4)12.0 (2.4)9.7 (3.4)10.0 (3.0)10.6 (3.1)11.0 (2.9)Material lifestyle indexdMean and SD.9.1 (1.8)9.0 (1.8)7.6 (2.6)7.7 (2.6)8.3 (2.4)8.4 (2.3)Smoking cigarettes (yes/no)ePercentage of sample. The percentages do not sum to 100 due to missing values.38/5620/7438/5113/6738/5317/71Drinking alcohol (yes/no)ePercentage of sample. The percentages do not sum to 100 due to missing values.43/488/8032/543/7437/516/77Physical activity (hours per week)dMean and SD.4.1 (6.3)1.9 (3.6)8.6 (14.8)2.3 (5.7)6.7 (12.0)2.1 (4.8)Body mass index (kg/m2)dMean and SD.33.5 (7.6)36.6 (8.4)28.9 (5.4)33.0 (7.6)30.9 (6.9)34.8 (8.2)Total cholesterol (mg/dl)dMean and SD.189.4 (37.8)187.2 (38.2)198 (39.3)202.9 (37)194.2 (38.8)195 (38.3)LDL (mg/dl)dMean and SD.118.3 (34.5)119.1 (33.6)127.9 (36.7)133.4 (33.2)123.8 (36.1)126.1 (34.1)HDL (mg/dl)dMean and SD.38.6 (8.8)42.1 (8.4)47.1 (11.6)47.9 (10.8)43.3 (11.3)45.0 (10.0)Triglyceride (mg/dl)dMean and SD.199.1 (205.2)129.7 (76.6)115.7 (71)108.4 (55)152.7 (152.2)119.2 (67.6)a Number of autosomal + X chromosomal markers included.b Total number of markers genotyped.c Pedigrees including individuals from both polities.d Mean and SD.e Percentage of sample. The percentages do not sum to 100 due to missing values. Open table in a new tab Fasting blood samples were collected from participants after a 10 h overnight fast. Serum was separated and then stored at −40°C in the field sites. Serum was transported frozen on dry ice from the field sites to Providence, Rhode Island, for analysis. The TC and TG contents of the serum samples were determined by enzymatic assays on a Gilford Impact 400 computer-directed analyzer (Gilford Instruments, Oberlin, OH) (21Allain C.C. Poon L.S. Chan C.S. Richmond W. Fu P.C. Enzymatic determination of total serum cholesterol.Clin. Chem. 1974; 20: 470-475Crossref PubMed Scopus (7305) Google Scholar, 22Gidez L.I. Miller G.J. Burstein M. Slagle S. Eder H.A. Separation and quantitation of subclasses of human plasma high density lipoproteins by a simple precipitation procedure.J. Lipid Res. 1982; 23: 1206-1223Abstract Full Text PDF PubMed Google Scholar). Serum HDL was determined by the double precipitation methods of Gidez et al. (22Gidez L.I. Miller G.J. Burstein M. Slagle S. Eder H.A. Separation and quantitation of subclasses of human plasma high density lipoproteins by a simple precipitation procedure.J. Lipid Res. 1982; 23: 1206-1223Abstract Full Text PDF PubMed Google Scholar). Serum LDL was calculated by the Friedewald equation (23Friedewald W.T. Levy R.I. Fredrickson D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.Clin. Chem. 1972; 18: 499-502Crossref PubMed Scopus (63) Google Scholar): LDL = TC−HDL−TG/5 For samples with TG values of >400 mg/dl, the Friedewald equation is not valid (23Friedewald W.T. Levy R.I. Fredrickson D.S. Estimation of the concentration of low-density lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge.Clin. Chem. 1972; 18: 499-502Crossref PubMed Scopus (63) Google Scholar); therefore, the LDL trait was set to missing for these individuals. Standard anthropometric techniques and measurements were used to measure stature and weight and to calculate body mass index (BMI). Questionnaires were used to collect information on environmental factors such as education (years), physical activity (hours per week doing moderate to very hard sport activities and/or performing farm work), alcohol consumption (yes/no), smoking (yes/no), and household physical characteristics and possessions. Similar to prior Samoan studies by Galanis et al. (8Galanis D.J. McGarvey S.T. Quested C. Sio B. Afele-Fa'amuli S.A. Dietary intake of modernizing Samoans: implications for risk of cardiovascular disease.J. Am. Diet. Assoc. 1999; 99: 184-190Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar), we used the information on household physical characteristics and possessions to create a household possessions or material lifestyle index (MLSI) ranging from 1 (low material lifestyle standard) to 12 (high material lifestyle standard). The MLSI is based on information regarding domestic flooring type, electricity, cooking facilities, bathroom fixtures, water supply, and possession of a refrigerator, freezer, television, video cassette recorder, stereo, portable stereo, and motor vehicle, where each of the 12 subunits of the information may contribute one point to the index. Our current data sets do not contain information regarding treatment for nonnormal lipid levels. However, the awareness and care for risky blood lipid levels in the Samoan islands is very limited, so the use of treatments for these CVD risk factors is extremely rare. We genotyped the samples from American Samoa and from Samoa with the markers in the ABI PRISM linkage mapping set v2.5 MD10 (Applied Biosystems, Inc., Foster City, CA) as described previously (5Dai F. Keighley E.D. Sun G. Indugula S.R. Roberts S.T. Aberg K. Smelser D. Tuitele J. Jin L. Deka R. et al.Genome-wide scan for adiposity-related phenotypes in adults from American Samoa.Int. J. Obes. (Lond). 2007; 31: 1832-1842Crossref PubMed Scopus (34) Google Scholar, 6Dai F. Sun G. Aberg K. Keighley E.D. Indugula S.R. Roberts S.T. Smelser D. Viali S. Jin L. Deka R. et al.A whole genome linkage scan identifies multiple chromosomal regions influencing adiposity-related traits among Samoans.Ann. Hum. Genet. 2008; (Epub ahead of print.)doi: 10.1111/j.1469-1809.2008.00462Crossref PubMed Scopus (24) Google Scholar). The samples from American Samoa were genotyped with an ABI PRISM 3100 genetic analyzer and with an ABI PRISM 3130XL (Applied Biosystems), while the Samoan samples were genotyped using the ABI PRISM 3130XL. Even though the same set of markers was used throughout, the numbers of successfully genotyped markers in the study samples are slightly different. American Samoa and Samoa have 368 overlapping autosomal markers and 14 overlapping X chromosomal markers. The total number of genotyped markers in each study sample is shown in Table 1. All results reported in this study use only the overlapping markers. However, to ensure that the uniquely genotyped markers did not detect any linkage signals in American Samoa or Samoa, we also performed polity-specific genome-wide scans with all available markers. No differences in log of the odds (LOD) score were observed (data not shown). When a study sample contains pedigrees that have individuals originating from different subsets (here, the American Samoa and Samoa study samples) that have been genotyped with different instruments, it is important to ensure that the same allele label defines identical alleles, to be able to perform linkage analysis. We previously described how we merged the two sets of genotypes according to the minimal sum of differences in allele frequencies (our unpublished data). For the TG trait, we found some very extreme outliers. Therefore, we used winsorization to bring the upper and lower 5% of the TG values closer to the trait mean (24Fernandez J.R. Etzel C. Beasley T.M. Shete S. Amos C.I. Allison D.B. Improving the power of sib pair quantitative trait loci detection by phenotype winsorization.Hum. Hered. 2002; 53: 59-67Crossref PubMed Scopus (30) Google Scholar, 25Shete S. Beasley T.M. Etzel C.J. Fernandez J.R. Chen J. Allison D.B. Amos C.I. Effect of winsorization on power and type 1 error of variance components and related methods of QTL detection.Behav. Genet. 2004; 34: 153-159Crossref PubMed Scopus (38) Google Scholar). As described by Shete et al. (25Shete S. Beasley T.M. Etzel C.J. Fernandez J.R. Chen J. Allison D.B. Amos C.I. Effect of winsorization on power and type 1 error of variance components and related methods of QTL detection.Behav. Genet. 2004; 34: 153-159Crossref PubMed Scopus (38) Google Scholar), winsorization increases the power to detect linkage and reduces the bias in estimation of the major VC. Box-Cox power transformations (26Box G.E.P. Cox D.R. An analysis of transformations (with discussion).J. R. Stat. Soc. [Ser. A]. 1964; 26: 211-252Google Scholar) were applied to the lipid traits and to BMI, since they were not normally distributed. Using a VC analysis when the trait is nonnormally distributed can lead to a biased estimate of the major gene effect. Also, falsely assuming normality may lead to excessive type I errors (27Allison D.B. Neale M.C. Zannolli R. Schork N.J. Amos C.I. Blangero J. Testing the robustness of the likelihood-ratio test in a variance-component quantitative-trait loci-mapping procedure.Am. J. Hum. Genet. 1999; 65: 531-544Abstract Full Text Full Text PDF PubMed Scopus (262) Google Scholar). To further guard against false positives due to possible nonnormality, we used the option “tdist” for multivariate t-distribution in SOLAR (13Almasy L. Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees.Am. J. Hum. Genet. 1998; 62: 1198-1211Abstract Full Text Full Text PDF PubMed Scopus (2565) Google Scholar, 14Amos C.I. Robust variance-components approach for assessing genetic linkage in pedigrees.Am. J. Hum. Genet. 1994; 54: 535-543PubMed Google Scholar). In our previous studies investigating adiposity-related phenotypes in the population on the Samoan islands, we extensively checked for genotype errors and errors of pedigree structure prior to statistical analysis (5Dai F. Keighley E.D. Sun G. Indugula S.R. Roberts S.T. Aberg K. Smelser D. Tuitele J. Jin L. Deka R. et al.Genome-wide scan for adiposity-related phenotypes in adults from American Samoa.Int. J. Obes. (Lond). 2007; 31: 1832-1842Crossref PubMed Scopus (34) Google Scholar, 6Dai F. Sun G. Aberg K. Keighley E.D. Indugula S.R. Roberts S.T. Smelser D. Viali S. Jin L. Deka R. et al.A whole genome linkage scan identifies multiple chromosomal regions influencing adiposity-related traits among Samoans.Ann. Hum. Genet. 2008; (Epub ahead of print.)doi: 10.1111/j.1469-1809.2008.00462Crossref PubMed Scopus (24) Google Scholar) (our unpublished data). In short, to detect errors in pedigree structure, PEDSTATS (28Wigginton J.E. Abecasis G.R. PEDSTATS: descriptive statistics, graphics and quality assessment for gene mapping data.Bioinformatics. 2005; 21: 3445-3447Crossref PubMed Scopus (330) Google Scholar) was used to check for internal consistency of ages, and RELPAIR v2.0.1 (29Boehnke M. Cox N.J. Accurate inference of relationships in sib-pair linkage studies.Am. J. Hum. Genet. 1997; 61: 423-429Abstract Full Text PDF PubMed Scopus (244) Google Scholar, 30Epstein M.P. Duren W.L. Boehnke M. Improved inference of relationship for pairs of individuals.Am. J. Hum. Genet. 2000; 67: 1219-1231Abstract Full Text Full Text PDF PubMed Scopus (220) Google Scholar) and PREST (31McPeek M.S. Sun L. Statistical tests for detection of misspecified relationships by use of genome-screen data.Am. J. Hum. Genet. 2000; 66: 1076-1094Abstract Full Text Full Text PDF PubMed Scopus (286) Google Scholar, 32Sun L. Wilder K. McPeek M.S. Enhanced pedigree error detection.Hum. Hered. 2002; 54: 99-110Crossref PubMed Scopus (122) Google Scholar) were used to check the accuracy of the self-reported pedigree relationships. The “set correct_errors 1” option in LOKI (12Heath S.C. Markov chain Monte Carlo segregation and linkage analysis for oligogenic models.Am. J. Hum. Genet. 1997; 61: 748-760Abstract Full Text PDF PubMed Scopus (473) Google Scholar) was used to remove a minimal set of genotypes to generate Mendelianly consistent pedigrees for the autosomes. For the X chromosome, we used the option in Mega2 (33Mukhopadhyay N. Almasy L. Schroeder M. Mulvihill W.P. Weeks D.E. Mega2: data-handling for facilitating genetic linkage and association analyses.Bioinformatics. 2005; 21: 2556-2557Crossref PubMed Scopus (120) Google Scholar) and Pedcheck (34O'Connell J.R. Weeks D.E. PedCheck: a program for identification of genotype incompatibilities in linkage analysis.Am. J. Hum. Genet. 1998; 63: 259-266Abstract Full Text Full Text PDF PubMed Scopus (1821) Google Scholar) to remove all genotypes within the entire pedigree for a locus where a Mendelian inconsistency was detected. Mega2 and the statistical software R (The R Project for Statistical Computing) were used interactively to set up files for the analyses performed in this study. For the American Samoan study sample, the Samoa study sample, and the combined study sample from the two polities, we used the same genetic map based on Kosambi centimorgan (35Kong X. Murphy K. Raj T. He C. White P.S. Matise T.C. A combined linkage-physical map of the human genome.Am. J. Hum. Genet. 2004; 75: 1143-1148Abstract Full Text Full Text PDF PubMed Scopus (195) Google Scholar) and applied the same statistical strategy previously used when investigating adiposity-related phenotypes in these study samples (5Dai F. Keighley E.D. Sun G. Indugula S.R. Roberts S.T. Aberg K. Smelser D. Tuitele J. Jin L. Deka R. et al.Genome-wide scan for adiposity-related phenotypes in adults from American Samoa.Int. J. Obes. (Lond). 2007; 31: 1832-1842Crossref PubMed Scopus (34) Google Scholar, 6Dai F. Sun G. Aberg K. Keighley E.D. Indugula S.R. Roberts S.T. Smelser D. Viali S. Jin L. Deka R. et al.A whole genome linkage scan identifies multiple chromosomal regions influencing adiposity-related traits among Samoans.Ann. Hum. Genet. 2008; (Epub ahead of print.)doi: 10.1111/j.1469-1809.2008.00462Crossref PubMed Scopus (24) Google Scholar) (our unpublished data). As previously, we estimated marker allele frequencies from our pedigree data while simultaneously estimating the identity-by-descent (IBD) sharing matrices using LOKI (12Heath S.C. Markov chain Monte Carlo segregation and linkage analysis for oligogenic models.Am. J. Hum. Genet. 1997; 61: 748-760Abstract Full Text PDF PubMed Scopus (473) Google Scholar). However, in contrast to our previous studies (5Dai F. Keighley E.D. Sun G. Indugula S.R. Roberts S.T. Aberg K. Smelser D. Tuitele J. Jin L. Deka R. et al.Genome-wide scan for adiposity-related phenotypes in adults from American Samoa.Int. J. Obes. (Lond). 2007; 31: 1832-1842Crossref PubMed Scopus (34) Google Scholar, 6Dai F. Sun G. Aberg K. Keighley E.D. Indugula S.R. Roberts S.T. Smelser D. Viali S. Jin L. Deka R. et al.A whole genome linkage scan identifies multiple chromosomal regions influencing adiposity-related traits among Samoans.Ann. Hum. Genet. 2008; (Epub ahead of print.)doi: 10.1111/j.1469-1809.2008.00462Crossref PubMed Scopus (24) Google Scholar), in this study we generated the IBD matrices using information from all available genotyped pedigree members for all of the data regardless of originating polity. With this strategy, the IBD matrix itself will not cause any differences in the LOD score calculation regardless of whether the American Samoa, Samoa, or combined study sample is studied. We used the multipoint VC linkage analysis as implemented in SOLAR (13Almasy L. Blangero J. Multipoint quantitative-trait linkage analysis in general pedigrees.Am. J. Hum. Genet. 1998; 62: 1198-1211Abstract Full Text Full Text PDF PubMed Scopus (2565) Google Scholar, 14Amos C.I. Robust variance-components approach for assessing genetic linkage in pedigrees.Am. J. Hum. Genet. 1994; 54: 535-543PubMed Google Scholar) to search for quantitative trait loci (QTLs) for serum lipid levels on the autosomes. Prior to the actual multipoint linkage analysis, we used the “polygenic -s” option in SOLAR to fit the VC model and screen for significance of covariates. Information from all individuals that have complete phenotype information available, from investigated traits and covariates, is used to generate the polygenic model. In an attempt to adjust for environmental factors that might influence the traits, we screened two sets of covariates for their significant (P ⩽ 0.10) effect on the traits using SOLAR. The initial covariate set included education, physical activity, cigarette smoking, alcohol consumption, and MLSI as well as age, age2, sex, age × sex, and age2 × sex. To investigate the serum lipid-related traits independently of body composition, we used a second covariate set that included BMI in addition to all other covariates. Only significant covariates were included in the final genetic model. For a given phenotype, a likelihood ratio test for linkage was carried out and classical LOD scores were obtained by converting the statistic into values of log10. A LOD score of ⩾3.3" @default.
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