Genome scan for quantitative trait loci linked to high-density lipoprotein cholesterol: The NHLBI Family Heart Study.

We conducted a genome-wide linkage scan for quantitative trait loci influencing total HDL-cholesterol (HDL-C) concentration in a sample of 1027 whites from 101 families participating in the NHLBI Family Heart Study. To maximize the relative contribution of genetic components of variance to the total variance of HDL-C, the HDL-C phenotype was adjusted for age, age(2), body mass index, and Family Heart Study field center, and standardized HDL-C residuals were created separately for men and women. All analyses were completed by the variance components method, as implemented in the program GENEHUNTER using 383 anonymous markers typed at the NHLBI Mammalian Genotyping Service in Marshfield, Wis. Evidence for linkage of residual HDL-C was detected near marker D5S1470 at location 39.9 cM from the p-terminal of chromosome 5 (LOD=3.64). Suggestive linkage was detected near marker D13S1493 at location 27.5 cM on chromosome 13 (LOD=2.36). We conclude that at least 1 genomic region is likely to harbor a gene that influences interindividual variation in HDL cholesterol.

Further refinement of the MYP2 locus for autosomal dominant high myopia by linkage disequilibrium analysis.

INTRODUCTION: High myopia (>-6.00 diopters) is a complex common disorder that predisposes individuals to retinal detachment, glaucoma, macular degeneration, and premature cataracts. A recent linkage analysis of seven families with autosomal dominant high myopia has identified one locus (MYP2) for high myopia on chromosome 18p11.31 (Young et al.: Am J Hum Genet 1998;63:109-119). Haplotype analysis revealed an initial interval of 7.6 centimorgans (cM). METHODS: Transmission disequilibrium tests (TDT) with both the Statistical Analysis for Genetic Epidemiology (SAGE) 3.1 TDTEX and GENEHUNTER 2 (GH2) programs were performed using chromosome 18p marker alleles for this interval. RESULTS: Using SAGE analysis, the following p values were obtained for markers in marker order in this region: D18S1146 (p = 0.227), D18S481 (p = 0.001), D18S63 (p = 0.062), D18S1138 (p = 0.0004), D18S52 (p = 1.79 x 10(-6)), and D18S62 (p = 0.141). GH2 TDT analysis revealed the following p values for the best allele for the markers: D18S1146 (p = 0.083), D18S481 (p = 0.108), D18S63 (p = 0.034), D18S1138 (p = 0.011), D18S52 (p = 0.007), and D18S62 (p = 0.479). CONCLUSION: These data suggest that the gene for 18p11.31-linked high myopia is most proximal to marker D18S52, with a likely interval of 0.8 cM between markers D18S63 and D18S52. Due to the contraction of the interval size by TDT, these results provide a basis for focused positional cloning and candidate gene analysis at the MYP2 locus.

Evidence for a major gene influence on abdominal fat distribution: the Minnesota Breast Cancer Family Study.

Abdominal fat has been shown to be an important risk factor for many chronic conditions, including diabetes, heart disease, and breast cancer. The objective of this study was to provide evidence for a major gene influence on the ratio of waist to hip circumference (WHR), a measurement commonly used in large scale studies to indicate the presence of abdominal fat. Segregation analysis was conducted on three subsets of families from the Minnesota Breast Cancer Family Study. One analysis was conducted among families with WHR measurements on all women. Two additional analyses were conducted on subsets of women stratified on menopausal status. Multiple regression analysis was used to identify factors associated with WHR expressed as a continuous trait. Complex segregation analyses were performed on the continuous trait of WHR and the covariates identified in the regression analysis. In the analysis of all women, all hypotheses were rejected. Among premenopausal women, the environmental hypothesis with no heterogeneity between generations fit the data best (P = 0.85). However, among postmenopausal women, the requirements for conclusion of the presence of a major gene were met. All non-Mendelian hypotheses were rejected (P < 0.0001), but the additive hypothesis was not rejected (P = 0.19) and provided the best fit to the data. The putative major gene identified by this model accounted for 42% of total phenotypic variance in WHR among these postmenopausal women. The allele for high WHR had a frequency of 27%. These findings support the hypothesis that the distribution of abdominal fat in postmenopausal women is under genetic control.

Genome-wide linkage analysis of blood pressure in Mexican Americans.

The genetic mechanisms that control variation in blood pressure level are largely unknown. One of the first steps in understanding those mechanisms is the localization of the genes that have a significant effect on blood pressure. We performed genome scans of systolic (SBP) and diastolic blood pressure (DBP) on a population-based sample of families in the San Antonio Family Heart Study. A likelihood-based Mendelian model incorporating genotype-specific effects of sex, age, age(2), BMI, and blood pressure (SBP or DBP, as appropriate) as covariates was used to perform two-point lodscore (Z) linkage on 399 polymorphic markers. Results showed that the genotype-specific covariate effects were highly significant for both SBP and DBP. Linkage results showed that a quantitative trait locus (QTL) influencing DBP was significantly linked to D2S1790 (Z = 3.92, theta = 0.00) and showed suggestive linkage to D8S373 (Z = 1.92, theta = 0.00). A QTL influencing SBP showed suggestive linkage to D21S1440 (Z = 2.82, theta = 0.00) and D18S844 (Z = 2.09, theta = 0.11). Without the genotype-specific effects in the model, the linkage to D2S1790 was not even suggestive (Z = 1.33, theta = 0.09); thus genotype-specific modeling was crucial in detecting this linkage. A comparison with linkage studies based in other populations showed that the significant linkage to D2S1790 has been replicated at the same marker in the Quebec Family Study. The replicated significant linkage at D2S1790 may begin to establish the locations of the genes that significantly affect blood pressure across several human ethnic groups.

Genome-wide linkage analysis of pulse pressure in Mexican Americans.

Pulse pressure, a measure of aortic stiffness, is a strong predictor of cardiovascular mortality. To locate genes that affect pulse pressure, we performed genetic analysis on randomly ascertained families in the San Antonio Family Heart Study. Pulse pressure was defined as the difference between systolic and diastolic blood pressures. Likelihood methods were used to construct a model that had both single-locus and polygenic components for 46 families (1308 individuals). The single-locus component included sex-specific and genotype-specific effects of both age and body mass index. Using this model, we then performed 2-point linkage analysis in 10 families (440 individuals) that were among the largest of the 46 families and that had been genotyped for 399 polymorphic markers. The model that contained only the polygenic component and simple effects of the covariates showed pulse pressure heritability of 0.21. When the single-locus component was added, the sex-specific and genotype-specific effects of age and body mass index were highly significant (P<0.002). The full model accounted for 73% of the total variation of pulse pressure. Linkage analysis using this model with each marker revealed 4 markers with lod scores >1.9, which is the Lander-Kruglyak suggestive linkage standard. D21S1440 had a lod score of 2.78 with a recombination fraction (theta) of 0.02. D7S1799 had a lod score of 2.04 (theta=0.01), D8S1100 had a lod score of 1.98 (theta=0.08), and D18S844 had a lod score of 1.95 (theta=0.11). These results are highly correlated with results involving systolic blood pressure, indicating that pulse pressure may not be genetically distinct from systolic blood pressure.

A genome scan for renal function among hypertensives: the HyperGEN study.

Decreased renal function is often a complication of hypertension. Although it has been suggested that the response of the kidney to hypertension has an underlying genetic component, there is limited information suggesting that specific genetic regions or candidate genes contribute to the variability in creatinine clearance, a commonly used measure of kidney function. As part of the Hypertension Genetic Epidemiology Network (HyperGEN) study, creatinine clearance measurements were assessed in a large biracial sample of hypertensive siblings (466 African American subjects and 634 white subjects in 215 and 265 sibships, respectively). All participants were hypertensive before the age of 60 years, and the mean age of the siblings was 52 years among the African American subjects and 61 years among the white subjects. Two residual models were created for creatinine clearance: a minimally adjusted model (which included age and age(2)) and a fully adjusted model (which included age, age(2), lean body mass, pulse rate, pulse pressure, hormone-replacement therapy, educational status, and physical activity). Standardized residuals were calculated separately for men and women in both racial groups. The heritability of the residual creatinine clearance was 17% and 18% among the African American and white subjects, respectively. We conducted multipoint variance components linkage analysis using GENEHUNTER2 and 387 anonymous markers (Cooperative Human Linkage Center screening set 8). The best evidence for linkage in African American subjects was found on chromosome 3 (LOD = 3.61 at 214.6 cM, 3q27) with the fully adjusted model, and the best evidence in white subjects was found on chromosome 3 (LOD = 3.36 at 115.1 cM) with the minimally adjusted model. Positional candidate genes that are contained in and around the region on chromosome 3 (214.6 cM) that may contribute to renal function include enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase (EHHADH) and apolipoprotein D (ApoD). These findings suggest there may be genetic regions related to the variability of creatinine clearance among hypertensive individuals.

Possible locus on chromosome 18q influencing postural systolic blood pressure changes.

We conducted a genome-wide scan for quantitative trait loci influencing the systolic blood pressure, diastolic blood pressure, and pulse responses to a postural challenge in 498 white sibling-pairs from the Hypertension Genetic Epidemiology Network, a multicenter study of the genetic susceptibility to hypertension. All participants were hypertensive (systolic blood pressure >/=140 mm Hg, diastolic blood pressure >/=90 mm Hg, or on antihypertensive medications) with diagnosis before age 60. Blood pressure and pulse were measured by an oscillometric method after a 5-minute rest in a supine position and again immediately on standing. The genome scan included a total of 387 autosomal short-tandem-repeat polymorphisms typed by the National Heart, Lung, and Blood Institute Mammalian Genotyping Service at Marshfield. We used multipoint variance-components linkage analysis to identify possible quantitative trait loci influencing postural change phenotypes after adjusting for sex, age, and use of antihypertensive medications. There was suggestive evidence for linkage on chromosome 18q for the postural systolic blood pressure response (maximum logarithm of the odds score=2.6 at 80 centiMorgans). We also observed a maximum logarithm of the odds score of 1.9 for the systolic blood pressure response and 1.7 for the diastolic blood pressure response on chromosome 6p. The marker that demonstrated the strongest evidence for linkage for the systolic blood pressure response (D18S858) lies within 20 centiMorgans of a marker previously linked to rare familial orthostatic hypotensive syndrome. Our findings indicate that there may be 1 or more genes on chromosome 18q that regulate systolic blood pressure during the physiological recovery period after a postural stressor.

Segregation analysis of serum uric acid in the NHLBI Family Heart Study.

Segregation analysis was performed on the serum uric acid measurements from 523 randomly ascertained Caucasian families from the NHLBI Family Heart Study. Gender-specific standardized residuals were used as the phenotypic variable in both familial correlation and segregation analysis. Uric acid residuals were adjusted for age, age2, age3, body mass index (kg/m2), creatinine level, aspirin use (yes/no), total drinks (per week), HOMA insulin resistance index [(glucose * insulin)/22.5], diuretic use (yes/no), and triglyceride level. Sibling correlations (r=0.193) and parent-offspring correlations (r=0.217) were significantly different from zero, but these two familial correlations were not significantly different from one another. After adjustment for covariates, the heritability estimate for serum uric acid was 0.399. Segregation analysis rejected the "no major gene" model but was unable to discriminate between an "environmental" and a "Mendelian major gene" model. These results support the hypothesis that uric acid is a multifactorial trait possibly influenced by more than one major gene, modifying genes, and environmental factors.

No linkage of the lipoprotein lipase locus to hypertension in Caucasians.

OBJECTIVE: A previous study has shown significant linkage of five markers near the lipoprotein lipase locus to systolic blood pressure, but not to diastolic blood pressure, in nondiabetic members of 48 Taiwanese families selected for noninsulin-dependent diabetes. However, lipoprotein lipase markers did not appear strongly linked to systolic blood pressure in a study of Mexican-Americans using a variety of selection schemes. The objective of the current study was to test whether markers near the lipoprotein lipase gene were linked to hypertension in Caucasians. DESIGN: To test for linkage of genetic markers in or near the lipoprotein lipase gene to hypertension in Caucasians, two sets of Caucasian hypertensive sibships were genotyped. The samples included 261 sibships (431 effective sibpairs) from four field centers of the National Heart, Lung and Blood Institute Family Heart Study and 211 sibships (282 effective sibpairs) from the Health Family Tree database in Utah. RESULTS: Two highly polymorphic markers in or near the lipoprotein lipase gene showed no evidence of excess allele sharing in either set of hypertensive sibships. Combining the two datasets resulted in 653 and 713 effective sibpairs for the two markers, sharing 0.495 +/- 0.30 and 0.486 +/- 0.28 alleles identical by descent compared to an expected sharing of 0.50. Multipoint analysis of the two loci also did not show linkage (P = 0.95). CONCLUSIONS: We conclude that the lipoprotein lipase locus and nearby regions do not appear to be linked to hypertension in Caucasians.

A second locus for familial high myopia maps to chromosome 12q.

Myopia, or nearsightedness, is the most common eye disorder worldwide. "Pathologic" high myopia, or myopia of <=-6.00 diopters, predisposes individuals to retinal detachment, macular degeneration, cataract, or glaucoma. A locus for autosomal dominant pathologic high myopia has been mapped to 18p11.31. We now report significant linkage of high myopia to a second locus at the 12q21-23 region in a large German/Italian family. The family had no clinical evidence of connective-tissue abnormalities or glaucoma. The average age at diagnosis of myopia was 5.9 years. The average spherical-component refractive error for the affected individuals was -9.47 diopters. Markers flanking or intragenic to the genes for the 18p locus, Stickler syndromes type I and II (12q13.1-q13.3 and 6p21.3), Marfan syndrome (15q21.1), and juvenile glaucoma (chromosome 1q21-q31) showed no linkage to the myopia in this family. The maximum LOD score with two-point linkage analysis in this pedigree was 3.85 at a recombination fraction of .0010, for markers D12S1706 and D12S327. Recombination events identified markers D12S1684 and D12S1605 as flanking markers that define a 30.1-cM interval on chromosome 12q21-23, for the second myopia gene. These results confirm genetic heterogeneity of myopia. The identification of this gene may provide insight into the pathophysiology of myopia and eye development.

Two major loci control variation in beta-lipoprotein cholesterol and response to dietary fat and cholesterol in baboons.

We explored the genetic control of cholesterolemic responses to dietary cholesterol and fat in 575 pedigreed baboons. We measured cholesterol in beta-lipoproteins (low density lipoprotein cholesterol [LDLC]) in blood drawn from baboons while they were consuming a baseline (low in cholesterol and fat) diet, a high-saturated fat (lard) diet, and a high-cholesterol, high-saturated fat diet. In addition to baseline levels (LDLC(Base)), we analyzed two variables for diet response: LDLC(RF), which represents the LDLC response to increasing dietary fat (ie, high-fat diet minus baseline), and LDLC(RC), which represents the LDLC response to increasing dietary cholesterol level (ie, high-cholesterol, high-fat diet minus high-fat diet). Heritabilities (h2) of the 3 traits were 0.59 for LDLC(Base), 0.14 for LDLC(RF), and 0.59 for LDLC(RC). In addition, LDLC(Base) and LDLC(RC) had a significant genetic correlation (ie, rhoG=0.54), suggesting that 1 or more genes exert pleiotropic effects on the 2 traits. Segregation analyses detected a single major locus that accounted for nearly all genetic variation in LDLC(RC) and some genetic variation in LDLC(Base) and LDLC(RF) and confirmed the presence of a different major locus that influences LDLC(Base) alone. Preliminary linkage analyses indicated that neither locus was linked to the LDL receptor gene, a likely candidate locus for LDLC. Detection of these major loci with large effects on the LDLC response to dietary cholesterol in a nonhuman primate offers hope of detecting and ultimately identifying similar loci that determine LDLC variation in human populations.

Evidence that a locus for familial high myopia maps to chromosome 18p.

Myopia, or nearsightedness, is the most common human eye disorder. A genomewide screen was conducted to map the gene(s) associated with high, early-onset, autosomal dominant myopia. Eight families that each included two or more individuals with >=-6.00 diopters (D) myopia, in two or more successive generations, were identified. Myopic individuals had no clinical evidence of connective-tissue abnormalities, and the average age at diagnosis of myopia was 6.8 years. The average spherical component refractive error for the affected individuals was -9.48 D. The families contained 82 individuals; of these, DNA was available for 71 (37 affected). Markers flanking or intragenic to the genes for Stickler syndrome types 1 and 2 (chromosomes 12q13.1-q13.3 and 6p21.3, respectively), Marfan syndrome (chromosome 15q21.1), and juvenile glaucoma (chromosome 1q21-q31) were also analyzed. No evidence of linkage was found for markers for the Stickler syndrome types 1 and 2, the Marfan syndrome, or the juvenile glaucoma loci. After a genomewide search, evidence of significant linkage was found on chromosome 18p. The maximum LOD score was 9.59, with marker D18S481, at a recombination fraction of .0010. Haplotype analysis further refined this myopia locus to a 7.6-cM interval between markers D18S59 and D18S1138 on 18p11.31.

Linkage of essential hypertension to the angiotensinogen locus in Mexican Americans.

Essential hypertension has been linked to a highly polymorphic marker at the angiotensinogen locus, and association with a polymorphism in this locus has been found in some populations. We tested the hypothesis that these same polymorphic markers are linked to essential hypertension in Mexican Americans. The data comprised all the affected relative pairs in 46 extended families chosen at random from a low-income barrio in San Antonio. Specifically, we searched for linkage by testing for excessive marker alleles shared identical by descent (IBD) among hypertensive relative pairs. When women taking oral contraceptives or hormones were excluded, the affected relative pairs shared a significant excess of alleles IBD for the highly heterozygous GT repeat polymorphism (P=.038) and were marginally significant for the M235T variant (P=.079), which has a much lower heterozygosity (0.43 versus 0.85 for the GT repeat). We also assayed plasma levels of angiotensinogen and, using likelihood methods, found no significant association (P=.43) between plasma levels of angiotensinogen and M235T genotypes. These results support the linkage of essential hypertension to the angiotensinogen locus but do not indicate a specific role for the M235T variant.

Impact of adjustments for intermediate phenotypes on the power to detect linkage.

Since the manifestation of a complex disease is likely to be influenced through multiple genetic and/or environmental pathways, it may be advantageous to adjust for these multiple factors in a genetic analysis of a complex quantitative trait. Sib-pair linkage analysis was performed on the simulated complex quantitative trait Q1 after adjustment for age, sex, and the environmental factor (i.e., minimally adjusted) and all combinations of the four intermediate phenotypes Q2, Q3, Q4, and Q5 (n = 15) for all 200 replications of the nuclear families data set. From the minimally adjusted Q1, the power to detect suggestive linkage to any of the three loci affecting Q1 was 0.585 with a false positive rate of 0.0025. Adjusting Q1 for Q3 increased the power to detect suggestive linkage to 0.860 with a similar false positive rate. Additional adjustments for Q2, Q4, and Q5 yielded no substantial improvements in power nor changes in the false positive rate. The power to detect significant linkage was also substantially improved after adjustment of Q1 for Q3 with no change in the false positive rate. The adjustment of a complex trait for other factors in the causal pathway reduces the phenotype variability and enhances the ability to detect linkage.

Prior segregation analysis and the power to detect linkage.

Complex parametric segregation and linkage analysis was performed on the simulated quantitative trait Q1 for all 200 replicates of the nuclear families data set. The segregation analysis inferred a major gene in 46% of the replicates. Among all replicates, including those that rejected a major gene, the power to detect suggestive linkage to any of three loci affecting Q1 was 0.600 and the false positive rate was 0.002. Among the replicates where a major gene was found, the power to detect suggestive linkage was 0.652 and the false positive rate was also 0.002. Thus, for purposes of linkage to this complex trait, a prior segregation then linkage analysis approach located a gene in 30% of all replicates, whereas a linkage only approach located a gene in 60% of all replicates.

Genetic analysis of the IRS. Pleiotropic effects of genes influencing insulin levels on lipoprotein and obesity measures.

Insulin resistance is part of a metabolic syndrome that also includes non-insulin-dependent diabetes mellitus, dyslipidemia, obesity, and hypertension. It has been hypothesized that insulin resistance represents the primary physiological defect underlying this syndrome. Since insulin resistance is at least partially genetically determined, we hypothesized that genes influencing insulin resistance would have pleiotropic effects on a number of other traits, including triglyceride (TG) and HDL cholesterol levels, body mass index (BMI) and body fat distribution, and blood pressure levels. To investigate this hypothesis, we analyzed data obtained from individuals in 41 families enrolled in the San Antonio Family Heart Study. Statistical methods that take advantage of the relatedness among individuals were used to differentiate between genetic and nongenetic (ie, environmental) contributions to phenotypic variation between traits. Serum levels of fasting and 2-hour insulin (measured in 767 and 743 nondiabetic family members, respectively) were used as a measure of insulin resistance. The genetic correlations were high between insulin levels (both fasting and 2-hour) and each of the following: BMI, HDL level, waist-to-hip ratio, and subscapular-to-triceps ratio, indicating that the same gene, or set of genes, influences each pair of traits. In contrast, the genetic correlations of insulin levels with systolic and diastolic blood pressures were low. We have previously shown that a single diallelic locus accounts for 31% of the phenotypic variation in 2-hour insulin levels in this population. We conducted a bivariate segregation analysis to see if the common genetic effects on insulin and these other traits could be attributable to this single locus. These results indicated a significant effect of the 2-hour insulin locus on fasting insulin levels (P = .02) and BMI (P = .05), with the "high" insulin allele associated with higher levels of fasting insulin but lower levels of BMI. There was no detectable effect of this locus on HDL level, TG level, subscapular-to-triceps ratio, or blood pressure. Overall, these results suggest that a common set of genes influencing insulin levels also influences other insulin resistance syndrome-related traits, although for the most part this pleiotropy is not attributable to the 2-hour insulin level major locus.

Evidence for a major gene affecting postchallenge insulin levels in Mexican-Americans.

Hyperinsulinemia, which is considered a hallmark of insulin resistance, precedes the development of non-insulin-dependent diabetes mellitus (NIDDM). Results of family and twin studies have shown that heredity influences insulin resistance and insulin levels. In Caucasian families ascertained through two or more NIDDM siblings, it has been reported that single genes with large effects, i.e., major genes, influence both fasting and 1-h postchallenge insulin levels. To determine whether a major gene affects 2-h postchallenge insulin levels in Mexican-Americans, we conducted segregation analyses using data collected on 527 pedigreed individuals from 27 families in San Antonio, TX. Probands for the families were randomly ascertained and all first-, second-, and third-degree relatives aged 16 years and older were invited to participate. Subjects received a 2-h oral glucose tolerance test, and diabetes was diagnosed according to World Health Organization criteria. We found that an autosomal dominant major gene best described the inheritance of 2-h insulin levels (ln-transformed) in these 27 families. Of the individuals in the population, 17% were homozygous for the 2-h low-insulin allele (back-transformed mean = 125 pmol/l) and 83% were heterozygous or homozygous for the 2-h high-insulin allele (back-transformed mean = 406 pmol/l). This major gene accounted for 31% of the variance in ln(2-h insulin levels) in this population. Using quantitative trait linkage analyses, we excluded tight linkage between this gene affecting 2-h insulin levels and three candidate loci for insulin levels: the insulin receptor gene, the low-density lipoprotein receptor gene, and the glucokinase gene.(ABSTRACT TRUNCATED AT 250 WORDS)

Segregation and linkage analysis of the complex trait Q1.

Segregation and linkage analysis of GAW9 Problem 2 quantitative trait 1 (Q1) was performed. Eight segregation models comprising all possible combinations of the environmental factor (EF), quantitative trait 2 (Q2), and quantitative trait 3 (Q3) as covariates were considered. Seven of the eight segregation models showed strong evidence for a major gene, the other model was marginal. When all genotypes are known, some evidence for linkage (lod > 2) was found to all three of the markers that affect Q1. Furthermore, four of the eight models each showed some linkage (lod > 2) to two of the three markers that affect Q1 with no false positives. Each of these segregation analysis major genes is a hybrid combination of the true multiple loci that affect Q1.

The influence of response bias on segregation and linkage analysis.

Response bias in epidemiologic studies can occur if affected individuals are more (or less) likely to participate in a survey than their unaffected counterparts. To examine the effect of response bias in the context of a family study, we conducted segregation and linkage analysis in all 1,000 individuals in the Problem 2 data set, and in two different 65% samples: one sample consisting of 648 randomly selected individuals, and the other sample nonrandomly constructed so that individuals with high levels of Q1 were oversampled. In this simulation the ability to detect major genes for Q1-Q4 in segregation analysis and to link these putative major genes to genetic markers in linkage analysis was not markedly different between the 65% random and the 65% enriched samples.