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1.  Evidence for bivariate linkage of obesity and HDL-C levels in the Framingham Heart Study 
BMC Genetics  2003;4(Suppl 1):S52.
Epidemiological studies have indicated that obesity and low high-density lipoprotein (HDL) levels are strong cardiovascular risk factors, and that these traits are inversely correlated. Despite the belief that these traits are correlated in part due to pleiotropy, knowledge on specific genes commonly affecting obesity and dyslipidemia is very limited. To address this issue, we first conducted univariate multipoint linkage analysis for body mass index (BMI) and HDL-C to identify loci influencing variation in these phenotypes using Framingham Heart Study data relating to 1702 subjects distributed across 330 pedigrees. Subsequently, we performed bivariate multipoint linkage analysis to detect common loci influencing covariation between these two traits.
We scanned the genome and identified a major locus near marker D6S1009 influencing variation in BMI (LOD = 3.9) using the program SOLAR. We also identified a major locus for HDL-C near marker D2S1334 on chromosome 2 (LOD = 3.5) and another region near marker D6S1009 on chromosome 6 with suggestive evidence for linkage (LOD = 2.7). Since these two phenotypes have been independently mapped to the same region on chromosome 6q, we used the bivariate multipoint linkage approach using SOLAR. The bivariate linkage analysis of BMI and HDL-C implicated the genetic region near marker D6S1009 as harboring a major gene commonly influencing these phenotypes (bivariate LOD = 6.2; LODeq = 5.5) and appears to improve power to map the correlated traits to a region, precisely.
We found substantial evidence for a quantitative trait locus with pleiotropic effects, which appears to influence both BMI and HDL-C phenotypes in the Framingham data.
PMCID: PMC1866489  PMID: 14975120
2.  DEAR1 Is a Dominant Regulator of Acinar Morphogenesis and an Independent Predictor of Local Recurrence-Free Survival in Early-Onset Breast Cancer 
PLoS Medicine  2009;6(5):e1000068.
Ann Killary and colleagues describe a new gene that is genetically altered in breast tumors, and that may provide a new breast cancer prognostic marker.
Breast cancer in young women tends to have a natural history of aggressive disease for which rates of recurrence are higher than in breast cancers detected later in life. Little is known about the genetic pathways that underlie early-onset breast cancer. Here we report the discovery of DEAR1 (ductal epithelium–associated RING Chromosome 1), a novel gene encoding a member of the TRIM (tripartite motif) subfamily of RING finger proteins, and provide evidence for its role as a dominant regulator of acinar morphogenesis in the mammary gland and as an independent predictor of local recurrence-free survival in early-onset breast cancer.
Methods and Findings
Suppression subtractive hybridization identified DEAR1 as a novel gene mapping to a region of high-frequency loss of heterozygosity (LOH) in a number of histologically diverse human cancers within Chromosome 1p35.1. In the breast epithelium, DEAR1 expression is limited to the ductal and glandular epithelium and is down-regulated in transition to ductal carcinoma in situ (DCIS), an early histologic stage in breast tumorigenesis. DEAR1 missense mutations and homozygous deletion (HD) were discovered in breast cancer cell lines and tumor samples. Introduction of the DEAR1 wild type and not the missense mutant alleles to complement a mutation in a breast cancer cell line, derived from a 36-year-old female with invasive breast cancer, initiated acinar morphogenesis in three-dimensional (3D) basement membrane culture and restored tissue architecture reminiscent of normal acinar structures in the mammary gland in vivo. Stable knockdown of DEAR1 in immortalized human mammary epithelial cells (HMECs) recapitulated the growth in 3D culture of breast cancer cell lines containing mutated DEAR1, in that shDEAR1 clones demonstrated disruption of tissue architecture, loss of apical basal polarity, diffuse apoptosis, and failure of lumen formation. Furthermore, immunohistochemical staining of a tissue microarray from a cohort of 123 young female breast cancer patients with a 20-year follow-up indicated that in early-onset breast cancer, DEAR1 expression serves as an independent predictor of local recurrence-free survival and correlates significantly with strong family history of breast cancer and the triple-negative phenotype (ER−, PR−, HER-2−) of breast cancers with poor prognosis.
Our data provide compelling evidence for the genetic alteration and loss of expression of DEAR1 in breast cancer, for the functional role of DEAR1 in the dominant regulation of acinar morphogenesis in 3D culture, and for the potential utility of an immunohistochemical assay for DEAR1 expression as an independent prognostic marker for stratification of early-onset disease.
Editors' Summary
Each year, more than one million women discover that they have breast cancer. This type of cancer begins when cells in the breast that line the milk-producing glands or the tubes that take the milk to the nipples (glandular and ductal epithelial cells, respectively) acquire genetic changes that allow them to grow uncontrollably and to move around the body (metastasize). The uncontrolled division leads to the formation of a lump that can be detected by mammography (a breast X-ray) or by manual breast examination. Breast cancer is treated by surgical removal of the lump or, if the cancer has started to spread, by removal of the whole breast (mastectomy). Surgery is usually followed by radiotherapy or chemotherapy. These “adjuvant” therapies are designed to kill any remaining cancer cells but can make patients very ill. Generally speaking, the outlook for women with breast cancer is good. In the US, for example, nearly 90% of affected women are still alive five years after their diagnosis.
Why Was This Study Done?
Although breast cancer is usually diagnosed in women in their 50s or 60s, some women develop breast cancer much earlier. In these women, the disease is often very aggressive. Compared to older women, young women with breast cancer have a lower overall survival rate and their cancer is more likely to recur locally or to metastasize. It would be useful to be able to recognize those younger women at the greatest risk of cancer recurrence so that they could be offered intensive surveillance and adjuvant therapy; those women at a lower risk could have gentler treatments. To achieve this type of “stratification,” the genetic changes that underlie breast cancer in young women need to be identified. In this study, the researchers discover a gene that is genetically altered (by mutations or deletion) in early-onset breast cancer and then investigate whether its expression can predict outcomes in women with this disease.
What Did the Researchers Do and Find?
The researchers used “suppression subtractive hybridization” to identify a new gene in a region of human Chromosome 1 where loss of heterozygosity (LOH; a genetic alteration associated with cancer development) frequently occurs. They called the gene DEAR1 (ductal epithelium-associated RING Chromosome 1) to indicate that it is expressed in ductal and glandular epithelial cells and encodes a “RING finger” protein (specifically, a subtype called a TRIM protein; RING finger proteins such as BRCA1 and BRCA2 have been implicated in early cancer development and in a large fraction of inherited breast cancers). DEAR1 expression was reduced or lost in several ductal carcinomas in situ (a local abnormality that can develop into breast cancer) and advanced breast cancers, the researchers report. Furthermore, many breast tumors carried DEAR1 missense mutations (genetic changes that interfere with the normal function of the DEAR1 protein) or had lost both copies of DEAR1 (the human genome contains two copies of most genes). To determine the function of DEAR1, the researchers replaced a normal copy of DEAR1 into a breast cancer cell that had a mutation in DEAR1. They then examined the growth of these genetically manipulated cells in special three-dimensional cultures. The breast cancer cells without DEAR1 grew rapidly without an organized structure while the breast cancer cells containing the introduced copy of DEAR1 formed structures that resembled normal breast acini (sac-like structures that secrete milk). In normal human mammary epithelial cells, the researchers silenced DEAR1 expression and also showed that without DEAR1, the normal mammary cells lost their ability to form proper acini. Finally, the researchers report that DEAR1 expression (detected “immunohistochemically”) was frequently lost in women who had had early-onset breast cancer and that the loss of DEAR1 expression correlated with reduced local recurrence-free survival, a strong family history of breast cancer and with a breast cancer subtype that has a poor outcome.
What Do These Findings Mean?
These findings indicate that genetic alteration and loss of expression of DEAR1 are common in breast cancer. Although laboratory experiments may not necessarily reflect what happens in people, the results from the three-dimensional culture of breast epithelial cells suggest that DEAR1 may regulate the normal acinar structure of the breast. Consequently, loss of DEAR1 expression could be an early event in breast cancer development. Most importantly, the correlation between DEAR1 expression and both local recurrence in early-onset breast cancer and a breast cancer subtype with a poor outcome suggests that it might be possible to use DEAR1 expression to identify women with early-onset breast cancer who have an increased risk of local recurrence so that they get the most appropriate treatment for their cancer.
Additional Information
Please access these Web sites via the online version of this summary at
This study is further discussed in a PLoS Medicine Perspective by Senthil Muthuswamy
The US National Cancer Institute provides detailed information for patients and health professionals on all aspects of breast cancer, including information on genetic alterations in breast cancer (in English and Spanish)
The MedlinePlus Encyclopedia provides information for patients about breast cancer; MedlinePlus also provides links to many other breast cancer resources (in English and Spanish)
The UK charities Cancerbackup (now merged with MacMillan Cancer Support) and Cancer Research UK also provide detailed information about breast cancer
PMCID: PMC2673042  PMID: 19536326
3.  A Genomic Scan for Age at Onset of Alzheimer’s Disease in 437 Families From the NIMH Genetic Initiative 
We performed linkage analysis for age at onset (AAO) in the total Alzheimer’s disease (AD) NIMH sample (N = 437 families). Families were subset as late-onset (320 families, AAO ≥65) and early/ mixed (117 families, at least 1 member with 50< AAO <65). Treating AAO as a censored trait, we obtained the gender and APOE adjusted residuals in a parametric survival model and analyzed the residuals as the quantitative trait (QT) in variance-component linkage analysis. For comparison, AAO–age at exam (AAE) was analyzed as the QT adjusting for affection status, gender, and APOE. Heritabilities for residual and AAO–AAE outcomes were 66.3% and 74.0%, respectively for the total sample, 56.0% and 57.0% in the late-onset sample, and 33.0% for both models in the early/mixed sample. The residual model yielded the largest peaks onchromosome1 with LOD = 2.0 at 190 cM in the total set, LOD = 1.7 at 116 cM on chromosome 3 in the early/mixed subset, and LOD = 1.4 at 71 and 86 cM, respectively, on chromosome 6 in the late-onset subset. For the AAO–AAE outcome model the largest peaks were identified on chromosome 1 at 137 cM (LOD = 2.8) and chromosome 6 at 69 cM (LOD = 2.3) and 86 cM (LOD = 2.2) all in the late-onset subset. Additional peaks with LOD ≥1 were identified on chromosomes 1, 2, 3, 6, 8, 9, 10, and 12 for the total sample and each subset. Results replicate previous findings, but identify additional suggestive peaks indicating the genetics of AAO in AD is complex with many chromosomal regions potentially containing modifying genes.
PMCID: PMC2661765  PMID: 18189239
Alzhiemer’s disease; censored quantitative trait; variance-component linkage analysis
4.  An international collaborative family-based whole genome quantitative trait linkage scan for myopic refractive error 
Molecular Vision  2012;18:720-729.
To investigate quantitative trait loci linked to refractive error, we performed a genome-wide quantitative trait linkage analysis using single nucleotide polymorphism markers and family data from five international sites.
Genomic DNA samples from 254 families were genotyped by the Center for Inherited Disease Research using the Illumina Linkage Panel IVb. Quantitative trait linkage analysis was performed on 225 Caucasian families and 4,656 markers after accounting for linkage disequilibrium and quality control exclusions. Two refractive quantitative phenotypes, sphere (SPH) and spherical equivalent (SE), were analyzed. The SOLAR program was used to estimate identity by descent probabilities and to conduct two-point and multipoint quantitative trait linkage analyses.
We found 29 markers and 11 linkage regions reaching peak two-point and multipoint logarithms of the odds (LODs)>1.5. Four linkage regions revealed at least one LOD score greater than 2: chromosome 6q13–6q16.1 (LOD=1.96 for SPH, 2.18 for SE), chromosome 5q35.1–35.2 (LOD=2.05 for SPH, 1.80 for SE), chromosome 7q11.23–7q21.2 (LOD=1.19 for SPH, 2.03 for SE), and chromosome 3q29 (LOD=1.07 for SPH, 2.05 for SE). Among these, the chromosome 6 and chromosome 5 regions showed the most consistent results between SPH and SEM. Four linkage regions with multipoint scores above 1.5 are near or within the known myopia (MYP) loci of MYP3, MYP12, MYP14, and MYP16. Overall, we observed consistent linkage signals across the SPH and SEM phenotypes, although scores were generally higher for the SEM phenotype.
Our quantitative trait linkage analyses of a large myopia family cohort provided additional evidence for several known MYP loci, and identified two additional potential loci at chromosome 6q13–16.1 and chromosome 5q35.1–35.2 for myopia. These results will benefit the efforts toward determining genes for myopic refractive error.
PMCID: PMC3324362  PMID: 22509102
5.  Genome-wide scan on plasma triglyceride and high density lipoprotein cholesterol levels, accounting for the effects of correlated quantitative phenotypes 
BMC Genetics  2003;4(Suppl 1):S47.
Plasma triglyceride and high density lipoprotein cholesterol levels are inversely correlated and both are genetically related. Two correlated traits may be influenced both by shared and unshared genes. The power to detect unshared trait-specific genes may be increased by incorporating correlated traits as covariates. The power to localize the shared genes may be improved by bivariate analysis. Univariate genome scans were carried out on triglyceride (high density lipoprotein cholesterol) with and without using high density lipoprotein cholesterol (triglyceride) as a covariate, and bivariate linkage analysis on triglyceride and high density lipoprotein cholesterol using the 330 Framingham pedigrees of the Genetic Analysis Workshop 13 data. The results of five genome scans were compared to determine the chromosomal regions which may harbor the genes influencing variation specific to triglycerides, specific to high density lipoprotein cholesterol, or the covariation of both triglyceride and high density lipoprotein cholesterol.
The results of our five genome scans identified some chromosomal regions with possible quantitative trait loci (QTL) that may specifically influence one trait, such as the regions on chromosome 1 (at 1 cM near marker 280we5), on high density lipoprotein cholesterol, or control the covariation of both traits, such as the regions on chromosome 7 (at 169 cM near marker GATA30D09), chromosome 12 (at 3 cM near marker GATA4H03), chromosome 20 (at 49 cM near marker GATA29F06), chromosome 2 (at 146 cM near marker GATA8H05), and chromosome 6 (at 148 cM near marker GATA184A08) on triglyceride and high density lipoprotein cholesterol. The one on chromosome 6 had a LOD score of 3.1 with the bivariate linkage analysis.
There is strong evidence for a QTL on chromosome 6 near marker GATA184A08 appearing to influence the variation of high density lipoprotein cholesterol and triglycerides in the Framingham population.
PMCID: PMC1866483  PMID: 14975115
6.  Diabetes-specific genetic effects on obesity traits in American Indian populations: the Strong Heart Family Study 
BMC Medical Genetics  2008;9:90.
Body fat mass distribution and deposition are determined by multiple environmental and genetic factors. Obesity is associated with insulin resistance, hyperinsulinemia, and type 2 diabetes. We previously identified evidence for genotype-by-diabetes interaction on obesity traits in Strong Heart Family Study (SHFS) participants. To localize these genetic effects, we conducted genome-wide linkage scans of obesity traits in individuals with and without type 2 diabetes, and in the combined sample while modeling interaction with diabetes using maximum likelihood methods (SOLAR 2.1.4).
SHFS recruited American Indians from Arizona, North and South Dakota, and Oklahoma. Anthropometric measures and diabetes status were obtained during a clinic visit. Marker allele frequencies were derived using maximum likelihood methods estimated from all individuals and multipoint identity by descent sharing was estimated using Loki. We used variance component linkage analysis to localize quantitative trait loci (QTLs) influencing obesity traits. We tested for evidence of additive and QTL-specific genotype-by-diabetes interactions using the regions identified in the diabetes-stratified analyses.
Among 245 diabetic and 704 non-diabetic American Indian individuals, we detected significant additive gene-by-diabetes interaction for weight and BMI (P < 0.02). In analysis accounting for QTL-specific interaction (P < 0.001), we detected a QTL for weight on chromosome 1 at 242 cM (LOD = 3.7). This chromosome region harbors the adiponectin receptor 1 gene, which has been previously associated with obesity.
These results suggest distinct genetic effects on body mass in individuals with diabetes compared to those without diabetes, and a possible role for one or more genes on chromosome 1 in the pathogenesis of obesity.
PMCID: PMC2572048  PMID: 18854016
7.  Age-At-Onset Linkage Analysis in Caribbean Hispanics with Familial Late-Onset Alzheimer’s Disease 
Neurogenetics  2007;9(1):51-60.
The aim of the study was to identify chromosomal regions containing putative genetic variants influencing age-at-onset in familial late-onset Alzheimer’s disease. Data from a genome-wide scan that included genotyping of APOE was analyzed in 1,161 individuals from 209 families of Caribbean Hispanic ancestry with a mean age-at-onset of 73.3 years multiply affected by late-onset Alzheimer’s disease. Two-point and multipoint analyses were conducted using variance component methods from 376 microsatellite markers with an average inter-marker distance of 9.3 cM. Family-based test of association were also conducted for the same set of markers. Age-at-onset of symptoms among affected individuals was used as the quantitative trait. Our results showed that the presence of APOE-ε4 lowered the age-at-onset by three years. Using linkage analysis strategy, the highest LOD scores were obtained using a conservative definition of LOAD at 5q15 (LOD 3.1) 17q25.1 (LOD=2.94) and 14q32.12 (LOD=2.36) and 7q36.3 (LOD=2.29) in covariate adjusted models that included APOE-ε4. Both linkage and family-based association identified 17p13 as a candidate region. In addition, family-based association analysis showed markers at 12q13 (p=0.00002), 13q (p=0.00043) and 14q23 (p=0.00046) to be significantly associated with age at onset. The current study supports the hypothesis that there are additional genetic loci that could influence age-at-onset of late onset Alzheimer’s disease. The novel loci at 5q15, 17q25.1, 13q and 17p13, and the previously reported loci at 7q36.3, 12q13, 14q23 and 14q32 need further investigation.
PMCID: PMC2701253  PMID: 17940814
Alzheimer’s disease; age-at-onset; linkage analysis; family-based association analysis; APOE
8.  Genome-wide linkage analysis of age at onset of alcohol dependence: a comparison between microsatellites and single-nucleotide polymorphisms 
BMC Genetics  2005;6(Suppl 1):S12.
Using the dataset provided for Genetic Analysis Workshop 14 by the Collaborative Study on the Genetics of Alcoholism, we performed genome-wide linkage analysis of age at onset of alcoholism to compare the utility of microsatellites and single-nucleotide polymorphisms (SNPs) in genetic linkage study.
A multipoint nonparametric variance component linkage analysis method was applied to the survival distribution function obtained from semiparametric proportional hazards model of the age at onset phenotype of alcoholism. Three separate linkage analyses were carried out using 315 microsatellites, 2,467 and 9,467 SNPs, spanning the 22 autosomal chromosomes.
Heritability of age at onset was estimated to be approximately 12% (p < 0.001). We observed weak correlation, both in trend and strength, of genome-wide linkage signals between microsatellites and SNPs. Results from SNPs revealed more and stronger linkage signals across the genome compared with those from microsatellites. The only suggestive evidence of linkage from microsatellites was on chromosome 1 (LOD of 1.43). Differences in map densities between the two sets of SNPs used in this study did not appear to confer an advantage in terms of strength of linkage signals.
Our study provided support for better performance of dense SNP maps compared with the sparse mirosatellite maps currently available for linkage analysis of quantitative traits. This better performance could be attributable to precise definition and high map resolutions achievable with dense SNP maps, thus resulting in increased power to detect possible loci affecting given trait or disease.
PMCID: PMC1866818  PMID: 16451577
9.  A variable age of onset segregation model for linkage analysis, with correction for ascertainment, applied to glioma 
We propose a two-step model-based approach, with correction for ascertainment, to linkage analysis of a binary trait with variable age of onset and apply it to a set of multiplex pedigrees segregating for adult glioma.
First, we fit segregation models by formulating the likelihood for a person to have a bivariate phenotype, affection status and age of onset, along with other covariates, and from these we estimate population trait allele frequencies and penetrance parameters as a function of age (N=281 multiplex glioma pedigrees). Second, the best fitting models are used as trait models in multipoint linkage analysis (N=74 informative multiplex glioma pedigrees). To correct for ascertainment, a prevalence constraint is used in the likelihood of the segregation models for all 281 pedigrees. Then the trait allele frequencies are re-estimated for the pedigree founders of the subset of 74 pedigrees chosen for linkage analysis.
Using the best fitting segregation models in model-based multipoint linkage analysis, we identified two separate peaks on chromosome 17; the first agreed with a region identified by Shete et al. who used model-free affected-only linkage analysis, but with a narrowed peak: and the second agreed with a second region they found but had a larger maximum log of the odds (LOD).
Our approach has the advantage of not requiring markers to be in linkage equilibrium unless the minor allele frequency is small (markers which tend to be uninformative for linkage), and of using more of the available information for LOD-based linkage analysis.
PMCID: PMC3518573  PMID: 22962404
Glioma; model-based linkage; segregation; age of onset; prevalence constraint
10.  Loci on Chromosomes 2, 4, 9, and 16 for body weight, body length, and adiposity identified in a genome scan of an F2 intercross between the 129P3/J and C57BL/6ByJ mouse strains 
Mice have proved to be a powerful model organism for understanding obesity in humans. Single gene mutants and genetically modified mice have been used to identify obesity genes, and the discovery of loci for polygenic forms of obesity in the mouse is an important next step. To pursue this goal, the inbred mouse strains 129P3/J (129) and C57BL/6ByJ (B6), which differ in body weight, body length, and adiposity, were used in an F2 cross to identify loci affecting these phenotypes. Linkages were determined in a two-phase process. In the first phase, 169 randomly selected F2 mice were genotyped for 134 markers that covered all autosomes and the X Chromosome (Chr). Significant linkages were found for body weight and body length on Chr 2. In addition, we detected several suggestive linkages on Chr 2 (adiposity), 9 (body weight, body length, and adiposity), and 16 (adiposity), as well as two suggestive sex-dependent linkages for body length on Chrs 4 and 9. In the second phase, 288 additional F2 mice were genotyped for markers near these regions of linkage. In the combined set of 457 F2 mice, six significant linkages were found: Chr 2 (Bwq5, body weight and Bdln3, body length), Chr 4 (Bdln6, body length, males only), Chr 9 (Bwq6, body weight and Adip5, adiposity), and Chr 16 (Adip9, adiposity), as well as several suggestive linkages (Adip2, adiposity on Chr 2; Bdln4 and Bdln5, body length on Chr 9). In addition, there was a suggestive linkage to body length in males on Chr 9 (Bdln4). For adiposity, there was evidence for epistatic interactions between loci on Chr 9 (Adip5) and 16 (Adip9). These results reinforce the concept that obesity is a complex trait. Genetic loci and their interactions, in conjunction with sex, age, and diet, determine body size and adiposity in mice.
PMCID: PMC1435867  PMID: 12856282
11.  Genome-wide association with bone mass and geometry in the Framingham Heart Study 
BMC Medical Genetics  2007;8(Suppl 1):S14.
Osteoporosis is characterized by low bone mass and compromised bone structure, heritable traits that contribute to fracture risk. There have been no genome-wide association and linkage studies for these traits using high-density genotyping platforms.
We used the Affymetrix 100K SNP GeneChip marker set in the Framingham Heart Study (FHS) to examine genetic associations with ten primary quantitative traits: bone mineral density (BMD), calcaneal ultrasound, and geometric indices of the hip. To test associations with multivariable-adjusted residual trait values, we used additive generalized estimating equation (GEE) and family-based association tests (FBAT) models within each sex as well as sexes combined. We evaluated 70,987 autosomal SNPs with genotypic call rates ≥80%, HWE p ≥ 0.001, and MAF ≥10% in up to 1141 phenotyped individuals (495 men and 646 women, mean age 62.5 yrs). Variance component linkage analysis was performed using 11,200 markers.
Heritability estimates for all bone phenotypes were 30–66%. LOD scores ≥3.0 were found on chromosomes 15 (1.5 LOD confidence interval: 51,336,679–58,934,236 bp) and 22 (35,890,398–48,603,847 bp) for femoral shaft section modulus. The ten primary phenotypes had 12 associations with 100K SNPs in GEE models at p < 0.000001 and 2 associations in FBAT models at p < 0.000001. The 25 most significant p-values for GEE and FBAT were all less than 3.5 × 10-6 and 2.5 × 10-5, respectively. Of the 40 top SNPs with the greatest numbers of significantly associated BMD traits (including femoral neck, trochanter, and lumbar spine), one half to two-thirds were in or near genes that have not previously been studied for osteoporosis. Notably, pleiotropic associations between BMD and bone geometric traits were uncommon. Evidence for association (FBAT or GEE p < 0.05) was observed for several SNPs in candidate genes for osteoporosis, such as rs1801133 in MTHFR; rs1884052 and rs3778099 in ESR1; rs4988300 in LRP5; rs2189480 in VDR; rs2075555 in COLIA1; rs10519297 and rs2008691 in CYP19, as well as SNPs in PPARG (rs10510418 and rs2938392) and ANKH (rs2454873 and rs379016). All GEE, FBAT and linkage results are provided as an open-access results resource at .
The FHS 100K SNP project offers an unbiased genome-wide strategy to identify new candidate loci and to replicate previously suggested candidate genes for osteoporosis.
PMCID: PMC1995606  PMID: 17903296
12.  Two New Loci for Body-Weight Regulation Identified in a Joint Analysis of Genome-Wide Association Studies for Early-Onset Extreme Obesity in French and German Study Groups 
PLoS Genetics  2010;6(4):e1000916.
Meta-analyses of population-based genome-wide association studies (GWAS) in adults have recently led to the detection of new genetic loci for obesity. Here we aimed to discover additional obesity loci in extremely obese children and adolescents. We also investigated if these results generalize by estimating the effects of these obesity loci in adults and in population-based samples including both children and adults. We jointly analysed two GWAS of 2,258 individuals and followed-up the best, according to lowest p-values, 44 single nucleotide polymorphisms (SNP) from 21 genomic regions in 3,141 individuals. After this DISCOVERY step, we explored if the findings derived from the extremely obese children and adolescents (10 SNPs from 5 genomic regions) generalized to (i) the population level and (ii) to adults by genotyping another 31,182 individuals (GENERALIZATION step). Apart from previously identified FTO, MC4R, and TMEM18, we detected two new loci for obesity: one in SDCCAG8 (serologically defined colon cancer antigen 8 gene; p = 1.85×10−8 in the DISCOVERY step) and one between TNKS (tankyrase, TRF1-interacting ankyrin-related ADP-ribose polymerase gene) and MSRA (methionine sulfoxide reductase A gene; p = 4.84×10−7), the latter finding being limited to children and adolescents as demonstrated in the GENERALIZATION step. The odds ratios for early-onset obesity were estimated at ∼1.10 per risk allele for both loci. Interestingly, the TNKS/MSRA locus has recently been found to be associated with adult waist circumference. In summary, we have completed a meta-analysis of two GWAS which both focus on extremely obese children and adolescents and replicated our findings in a large followed-up data set. We observed that genetic variants in or near FTO, MC4R, TMEM18, SDCCAG8, and TNKS/MSRA were robustly associated with early-onset obesity. We conclude that the currently known major common variants related to obesity overlap to a substantial degree between children and adults.
Author Summary
Genome-wide association studies (GWAS) have successfully contributed to the detection of genetic variants involved in body-weight regulation. We jointly analysed two GWAS for early-onset extreme obesity in 2,258 individuals of European origin and followed-up the findings in 3,141 individuals. Evidence for association of markers in two new genetic loci was shown (SDCCAG8 on chromosome 1q43–q44 and between TNKS/MSRA on chromosome 8p23.1). We also re-identified variants in or near FTO, MC4R, and TMEM18 to be associated with extreme obesity. In addition, we assessed the effect of the markers in 31,182 obese, lean, normal weight, and unselected individuals from population-based samples and showed that the variants near FTO, MC4R, TMEM18, and SDCCAG8 were consistently associated with obesity. For variants of TNKS/MSRA, the obesity association was limited to children and adolescents. In summary, we detected two new obesity loci and confirmed that the currently known major common variants related to obesity overlap to a substantial degree between children and adults.
PMCID: PMC2858696  PMID: 20421936
13.  Whole genome QTL mapping for growth, meat quality and breast meat yield traits in turkey 
BMC Genetics  2011;12:61.
The turkey (Meleagris gallopavo) is an important agricultural species and is the second largest contributor to the world's poultry meat production. Demand of turkey meat is increasing very rapidly. Genetic markers linked to genes affecting quantitative traits can increase the selection response of animal breeding programs. The use of these molecular markers for the identification of quantitative trait loci, and subsequently fine-mapping of quantitative trait loci regions, allows for pinpointing of genes that underlie such economically important traits.
The quantitative trait loci analyses of the growth curve, body weight, breast yield and the meat quality traits showed putative quantitative trait loci on 21 of the 27 turkey chromosomes covered by the linkage map. Forty-five quantitative trait loci were detected across all traits and these were found in 29 different regions on 21 chromosomes. Out of the 45 quantitative trait loci, twelve showed significant (p < 0.01) evidence of linkage while the remaining 33 showed suggestive evidence (p < 0.05) of linkage with different growth, growth curve, meat quality and breast yield traits.
A large number of quantitative trait loci were detected across the turkey genome, which affected growth, breast yield and meat quality traits. Pleiotropic effects or close linkages between quantitative trait loci were suggested for several of the chromosomal regions. The comparative analysis regarding the location of quantitative trait loci on different turkey, and on the syntenic chicken chromosomes, along with their phenotypic associations, revealed signs of functional conservation between these species.
PMCID: PMC3142527  PMID: 21745371
14.  Genome-Wide Mapping of Susceptibility to Coronary Artery Disease Identifies a Novel Replicated Locus on Chromosome 17 
PLoS Genetics  2006;2(5):e72.
Coronary artery disease (CAD) is a leading cause of death world-wide, and most cases have a complex, multifactorial aetiology that includes a substantial heritable component. Identification of new genes involved in CAD may inform pathogenesis and provide new therapeutic targets. The PROCARDIS study recruited 2,658 affected sibling pairs (ASPs) with onset of CAD before age 66 y from four European countries to map susceptibility loci for CAD. ASPs were defined as having CAD phenotype if both had CAD, or myocardial infarction (MI) phenotype if both had a MI. In a first study, involving a genome-wide linkage screen, tentative loci were mapped to Chromosomes 3 and 11 with the CAD phenotype (1,464 ASPs), and to Chromosome 17 with the MI phenotype (739 ASPs). In a second study, these loci were examined with a dense panel of grid-tightening markers in an independent set of families (1,194 CAD and 344 MI ASPs). This replication study showed a significant result on Chromosome 17 (MI phenotype; p = 0.009 after adjustment for three independent replication tests). An exclusion analysis suggests that further genes of effect size λsib > 1.24 are unlikely to exist in these populations of European ancestry. To our knowledge, this is the first genome-wide linkage analysis to map, and replicate, a CAD locus. The region on Chromosome 17 provides a compelling target within which to identify novel genes underlying CAD. Understanding the genetic aetiology of CAD may lead to novel preventative and/or therapeutic strategies.
Coronary artery disease (CAD), which presents clinically as a heart attack (myocardial infarction) or angina, is a leading cause of death world-wide. The aetiology of CAD is complex with a substantial heritable component. Although there is a huge knowledge-base detailing many aspects of the underlying pathophysiology of CAD, it is likely that undiscovered pathways exist. Positional cloning projects can identify novel susceptibility genes; in the first step genome-wide linkage screens are used to assign loci to specific chromosomes.
The authors have collected 2,036 CAD families from four European countries, in order to maximise the power of detecting genes that confer modest risks. A genome-wide linkage scan identified three promising regions for intensive study; one of the linked regions (Chromosome 17) was confined to families with multiple cases of myocardial infarction and was replicated in a second independent series of families. In addition the linkage scan confirmed a previously identified locus on Chromosome 2. These results demonstrate that novel CAD susceptibility genes are tractable to positional cloning which promises to lead to the identification of new molecular insights into this condition, and hopefully, new treatments.
PMCID: PMC1463045  PMID: 16710446
15.  Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5 
BMC Genetics  2012;13:12.
Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas).
We identified four genes with SNPs that showed the strongest and most consistent associations with LDL-C and CAD: EBF1, PPP2R2B, SPOCK1, and PRELID2. The most significant results for association of SNPs with LDL-C were: EBF1, rs6865969, p = 0.01; PPP2R2B, rs2125443, p = 0.005; SPOCK1, rs17600115, p = 0.003; and PRELID2, rs10074645, p = 0.0002). The most significant results for CAD were EBF1, rs6865969, p = 0.007; PPP2R2B, rs7736604, p = 0.0003; SPOCK1, rs17170899, p = 0.004; and PRELID2, rs7713855, p = 0.003.
Using an intermediate disease-related quantitative trait of LDL-C we have identified four novel CAD genes, EBF1, PRELID2, SPOCK1, and PPP2R2B. These four genes should be further examined in future functional studies as candidate susceptibility loci for cardiovascular disease mediated through LDL-cholesterol pathways.
PMCID: PMC3309961  PMID: 22369142
Cardiovascular Disease; Positional Cloning; Intermediate Phenotype; Linkage; Fine Mapping
16.  DNA sequence polymorphisms within the bovine guanine nucleotide-binding protein Gs subunit alpha (Gsα)-encoding (GNAS) genomic imprinting domain are associated with performance traits 
BMC Genetics  2011;12:4.
Genes which are epigenetically regulated via genomic imprinting can be potential targets for artificial selection during animal breeding. Indeed, imprinted loci have been shown to underlie some important quantitative traits in domestic mammals, most notably muscle mass and fat deposition. In this candidate gene study, we have identified novel associations between six validated single nucleotide polymorphisms (SNPs) spanning a 97.6 kb region within the bovine guanine nucleotide-binding protein Gs subunit alpha gene (GNAS) domain on bovine chromosome 13 and genetic merit for a range of performance traits in 848 progeny-tested Holstein-Friesian sires. The mammalian GNAS domain consists of a number of reciprocally-imprinted, alternatively-spliced genes which can play a major role in growth, development and disease in mice and humans. Based on the current annotation of the bovine GNAS domain, four of the SNPs analysed (rs43101491, rs43101493, rs43101485 and rs43101486) were located upstream of the GNAS gene, while one SNP (rs41694646) was located in the second intron of the GNAS gene. The final SNP (rs41694656) was located in the first exon of transcripts encoding the putative bovine neuroendocrine-specific protein NESP55, resulting in an aspartic acid-to-asparagine amino acid substitution at amino acid position 192.
SNP genotype-phenotype association analyses indicate that the single intronic GNAS SNP (rs41694646) is associated (P ≤ 0.05) with a range of performance traits including milk yield, milk protein yield, the content of fat and protein in milk, culled cow carcass weight and progeny carcass conformation, measures of animal body size, direct calving difficulty (i.e. difficulty in calving due to the size of the calf) and gestation length. Association (P ≤ 0.01) with direct calving difficulty (i.e. due to calf size) and maternal calving difficulty (i.e. due to the maternal pelvic width size) was also observed at the rs43101491 SNP. Following adjustment for multiple-testing, significant association (q ≤ 0.05) remained between the rs41694646 SNP and four traits (animal stature, body depth, direct calving difficulty and milk yield) only. Notably, the single SNP in the bovine NESP55 gene (rs41694656) was associated (P ≤ 0.01) with somatic cell count--an often-cited indicator of resistance to mastitis and overall health status of the mammary system--and previous studies have demonstrated that the chromosomal region to where the GNAS domain maps underlies an important quantitative trait locus for this trait. This association, however, was not significant after adjustment for multiple testing. The three remaining SNPs assayed were not associated with any of the performance traits analysed in this study. Analysis of all pairwise linkage disequilibrium (r2) values suggests that most allele substitution effects for the assayed SNPs observed are independent. Finally, the polymorphic coding SNP in the putative bovine NESP55 gene was used to test the imprinting status of this gene across a range of foetal bovine tissues.
Previous studies in other mammalian species have shown that DNA sequence variation within the imprinted GNAS gene cluster contributes to several physiological and metabolic disorders, including obesity in humans and mice. Similarly, the results presented here indicate an important role for the imprinted GNAS cluster in underlying complex performance traits in cattle such as animal growth, calving, fertility and health. These findings suggest that GNAS domain-associated polymorphisms may serve as important genetic markers for future livestock breeding programs and support previous studies that candidate imprinted loci may act as molecular targets for the genetic improvement of agricultural populations. In addition, we present new evidence that the bovine NESP55 gene is epigenetically regulated as a maternally expressed imprinted gene in placental and intestinal tissues from 8-10 week old bovine foetuses.
PMCID: PMC3025900  PMID: 21214909
17.  Identifying the genetic determinants of transcription factor activity 
Genome-wide messenger RNA expression levels are highly heritable. However, the molecular mechanisms underlying this heritability are poorly understood.The influence of trans-acting polymorphisms is often mediated by changes in the regulatory activity of one or more sequence-specific transcription factors (TFs). We use a method that exploits prior information about the DNA-binding specificity of each TF to estimate its genotype-specific regulatory activity. To this end, we perform linear regression of genotype-specific differential mRNA expression on TF-specific promoter-binding affinity.Treating inferred TF activity as a quantitative trait and mapping it across a panel of segregants from an experimental genetic cross allows us to identify trans-acting loci (‘aQTLs') whose allelic variation modulates the TF. A few of these aQTL regions contain the gene encoding the TF itself; several others contain a gene whose protein product is known to interact with the TF.Our method is strictly causal, as it only uses sequence-based features as predictors. Application to budding yeast demonstrates a dramatic increase in statistical power, compared with existing methods, to detect locus-TF associations and trans-acting loci. Our aQTL mapping strategy also succeeds in mouse.
Genetic sequence variation naturally perturbs mRNA expression levels in the cell. In recent years, analysis of parallel genotyping and expression profiling data for segregants from genetic crosses between parental strains has revealed that mRNA expression levels are highly heritable. Expression quantitative trait loci (eQTLs), whose allelic variation regulates the expression level of individual genes, have successfully been identified (Brem et al, 2002; Schadt et al, 2003). The molecular mechanisms underlying the heritability of mRNA expression are poorly understood. However, they are likely to involve mediation by transcription factors (TFs). We present a new transcription-factor-centric method that greatly increases our ability to understand what drives the genetic variation in mRNA expression (Figure 1). Our method identifies genomic loci (‘aQTLs') whose allelic variation modulates the protein-level activity of specific TFs. To map aQTLs, we integrate genotyping and expression profiling data with quantitative prior information about DNA-binding specificity of transcription factors in the form of position-specific affinity matrices (Bussemaker et al, 2007). We applied our method in two different organisms: budding yeast and mouse.
In our approach, the inferred TF activity is explicitly treated as a quantitative trait, and genetically mapped. The decrease of ‘phenotype space' from that of all genes (in the eQTL approach) to that of all TFs (in our aQTL approach) increases the statistical power to detect trans-acting loci in two distinct ways. First, as each inferred TF activity is derived from a large number of genes, it is far less noisy than mRNA levels of individual genes. Second, the number of trait/marker combinations that needs to be tested for statistical significance in parallel is roughly two orders of magnitude smaller than for eQTLs. We identified a total of 103 locus-TF associations, a more than six-fold improvement over the 17 locus-TF associations identified by several existing methods (Brem et al, 2002; Yvert et al, 2003; Lee et al, 2006; Smith and Kruglyak, 2008; Zhu et al, 2008). The total number of distinct genomic loci identified as an aQTL equals 31, which includes 11 of the 13 previously identified eQTL hotspots (Smith and Kruglyak, 2008).
To better understand the mechanisms underlying the identified genetic linkages, we examined the genes within each aQTL region. First, we found four ‘local' aQTLs, which encompass the gene encoding the TF itself. This includes the known polymorphism in the HAP1 gene (Brem et al, 2002), but also novel predictions of trans-acting polymorphisms in RFX1, STB5, and HAP4. Second, using high-throughput protein–protein interaction data, we identified putative causal genes for several aQTLs. For example, we predict that a polymorphism in the cyclin-dependent kinase CDC28 antagonistically modulates the functionally distinct cell cycle regulators Fkh1 and Fkh2. In this and other cases, our approach naturally accounts for post-translational modulation of TF activity at the protein level.
We validated our ability to predict locus-TF associations in yeast using gene expression profiles of allele replacement strains from a previous study (Smith and Kruglyak, 2008). Chromosome 15 contains an aQTL whose allelic status influences the activity of no fewer than 30 distinct TFs. This locus includes IRA2, which controls intracellular cAMP levels. We used the gene expression profile of IRA2 replacement strains to confirm that the polymorphism within IRA2 indeed modulates a subset of the TFs whose activity was predicted to link to this locus, and no other TFs.
Application of our approach to mouse data identified an aQTL modulating the activity of a specific TF in liver cells. We identified an aQTL on mouse chromosome 7 for Zscan4, a transcription factor containing four zinc finger domains and a SCAN domain. Even though we could not detect a candidate causal gene for Zscan4p because of lack of information about the mouse genome, our result demonstrates that our method also works in higher eukaryotes.
In summary, aQTL mapping has a greatly improved sensitivity to detect molecular mechanisms underlying the heritability of gene expression. The successful application of our approach to yeast and mouse data underscores the value of explicitly treating the inferred TF activity as a quantitative trait for increasing statistical power of detecting trans-acting loci. Furthermore, our method is computationally efficient, and easily applicable to any other organism whenever prior information about the DNA-binding specificity of TFs is available.
Analysis of parallel genotyping and expression profiling data has shown that mRNA expression levels are highly heritable. Currently, only a tiny fraction of this genetic variance can be mechanistically accounted for. The influence of trans-acting polymorphisms on gene expression traits is often mediated by transcription factors (TFs). We present a method that exploits prior knowledge about the in vitro DNA-binding specificity of a TF in order to map the loci (‘aQTLs') whose inheritance modulates its protein-level regulatory activity. Genome-wide regression of differential mRNA expression on predicted promoter affinity is used to estimate segregant-specific TF activity, which is subsequently mapped as a quantitative phenotype. In budding yeast, our method identifies six times as many locus-TF associations and more than twice as many trans-acting loci as all existing methods combined. Application to mouse data from an F2 intercross identified an aQTL on chromosome VII modulating the activity of Zscan4 in liver cells. Our method has greatly improved statistical power over existing methods, is mechanism based, strictly causal, computationally efficient, and generally applicable.
PMCID: PMC2964119  PMID: 20865005
gene expression; gene regulatory networks; genetic variation; quantitative trait loci; transcription factors
18.  Genome scan in familial late-onset Alzheimer’s disease: a locus on chromosome 6 contributes to age at onset 
Alzheimer’s disease (AD) is a common, genetically complex, fatal neurodegenerative disorder of late life. Although several genes are known to play a role in early-onset AD, identification of the genetic basis of late onset AD (LOAD) has been challenging, with only the APOE gene known to have a high contribution to both AD risk and age-at-onset. Here we present the first genome-scan analysis of the complete, well-characterized University of Washington LOAD sample of 119 pedigrees, using age-at-onset as the trait of interest. The analysis approach used allows for a multilocus trait model while at the same time accommodating age censoring, effects of APOE as a known genetic covariate, and full pedigree and marker information. The results provide strong evidence for linkage of loci contributing to age-at-onset to genomic regions on chromosome 6q16.3, and to 19q13.42 in the region of the APOE locus. There was evidence for interaction between APOE and the locus on chromosome 6q and suggestive evidence for linkage to chromosomes 11p13, 15q12-14, and 19p13.12. These results provide the first independent confirmation of an AD age-at-onset locus on chromosome 6 and suggest that further efforts towards identifying the underlying causal locus or loci are warranted.
PMCID: PMC3654841  PMID: 23355194
linkage analysis; MCMC; oligogenic; dementia; age-censored
19.  Association of the timing of puberty with a chromosome 2 locus 
Twin studies indicate that the timing of pubertal onset is under strong genetic control. However, genes controlling pubertal timing in the general population have not yet been identified.
To facilitate the identification of genes influencing the timing of pubertal growth and maturation, we conducted linkage mapping of constitutional delay of growth and puberty (CDGP), an extreme variant of normal pubertal timing, in extended families.
Participants and methods:
Fifty-two families multiply affected with CDGP were genotyped with 383 multiallelic markers. CDGP was defined based on growth charts (the age at onset of growth spurt, peak height velocity, or attaining adult height taking place at least 1.5 SD later than average). Chromosomal regions co-segregating with CDGP were identified with parametric affected only linkage analysis using CDGP as a dichotomized trait.
The genome-wide scan detected linkage of CDGP to a region on chromosome 2p13-2q13. The two-point HLOD-score was 1.62 (α 0.27) and the corresponding multipoint HLOD 2.54 (α 0.31). Fine-mapping the region at 1 cM resolution increased the multipoint HLOD-score to 4.44 (α 0.41). The linkage became weaker if also family members diagnosed with CDGP without growth data were included in the analyses.
The pericentromeric region of chromosome 2 harbors a gene predisposing to pubertal delay in multiply affected pedigrees. Our data suggest that this locus may be a component of the internal clock controlling the timing of the onset of puberty.
PMCID: PMC2685475  PMID: 18812480
puberty timing; genes; linkage mapping
20.  A genome-wide scan maps a novel autosomal dominant juvenile-onset open-angle glaucoma locus to 2p15-16 
Molecular Vision  2008;14:739-744.
To study the clinical features and to perform genetic linkage study in two large Chinese families with autosomal dominant juvenile-onset primary open-angle glaucoma (POAG).
Eighteen members of one Chinese family and 25 members of a second Chinese family with juvenile-onset primary open-angle glaucoma (POAG) were investigated. Thirteen members in one family and 14 members in the second family were diagnosed with juvenile-onset POAG. A genome-wide linkage scan was performed on one family using 411 short tandem repeat (STR) markers. Subsequent fine mapping was performed in the two study families using a modified fluorescent labeled M13 primer method.
A whole genome-wide scan in one family showed linkage to chromosome 2p15-p16 with a two-point maximum LOD score of 5.01 at θ=0 between the disease phenotype and STR marker D2S337. The second family was also mapped to the same locus with a two-point maximum LOD score of 6.30 at θ=0 for D2S378. Haplotype analysis in these two families demonstrated that they shared the same disease haplotype, suggesting they have inherited the mutation from a common founder. The maximum LOD scores were 8.93 at θ=0 for D2S378 and 9.9 at θ=0 for D2S337 when the two families were combined for analysis. The disease interval for these two families was localized to 9.2 cM or 13.3 Mb between D2S123 and D2S2397. There are 42 known genes/transcripts within the interval. Five of these genes were sequenced, and no disease-causing mutation was identified in either family.
This novel juvenile-onset POAG locus on chromosome 2p15–16 is overlapped by the Glaucoma 1, open angle, H (GLC1H) locus for adult-onset POAG. Eventual identification of the disease-causing gene will provide insights into the pathogenesis of POAG.
PMCID: PMC2324117  PMID: 18432317
21.  Genetic correlates of longevity and selected age-related phenotypes: a genome-wide association study in the Framingham Study 
BMC Medical Genetics  2007;8(Suppl 1):S13.
Family studies and heritability estimates provide evidence for a genetic contribution to variation in the human life span.
We conducted a genome wide association study (Affymetrix 100K SNP GeneChip) for longevity-related traits in a community-based sample. We report on 5 longevity and aging traits in up to 1345 Framingham Study participants from 330 families. Multivariable-adjusted residuals were computed using appropriate models (Cox proportional hazards, logistic, or linear regression) and the residuals from these models were used to test for association with qualifying SNPs (70, 987 autosomal SNPs with genotypic call rate ≥80%, minor allele frequency ≥10%, Hardy-Weinberg test p ≥ 0.001).
In family-based association test (FBAT) models, 8 SNPs in two regions approximately 500 kb apart on chromosome 1 (physical positions 73,091,610 and 73, 527,652) were associated with age at death (p-value < 10-5). The two sets of SNPs were in high linkage disequilibrium (minimum r2 = 0.58). The top 30 SNPs for generalized estimating equation (GEE) tests of association with age at death included rs10507486 (p = 0.0001) and rs4943794 (p = 0.0002), SNPs intronic to FOXO1A, a gene implicated in lifespan extension in animal models. FBAT models identified 7 SNPs and GEE models identified 9 SNPs associated with both age at death and morbidity-free survival at age 65 including rs2374983 near PON1. In the analysis of selected candidate genes, SNP associations (FBAT or GEE p-value < 0.01) were identified for age at death in or near the following genes: FOXO1A, GAPDH, KL, LEPR, PON1, PSEN1, SOD2, and WRN. Top ranked SNP associations in the GEE model for age at natural menopause included rs6910534 (p = 0.00003) near FOXO3a and rs3751591 (p = 0.00006) in CYP19A1. Results of all longevity phenotype-genotype associations for all autosomal SNPs are web posted at .
Longevity and aging traits are associated with SNPs on the Affymetrix 100K GeneChip. None of the associations achieved genome-wide significance. These data generate hypotheses and serve as a resource for replication as more genes and biologic pathways are proposed as contributing to longevity and healthy aging.
PMCID: PMC1995604  PMID: 17903295
22.  Evidence for Three Loci Modifying Age-at-Onset of Alzheimer’s Disease in Early-Onset PSEN2 Families 
Families with early-onset Alzheimer’s disease (AD) sharing a single PSEN2 mutation exhibit a wide range of age-at-onset, suggesting that modifier loci segregate within these families. While APOE is known to be an age-at-onset modifier, it does not explain all of this variation. We performed a genome scan within nine such families for loci influencing age-at-onset, while simultaneously controlling for variation in the primary PSEN2 mutation (N141I) and APOE. We found significant evidence of linkage between age-at-onset and chromosome 1q23.3 (P < 0.001) when analysis included all families, and to chromosomes 1q23.3 (P < 0.001), 17p13.2 (P = 0.0002), 7q33 (P = 0.017), and 11p14.2 (P = 0.017) in a single large pedigree. Simultaneous analysis of these four chromosomes maintained strong evidence of linkage to chromosomes 1q23.3 and 17p13.2 when all families were analyzed, and to chromosomes 1q23.3, 7q33, and 17p13.2 within the same single pedigree. Inclusion of major gene covariates proved essential to detect these linkage signals, as all linkage signals dissipated when PSEN2 and APOE were excluded from the model. The four chromosomal regions with evidence of linkage all coincide with previous linkage signals, associated SNPs, and/or candidate genes identified in independent AD study populations. This study establishes several candidate regions for further analysis and is consistent with an oligogenic model of AD risk and age-at-onset. More generally, this study also demonstrates the value of searching for modifier loci in existing datasets previously used to identify primary causal variants for complex disease traits.
PMCID: PMC3022037  PMID: 20333730
genome-scan; modifier scan; quantitative trait; complex disease; dementia
23.  Genome scan for body mass index and height in the Framingham Heart Study 
BMC Genetics  2003;4(Suppl 1):S91.
Body mass index (BMI) and adult height are moderately and highly heritable traits, respectively. To investigate the genetic background of these quantitative phenotypes, we performed a linkage genome scan in the extended pedigrees of the Framingham Heart Study. Two variance-components approaches (SOLAR and MERLIN-VC) and one regression method (MERLIN-REGRESS) were applied to the data.
Evidence for linkage to BMI was found on chromosomes 16 and 6 with maximum LOD scores of 3.2 and 2.7, respectively. For height, all markers showing a LOD score greater than 1 in our analysis correspond to previously reported linkage regions, including chromosome 6q with a maximum LOD score of 2.45 and chromosomes 9, 12, 14, 18, and 22. Regarding the analysis, the three applied methods gave very similar results in this unselected sample with approximately normally distributed traits.
Our analysis resulted in the successful identification of linked regions. In particular, we consider the regions on chromosomes 6 and 16 for BMI and the regions on chromosomes 6, 9, and 12 for stature interesting for fine mapping and candidate gene studies.
PMCID: PMC1866532  PMID: 14975159
24.  Seed colour loci, homoeology and linkage groups of the C genome chromosomes revealed in Brassica rapa–B. oleracea monosomic alien addition lines 
Annals of Botany  2012;109(7):1227-1242.
Background and Aims
Brassica rapa and B. oleracea are the progenitors of oilseed rape B. napus. The addition of each chromosome of B. oleracea to the chromosome complement of B. rapa results in a series of monosomic alien addition lines (MAALs). Analysis of MAALs determines which B. oleracea chromosomes carry genes controlling specific phenotypic traits, such as seed colour. Yellow-seeded oilseed rape is a desirable breeding goal both for food and livestock feed end-uses that relate to oil, protein and fibre contents. The aims of this study included developing a missing MAAL to complement an available series, for studies on seed colour control, chromosome homoeology and assignment of linkage groups to B. oleracea chromosomes.
A new batch of B. rapa–B. oleracea aneuploids was produced to generate the missing MAAL. Seed colour and other plant morphological features relevant to differentiation of MAALs were recorded. For chromosome characterization, Snow's carmine, fluorescence in situ hybridization (FISH) and genomic in situ hybridization (GISH) were used.
Key Results
The final MAAL was developed. Morphological traits that differentiated the MAALs comprised cotyledon number, leaf morphology, flower colour and seed colour. Seed colour was controlled by major genes on two B. oleracea chromosomes and minor genes on five other chromosomes of this species. Homoeologous pairing was largely between chromosomes with similar centromeric positions. FISH, GISH and a parallel microsatellite marker analysis defined the chromosomes in terms of their linkage groups.
A complete set of MAALs is now available for genetic, genomic, evolutionary and breeding perspectives. Defining chromosomes that carry specific genes, physical localization of DNA markers and access to established genetic linkage maps contribute to the integration of these approaches, manifested in the confirmed correspondence of linkage groups with specific chromosomes. Applications include marker-assisted selection and breeding for yellow seeds.
PMCID: PMC3359914  PMID: 22628364
Brassica rapa var. trilocularis; B. oleracea var. alboglabra; MAALs; characterization of C chromosomes; plant morphology; seed colour control; FISH; GISH; chromosome homoeology; chromosome structural changes; linkage groups; crop plant breeding
25.  Genome-wide association studies for agronomical traits in a world wide spring barley collection 
BMC Plant Biology  2012;12:16.
Genome-wide association studies (GWAS) based on linkage disequilibrium (LD) provide a promising tool for the detection and fine mapping of quantitative trait loci (QTL) underlying complex agronomic traits. In this study we explored the genetic basis of variation for the traits heading date, plant height, thousand grain weight, starch content and crude protein content in a diverse collection of 224 spring barleys of worldwide origin. The whole panel was genotyped with a customized oligonucleotide pool assay containing 1536 SNPs using Illumina's GoldenGate technology resulting in 957 successful SNPs covering all chromosomes. The morphological trait "row type" (two-rowed spike vs. six-rowed spike) was used to confirm the high level of selectivity and sensitivity of the approach. This study describes the detection of QTL for the above mentioned agronomic traits by GWAS.
Population structure in the panel was investigated by various methods and six subgroups that are mainly based on their spike morphology and region of origin. We explored the patterns of linkage disequilibrium (LD) among the whole panel for all seven barley chromosomes. Average LD was observed to decay below a critical level (r2-value 0.2) within a map distance of 5-10 cM. Phenotypic variation within the panel was reasonably large for all the traits. The heritabilities calculated for each trait over multi-environment experiments ranged between 0.90-0.95. Different statistical models were tested to control spurious LD caused by population structure and to calculate the P-value of marker-trait associations. Using a mixed linear model with kinship for controlling spurious LD effects, we found a total of 171 significant marker trait associations, which delineate into 107 QTL regions. Across all traits these can be grouped into 57 novel QTL and 50 QTL that are congruent with previously mapped QTL positions.
Our results demonstrate that the described diverse barley panel can be efficiently used for GWAS of various quantitative traits, provided that population structure is appropriately taken into account. The observed significant marker trait associations provide a refined insight into the genetic architecture of important agronomic traits in barley. However, individual QTL account only for a small portion of phenotypic variation, which may be due to insufficient marker coverage and/or the elimination of rare alleles prior to analysis. The fact that the combined SNP effects fall short of explaining the complete phenotypic variance may support the hypothesis that the expression of a quantitative trait is caused by a large number of very small effects that escape detection. Notwithstanding these limitations, the integration of GWAS with biparental linkage mapping and an ever increasing body of genomic sequence information will facilitate the systematic isolation of agronomically important genes and subsequent analysis of their allelic diversity.
PMCID: PMC3349577  PMID: 22284310

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