Extent and distribution of linkage disequilibrium in the Old Order Amish

Knowledge of the extent and distribution of linkage disequilibrium (LD) is critical to the design and interpretation of gene mapping studies. Because the demographic history of each population varies and is often not accurately known, it is necessary to empirically evaluate LD on a population-specific basis. Here we present the first genome-wide survey of LD in the Old Order Amish (OOA) of Lancaster County Pennsylvania, a closed population derived from a modest number of founders. Specifically, we present a comparison of LD between OOA individuals and US Utah participants in the International HapMap project (abbreviated CEU) using a high-density single nucleotide polymorphism (SNP) map. Overall, the allele (and haplotype) frequency distributions and LD profiles were remarkably similar between these two populations. For example, the median absolute allele frequency difference for autosomal SNPs was 0.05, with an inter-quartile range of 0.02–0.09, and for autosomal SNPs 10–20 kb apart with common alleles (minor allele frequency≥0.05), the LD measure r 2 was at least 0.8 for 15 and 14% of SNP pairs in the OOA and CEU, respectively. Moreover, tag SNPs selected from the HapMap CEU sample captured a substantial portion of the common variation in the OOA (∼88%) at r 2 ≥0.8. These results suggest that the OOA and CEU may share similar LD profiles for other common but untyped SNPs. Thus, in the context of the common variant-common disease hypothesis, genetic variants discovered in gene mapping studies in the OOA may generalize to other populations. Genet. Epidemiol . 34: 146–150, 2010. © 2009 Wiley-Liss, Inc.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/64895/1/20444_ftp.pd

Cardiac performance, biomarkers and gene expression studies in previously sedentary men participating in half-marathon training

BACKGROUND: The mechanisms through which exercise reduces cardiovascular disease are not fully understood. We used echocardiograms, cardiac biomarkers and gene expression to investigate cardiovascular effects associated with exercise training. METHODS: Nineteen sedentary men (22-37 years) completed a 17-week half-marathon training program. Serial measurements of resting heart rate, blood pressure, maximum oxygen consumption, lipids, C-reactive protein, cardiac troponin T, echocardiograms and blood for gene expression were obtained from baseline to peak training. Controls included 22 sedentary men who did not exercise. RESULTS: Among the training group, VO2 max increased from 37.1 to 42.0 ml/kg/min (p \u3c 0.001). Significant changes were seen in left ventricular wall thickness and mass, stroke volume, resting heart rate and blood pressure (p \u3c 0.001). The control group demonstrated no significant changes. Expression profiling in the training group identified 10 significantly over-expressed and 53 significantly under-expressed loci involved in inflammatory pathways. Dividing the training group into high and low responders based on percent change in VO2 max identified loci that differentiated these two groups at baseline and after training. CONCLUSION: Intensive exercise training leads to significant increase in cardiac and hemodynamic performance, and significant changes in expression of genes involved in immune and inflammatory response.

Temporal course of cognitive and behavioural changes in motor neuron diseases

Background Cognitive and behavioural dysfunction may occur in people with motor neuron disease (MND), with some studies suggesting an association with the C9ORF72 repeat expansion. Their onset and progression, however, is poorly understood. We explored how cognition and behaviour change over time, and whether demographic, clinical and genetic factors impact these changes. Methods Participants with MND were recruited through the Phenotype-Genotype-Biomarker study. Every 3–6 months, the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) was used to assess amyotrophic lateral sclerosis (ALS) specific (executive functioning, verbal fluency, language) and ALS non-specific (memory, visuospatial) functions. Informants reported on behaviour symptoms via semi-structured interview. Results Participants with neuropsychological data at ≥3 visits were included (n=237, mean age=59, 60% male), of which 18 (8%) were C9ORF72 positive. Baseline cognitive impairment was apparent in 18 (8%), typically in ALS specific domains, and associated with lower education, but not C9ORF72 status. Cognition, on average, remained stable over time, with two exceptions: (1) C9ORF72 carriers declined in all ECAS domains, (2) 8%–9% of participants with baseline cognitive impairment further declined, primarily in the ALS non-specific domain, which was associated with less education. Behavioural symptoms were uncommon. Conclusions In this study, cognitive dysfunction was less common than previously reported and remained stable over time for most. However, cognition declines longitudinally in a small subset, which is not entirely related to C9ORF72 status. Our findings raise questions about the timing of cognitive impairment in MND, and whether it arises during early clinically manifest disease or even prior to motor manifestations

Adjusting for covariates on a slippery slope: linkage analysis of change over time

BACKGROUND: We analyzed the Genetic Analysis Workshop 13 (GAW13) simulated data to contrast and compare different methods for the genetic linkage analysis of hypertension and change in blood pressure over time. We also examined methods for incorporating covariates into the linkage analysis. We used methods for quantitative trait loci (QTL) linkage analysis with and without covariates and affected sib-pair (ASP) analysis of hypertension followed by ordered subset analysis (OSA), using variables associated with change in blood pressure over time. RESULTS: Four of the five baseline genes and one of the three slope genes were not detected by any method using conventional criteria. OSA detected baseline gene b35 on chromosome 13 when using the slope in blood pressure to adjust for change over time. Slope gene s10 was detected by the ASP analysis and slope gene s11 was detected by QTL linkage analysis as well as by OSA analysis. Analysis of null chromosomes, i.e., chromosomes without genes, did not reveal significant increases in type I error. However, there were a number of genes indirectly related to blood pressure detected by a variety of methods. CONCLUSIONS: We noted that there is no obvious first choice of analysis software for analyzing a complicated model, such as the one underlying the GAW13 simulated data. Inclusion of covariates and longitudinal data can improve localization of genes for complex traits but it is not always clear how best to do this. It remains a worthwhile task to apply several different approaches since one method is not always the best

Gene-environment interactions and obesity traits among postmenopausal African-American and Hispanic women in the Women’s Health Initiative SHARe Study

Genome-wide association studies of obesity measures have identified associations with single nucleotide polymorphisms (SNPs). However, no large-scale evaluation of gene-environment interactions has been performed. We conducted a search of gene-environment (G×E) interactions in post-menopausal African-American and Hispanic women from the Women’s Health Initiative SNP Health Association Resource GWAS study. Single SNP linear regression on body mass index (BMI) and waist-to-hip circumference ratio (WHR) adjusted for multidimensional-scaling-derived axes of ancestry and age was run in race-stratified data with 871,512 SNPs available from African-Americans (N=8,203) and 786,776 SNPs from Hispanics (N=3,484). Tests of G×E interaction at all SNPs for recreational physical activity (met-hrs/wk), dietary energy intake (kcal/day), alcohol intake (categorical), cigarette smoking years, and cigarette smoking (ever vs. never) were run in African-Americans and Hispanics adjusted for ancestry and age at interview, followed by meta-analysis of G×E interaction terms. The strongest evidence for concordant G×E interactions in African-Americans and Hispanics was for smoking and marker rs10133840 (Q statistic P=0.70, beta=−0.01, P=3.81×10−7) with BMI as the outcome. The strongest evidence for G×E interaction within a cohort was in African-Americans with WHR as outcome for dietary energy intake and rs9557704 (SNP×kcal =−0.04, P=2.17×10−7). No results exceeded the Bonferroni–corrected statistical significance threshold

High Density SNP Screen in A Large Multiplex Neural Tube Defect Family Refines Linkage to Loci at 7p21-Pter And 2q33.1-35

Neural tube defects (NTDs) are considered complex with both genetic and environmental factors implicated. To date, no major causative genes have been identified in humans despite several investigations. The first genomewide screen in NTDs (Rampersaud et al. 2005) demonstrated evidence of linkage to chromosomes 7 and 10. This screen included forty-four multiplex families and consisted of 402 microsatellite markers spaced approximately 10 cM apart. Further investigation of the genomic screen data identified a single large multiplex family, pedigree 8776, as primarily driving the linkage results on chromosome 7

XAF1 as a modifier of p53 function and cancer susceptibility

Cancer risk is highly variable in carriers of the common TP53-R337H founder allele, possibly due to the influence of modifier genes. Whole-genome sequencing identified a variant in the tumor suppressor XAF1 (E134*/Glu134Ter/rs146752602) in a subset of R337H carriers. Haplotype-defining variants were verified in 203 patients with cancer, 582 relatives, and 42,438 newborns. The compound mutant haplotype was enriched in patients with cancer, conferring risk for sarcoma (P = 0.003) and subsequent malignancies (P = 0.006). Functional analyses demonstrated that wild-type XAF1 enhances transactivation of wild-type and hypomorphic TP53 variants, whereas XAF1-E134* is markedly attenuated in this activity. We propose that cosegregation of XAF1-E134* and TP53-R337H mutations leads to a more aggressive cancer phenotype than TP53-R337H alone, with implications for genetic counseling and clinical management of hypomorphic TP53 mutant carriers.Fil: Pinto, Emilia M.. St. Jude Children's Research Hospital; Estados UnidosFil: Figueiredo, Bonald C.. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Chen, Wenan. St. Jude Children's Research Hospital; Estados UnidosFil: Galvao, Henrique C.R.. Hospital de Câncer de Barretos; BrasilFil: Formiga, Maria Nirvana. A.c.camargo Cancer Center; BrasilFil: Fragoso, Maria Candida B.V.. Universidade de Sao Paulo; BrasilFil: Ashton Prolla, Patricia. Universidade Federal do Rio Grande do Sul; BrasilFil: Ribeiro, Enilze M.S.F.. Universidade Federal do Paraná; BrasilFil: Felix, Gabriela. Universidade Federal da Bahia; BrasilFil: Costa, Tatiana E.B.. Hospital Infantil Joana de Gusmao; BrasilFil: Savage, Sharon A.. National Cancer Institute; Estados UnidosFil: Yeager, Meredith. National Cancer Institute; Estados UnidosFil: Palmero, Edenir I.. Hospital de Câncer de Barretos; BrasilFil: Volc, Sahlua. Hospital de Câncer de Barretos; BrasilFil: Salvador, Hector. Hospital Sant Joan de Deu Barcelona; EspañaFil: Fuster Soler, Jose Luis. Hospital Clínico Universitario Virgen de la Arrixaca; EspañaFil: Lavarino, Cinzia. Hospital Sant Joan de Deu Barcelona; EspañaFil: Chantada, Guillermo Luis. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. St. Jude Children's Research Hospital; Estados UnidosFil: Vaur, Dominique. Comprehensive Cancer Center François Baclesse; FranciaFil: Odone Filho, Vicente. Universidade de Sao Paulo; BrasilFil: Brugières, Laurence. Institut de Cancerologie Gustave Roussy; FranciaFil: Else, Tobias. University of Michigan; Estados UnidosFil: Stoffel, Elena M.. University of Michigan; Estados UnidosFil: Maxwell, Kara N.. University of Pennsylvania; Estados UnidosFil: Achatz, Maria Isabel. Hospital Sirio-libanês; BrasilFil: Kowalski, Luis. A.c.camargo Cancer Center; BrasilFil: De Andrade, Kelvin C.. National Cancer Institute; Estados UnidosFil: Pappo, Alberto. St. Jude Children's Research Hospital; Estados UnidosFil: Letouze, Eric. Centre de Recherche Des Cordeliers; FranciaFil: Latronico, Ana Claudia. Universidade de Sao Paulo; BrasilFil: Mendonca, Berenice B.. Universidade de Sao Paulo; BrasilFil: Almeida, Madson Q.. Universidade de Sao Paulo; BrasilFil: Brondani, Vania B.. Universidade de Sao Paulo; BrasilFil: Bittar, Camila M.. Universidade Federal do Rio Grande do Sul; BrasilFil: Soares, Emerson W.S.. Hospital Do Câncer de Cascavel; BrasilFil: Mathias, Carolina. Universidade Federal do Paraná; BrasilFil: Ramos, Cintia R.N.. Hospital de Câncer de Barretos; BrasilFil: Machado, Moara. National Cancer Institute; Estados UnidosFil: Zhou, Weiyin. National Cancer Institute; Estados UnidosFil: Jones, Kristine. National Cancer Institute; Estados UnidosFil: Vogt, Aurelie. National Cancer Institute; Estados UnidosFil: Klincha, Payal P.. National Cancer Institute; Estados UnidosFil: Santiago, Karina M.. A.c.camargo Cancer Center; BrasilFil: Komechen, Heloisa. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Paraizo, Mariana M.. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Parise, Ivy Z.S.. Instituto de Pesquisa Pelé Pequeno Principe; BrasilFil: Hamilton, Kayla V.. St. Jude Children's Research Hospital; Estados UnidosFil: Wang, Jinling. St. Jude Children's Research Hospital; Estados UnidosFil: Rampersaud, Evadnie. St. Jude Children's Research Hospital; Estados UnidosFil: Clay, Michael R.. St. Jude Children's Research Hospital; Estados UnidosFil: Murphy, Andrew J.. St. Jude Children's Research Hospital; Estados UnidosFil: Lalli, Enzo. Institut de Pharmacologie Moléculaire et Cellulaire; FranciaFil: Nichols, Kim E.. St. Jude Children's Research Hospital; Estados UnidosFil: Ribeiro, Raul C.. St. Jude Children's Research Hospital; Estados UnidosFil: Rodriguez-Galindo, Carlos. St. Jude Children's Research Hospital; Estados UnidosFil: Korbonits, Marta. Queen Mary University of London; Reino UnidoFil: Zhang, Jinghui. St. Jude Children's Research Hospital; Estados UnidosFil: Thomas, Mark G.. Colegio Universitario de Londres; Reino UnidoFil: Connelly, Jon P.. St. Jude Children's Research Hospital; Estados UnidosFil: Pruett-Miller, Shondra. St. Jude Children's Research Hospital; Estados UnidosFil: Diekmann, Yoan. Colegio Universitario de Londres; Reino UnidoFil: Neale, Geoffrey. St. Jude Children's Research Hospital; Estados UnidosFil: Wu, Gang. St. Jude Children's Research Hospital; Estados UnidosFil: Zambetti, Gerard P.. St. Jude Children's Research Hospital; Estados Unido

Genome-Wide Association of Body Fat Distribution in African Ancestry Populations Suggests New Loci

Central obesity, measured by waist circumference (WC) or waist-hip ratio (WHR), is a marker of body fat distribution. Although obesity disproportionately affects minority populations, few studies have conducted genome-wide association study (GWAS) of fat distribution among those of predominantly African ancestry (AA). We performed GWAS of WC and WHR, adjusted and unadjusted for BMI, in up to 33,591 and 27,350 AA individuals, respectively. We identified loci associated with fat distribution in AA individuals using meta-analyses of GWA results for WC and WHR (stage 1). Overall, 25 SNPs with single genomic control (GC)-corrected p-values<5.0×10−6 were followed-up (stage 2) in AA with WC and with WHR. Additionally, we interrogated genomic regions of previously identified European ancestry (EA) WHR loci among AA. In joint analysis of association results including both Stage 1 and 2 cohorts, 2 SNPs demonstrated association, rs2075064 at LHX2, p = 2.24×10−8 for WC-adjusted-for-BMI, and rs6931262 at RREB1, p = 2.48×10−8 for WHR-adjusted-for-BMI. However, neither signal was genome-wide significant after double GC-correction (LHX2: p = 6.5×10−8; RREB1: p = 5.7×10−8). Six of fourteen previously reported loci for waist in EA populations were significant (p<0.05 divided by the number of independent SNPs within the region) in AA studied here (TBX15-WARS2, GRB14, ADAMTS9, LY86, RSPO3, ITPR2-SSPN). Further, we observed associations with metabolic traits: rs13389219 at GRB14 associated with HDL-cholesterol, triglycerides, and fasting insulin, and rs13060013 at ADAMTS9 with HDL-cholesterol and fasting insulin. Finally, we observed nominal evidence for sexual dimorphism, with stronger results in AA women at the GRB14 locus (p for interaction = 0.02). In conclusion, we identified two suggestive loci associated with fat distribution in AA populations in addition to confirming 6 loci previously identified in populations of EA. These findings reinforce the concept that there are fat distribution loci that are independent of generalized adiposity

Genome-wide Analyses Identify KIF5A as a Novel ALS Gene

To identify novel genes associated with ALS, we undertook two lines of investigation. We carried out a genome-wide association study comparing 20,806 ALS cases and 59,804 controls. Independently, we performed a rare variant burden analysis comparing 1,138 index familial ALS cases and 19,494 controls. Through both approaches, we identified kinesin family member 5A (KIF5A) as a novel gene associated with ALS. Interestingly, mutations predominantly in the N-terminal motor domain of KIF5A are causative for two neurodegenerative diseases: hereditary spastic paraplegia (SPG10) and Charcot-Marie-Tooth type 2 (CMT2). In contrast, ALS-associated mutations are primarily located at the C-terminal cargo-binding tail domain and patients harboring loss-of-function mutations displayed an extended survival relative to typical ALS cases. Taken together, these results broaden the phenotype spectrum resulting from mutations in KIF5A and strengthen the role of cytoskeletal defects in the pathogenesis of ALS.Peer reviewe