Preterm birth (PTB) is a complex trait, but little is known regarding its major genetic determinants. The objective of this study is to localize genes that influence susceptibility to PTB in Mexican Americans (MAs), a minority population in the USA, using predominantly microfilmed birth certificate-based data obtained from the San Antonio Family Birth Weight Study. Only 1302 singleton births from 288 families with information on PTB and significant covariates were considered for genetic analysis. PTB is defined as a childbirth that occurs at <37 completed weeks of gestation, and the prevalence of PTB in this sample was 6.4%. An ∼10 cM genetic map was used to conduct a genome-wide linkage analysis using the program SOLAR. The heritability of PTB was high (h(2) ± SE: 0.75 ± 0.20) and significant (P = 4.5 × 10(-5)), after adjusting for the significant effects of birthweight and birth order. We found significant evidence for linkage of PTB (LOD = 3.6; nominal P = 2.3 × 10(-5); empirical P = 1.0 × 10(-5)) on chromosome 18q between markers D18S1364 and D18S541. Several other chromosomal regions (2q, 9p, 16q and 20q) were also potentially linked with PTB. A strong positional candidate gene in the 18q linked region is SERPINB2 or PAI-2, a member of the plasminogen activator system that is associated with various reproductive processes. In conclusion, to our knowledge, perhaps for the first time in MAs or US populations, we have localized a major susceptibility locus for PTB on chromosome 18q21.33-q23.
Publications
2013
BACKGROUND: A significant proportion of the variability in carotid artery lumen diameter is attributable to genetic factors.
METHODS: Carotid ultrasonography and genotyping were performed in the 3300 American Indian participants in the Strong Heart Family Study (SHFS) to identify chromosomal regions harboring novel genes associated with inter-individual variation in carotid artery lumen diameter. Genome-wide linkage analysis was conducted using standard variance component linkage methods, implemented in SOLAR, based on multipoint identity-by-descent matrices.
RESULTS: Genome-wide linkage analysis revealed a significant evidence for linkage for a locus for left carotid artery diastolic and systolic lumen diameters in Arizona SHFS participants on chromosome 7 at 120 cM (lod = 4.85 and 3.77, respectively, after sex and age adjustment, and lod = 3.12 and 2.72, respectively, after adjustment for sex, age, height, weight, systolic and diastolic blood pressure, diabetes mellitus and current smoking). Other regions with suggestive evidence of linkage for left carotid artery diastolic and systolic lumen diameter were found on chromosome 12 at 153 cM (lod = 2.20 and 2.60, respectively, after sex and age adjustment, and lod = 2.44 and 2.16, respectively, after full covariate adjustment) in Oklahoma SHFS participants; suggestive linkage for right carotid artery diastolic and systolic lumen diameter was found on chromosome 9 at 154 cM (lod = 2.72 and 3.19, respectively after sex and age adjustment, and lod = 2.36 and 2.21, respectively, after full covariate adjustment) in Oklahoma SHFS participants.
CONCLUSION: We found significant evidence for loci influencing carotid artery lumen diameter on chromosome 7q and suggestive linkage on chromosomes 12q and 9q.
Arsenic species patterns in urine are associated with risk for cancer and cardiovascular diseases. The organic anion transporter coded by the gene SLCO1B1 may transport arsenic species, but its association with arsenic metabolites in human urine has not yet been studied. The objective of this study is to evaluate associations of urine arsenic metabolites with variants in the candidate gene SLCO1B1 in adults from the Strong Heart Family Study. We estimated associations between % arsenic species biomarker traits and 5 single-nucleotide polymorphisms (SNPs) in the SLCO1B1 gene in 157 participants, assuming additive genetics. Linear regression models for each SNP accounted for kinships and were adjusted for sex, body mass index, and study center. The minor allele of rs1564370 was associated with lower %MMA (p = .0003) and higher %DMA (p = .0002), accounting for 8% of the variance for %MMA and 9% for %DMA. The rs1564370 minor allele homozygote frequency was 17% and the heterozygote frequency was 43%. The minor allele of rs2291075 was associated with lower %MMA (p = .0006) and higher %DMA (p = .0014), accounting for 7% of the variance for %MMA and 5% for %DMA. The frequency of rs2291075 minor allele homozygotes was 1% and of heterozygotes was 15%. Common variants in SLCO1B1 were associated with differences in arsenic metabolites in a preliminary candidate gene study. Replication of this finding in other populations and analyses with respect to disease outcomes are needed to determine whether this novel candidate gene is important for arsenic-associated disease risks.
This paper describes genetic investigations of seroreactivity to five common infectious pathogens in the Genetics of Coronary Artery Disease in Alaska Natives (GOCADAN) study. Antibody titers and seroprevalence were available for 495 to 782 (depending on the phenotype) family members at two time points, approximately 15 years apart, for Chlamydophila pneumoniae, Helicobacter pylori, cytomegalovirus (CMV), herpes simplex virus 1 (HSV-1), and herpes simplex virus 2 (HSV-2). Seroprevalence rates indicate that infections with most of these pathogens are common (≥20% for all of them, >80% for H. pylori, CMV, and HSV-1). Seropositive individuals typically remain seropositive over time, with seroreversion rates of <1% to 10% over ∼15 years. Antibody titers were significantly heritable for most pathogens, with the highest estimate being 0.61 for C. pneumoniae. Significant genome-wide linkage evidence was obtained for C. pneumoniae on chromosome 15 (logarithm of odds, LOD score of 3.13). These results demonstrate that individual host genetic differences influence antibody measures of common infections in this population, and further investigation may elucidate the underlying immunological processes and genes involved.
INTRODUCTION: We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging.
METHODS: Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 μm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability.
RESULTS: Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT.
CONCLUSION: Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.
Genome-wide association studies (GWAS) have identified many variants that influence high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and/or triglycerides. However, environmental modifiers, such as smoking, of these known genotype-phenotype associations are just recently emerging in the literature. We have tested for interactions between smoking and 49 GWAS-identified variants in over 41,000 racially/ethnically diverse samples with lipid levels from the Population Architecture Using Genomics and Epidemiology (PAGE) study. Despite their biological plausibility, we were unable to detect significant SNP × smoking interactions.
Increased serum uric acid (SUA) is a risk factor for gout and renal and cardiovascular disease (CVD). The purpose of this study was to identify genetic factors that affect the variation in SUA in 632 Mexican Americans participants of the San Antonio Family Heart Study (SAFHS). A genome-wide association (GWA) analysis was performed using the Illumina Human Hap 550K single nucleotide polymorphism (SNP) microarray. We used a linear regression-based association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. All analyses were performed in the software package SOLAR. SNPs rs6832439, rs13131257, and rs737267 in solute carrier protein 2 family, member 9 (SLC2A9) were associated with SUA at genome-wide significance (p < 1.3 × 10(-7)). The minor alleles of these SNPs had frequencies of 36.2, 36.2, and 38.2%, respectively, and were associated with decreasing SUA levels. All of these SNPs were located in introns 3-7 of SLC2A9, the location of the previously reported associations in European populations. When analyzed for association with cardiovascular-renal disease risk factors, conditional on SLC2A9 SNPs strongly associated with SUA, significant associations were found for SLC2A9 SNPs with BMI, body weight, and waist circumference (p < 1.4 × 10(-3)) and suggestive associations with albumin-creatinine ratio and total antioxidant status (TAS). The SLC2A9 gene encodes an urate transporter that has considerable influence on variation in SUA. In addition to the primary association locus, suggestive evidence (p < 1.9 × 10(-6)) for joint linkage/association (JLA) was found at a previously-reported urate quantitative trait locus (Logarithm of odds score = 3.6) on 3p26.3. In summary, our GWAS extends and confirms the association of SLC2A9 with SUA for the first time in a Mexican American cohort and also shows for the first time its association with cardiovascular-renal disease risk factors.
2012
Quantitative ultrasound (QUS) traits are correlated with bone mineral density (BMD), but predict risk for future fracture independent of BMD. Only a few studies, however, have sought to identify specific genes influencing calcaneal QUS measures. The aim of this study was to conduct a genome-wide linkage scan to identify quantitative trait loci (QTL) influencing normal variation in QUS traits. QUS measures were collected from a total of 719 individuals (336 males and 383 females) from the Fels Longitudinal Study who have been genotyped and have at least one set of QUS measurements. Participants ranged in age from 18.0 to 96.6 years and were distributed across 110 nuclear and extended families. Using the Sahara ® bone sonometer, broadband ultrasound attenuation (BUA), speed of sound (SOS) and stiffness index (QUI) were collected from the right heel. Variance components based linkage analysis was performed on the three traits using 400 polymorphic short tandem repeat (STR) markers spaced approximately 10 cM apart across the autosomes to identify QTL influencing the QUS traits. Age, sex, and other significant covariates were simultaneously adjusted. Heritability estimates (h²) for the QUS traits ranged from 0.42 to 0.57. Significant evidence for a QTL influencing BUA was found on chromosome 11p15 near marker D11S902 (LOD = 3.11). Our results provide additional evidence for a QTL on chromosome 11p that harbors a potential candidate gene(s) related to BUA and bone metabolism.
A theory of aging holds that senescence is caused by a dysregulated nuclear factor kappa B (NF-κB) signal transduction network (STN). We adopted a systems genetics approach in our study of the NF-κB STN. Ingenuity Pathways Analysis (IPA) was used to identify gene/gene product interactions between NF-κB and the genes in our transcriptional profiling array. Principal components factor analysis (PCFA) was performed on a sub-network of 19 genes, including two initiators of the toll-like receptor (TLR) pathway, myeloid differentiation primary response gene (88) (MyD88) and TIR (Toll/interleukin-1 receptor)-domain-containing adapter-inducing interferon-β (TRIF). TLR pathways are either MyD88-dependent or TRIF-dependent. Therefore, we also performed PCFA on a subset excluding the MyD88 transcript, and on another subset excluding two TRIF transcripts. Using linkage analysis we found that each set gave rise to at least one factor with a logarithm of the odds (LOD) score greater than 3, two on chromosome 15 at 15q12 and 15q22.2, and another two on chromosome 17 at 17p13.3 and 17q25.3. We also found several suggestive signals (2<LOD score<3) at 1q32.1, 1q41, 2q34, 3q23, and 7p15.3. We are currently examining potential associations with single nucleotide polymorphisms within the 1-LOD intervals of our linkage signals.
BACKGROUND: Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance.
METHODS: We searched PubMed to identify genome linkage analyses of renal function traits in humans, such as estimated glomerular filtration rate (GFR), albuminuria, serum creatinine concentration and creatinine clearance. We contacted authors for numerical data and extracted information from individual studies. We applied the GSMA nonparametric approach to combine results across 14 linkage studies for GFR, 11 linkage studies for albumin creatinine ratio, 11 linkage studies for serum creatinine and 4 linkage studies for creatinine clearance.
RESULTS: No chromosomal region reached genome-wide statistical significance in the main analysis which included all scans under each phenotype; however, regions on Chromosomes 7, 10 and 16 reached suggestive significance for linkage to two or more phenotypes. Subgroup analyses by disease status or ethnicity did not yield additional information.
CONCLUSIONS: While heterogeneity across populations, methodologies and study designs likely explain this lack of agreement, it is possible that linkage scan methodologies lack the resolution for investigating complex traits. Combining family-based linkage studies with genome-wide association studies may be a powerful approach to detect private mutations contributing to complex renal phenotypes.