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Genome-wide association studies have identified numerous variants associated with lipid levels; yet, the majority are located in non-coding regions with unclear mechanisms. In the Insulin Resistance Atherosclerosis Family Study (IRASFS), heritability estimates suggest a strong genetic basis: low-density lipoprotein (LDL, h = 0.50), high-density lipoprotein (HDL, h = 0.57), total cholesterol (TC, h = 0.53), and triglyceride (TG, h = 0.42) levels. Exome sequencing of 1,205 Mexican Americans (90 pedigrees) from the IRASFS identified 548,889 variants and association and linkage analyses with lipid levels were performed. One genome-wide significant signal was detected in APOA5 with TG (rs651821, P = 3.67 × 10, LOD = 2.36, MAF = 14.2%). In addition, two correlated SNPs (r = 1.0) rs189547099 (P = 6.31 × 10, LOD = 3.13, MAF = 0.50%) and chr4:157997598 (P = 6.31 × 10, LOD = 3.13, MAF = 0.50%) reached exome-wide significance (P < 9.11 × 10). rs189547099 is an intronic SNP in FNIP2 and SNP chr4:157997598 is intronic in GLRB. Linkage analysis revealed 46 SNPs with a LOD > 3 with the strongest signal at rs1141070 (LOD = 4.30, P = 0.33, MAF = 21.6%) in DFFB. A total of 53 nominally associated variants (P < 5.00 × 10, MAF ≥ 1.0%) were selected for replication in six Mexican-American cohorts (N = 3,280). The strongest signal observed was a synonymous variant (rs1160983, P = 4.44 × 10, MAF = 2.7%) in TOMM40. Beyond primary findings, previously reported lipid loci were fine-mapped using exome sequencing in IRASFS. These results support that exome sequencing complements and extends insights into the genetics of lipid levels.
Dopamine function is broadly implicated in multiple neuropsychiatric conditions believed to have a genetic basis. Although a few positron emission tomography (PET) studies have investigated the impact of single-nucleotide polymorphisms (SNPs) in the dopamine D2 receptor gene (DRD2) on D2/3 receptor availability (binding potential, BP), these studies have often been limited by small sample size. Furthermore, the most commonly studied SNP in D2/3 BP (Taq1A) is not located in the DRD2 gene itself, suggesting that its linkage with other DRD2 SNPs may explain previous PET findings. Here, in the largest PET genetic study to date (n=84), we tested for effects of the C957T and -141C Ins/Del SNPs (located within DRD2) as well as Taq1A on BP of the high-affinity D2 receptor tracer F-Fallypride. In a whole-brain voxelwise analysis, we found a positive linear effect of C957T T allele status on striatal BP bilaterally. The multilocus genetic scores containing C957T and one or both of the other SNPs produced qualitatively similar striatal results to C957T alone. The number of C957T T alleles predicted BP in anatomically defined putamen and ventral striatum (but not caudate) regions of interest, suggesting some regional specificity of effects in the striatum. By contrast, no significant effects arose in cortical regions. Taken together, our data support the critical role of C957T in striatal D2/3 receptor availability. This work has implications for a number of psychiatric conditions in which dopamine signaling and variation in C957T status have been implicated, including schizophrenia and substance use disorders.
Many large genome-wide association studies (GWAS) have identified common blood pressure (BP) variants. However, most of the identified BP variants do not overlap with the linkage evidence observed from family studies. We thus hypothesize that multiple rare variants contribute to the observed linkage evidence. We performed linkage analysis using 517 individuals in 130 European families from the Cleveland Family Study (CFS) who have been genotyped on the Illumina OmniExpress Exome array. The largest linkage peak was observed on chromosome 16p13 (MLOD = 2.81) for systolic blood pressure (SBP). Follow-up conditional linkage and association analyses in the linkage region identified multiple rare, coding variants in RBFOX1 associated with reduced SBP. In a 17-member CFS family, carriers of the missense variant rs149974858 are normotensive despite being obese (average BMI = 60 kg/m2). Gene-based association test of rare variants using SKAT-O showed significant association with SBP (p-value = 0.00403) and DBP (p-value = 0.0258) in the CFS participants and the association was replicated in large independent replication studies (N = 57,234, p-value = 0.013 for SBP, 0.0023 for PP). RBFOX1 is expressed in brain tissues, the atrial appendage and left ventricle in the heart, and in skeletal muscle tissues, organs/tissues which are potentially related to blood pressure. Our study showed that associations of rare variants could be efficiently detected using family information.
Closely spaced clusters of tandemly duplicated genes (CTDGs) contribute to the diversity of many phenotypes, including chemosensation, snake venom, and animal body plans. CTDGs have traditionally been identified subjectively as genomic neighborhoods containing several gene duplicates in close proximity; however, CTDGs are often highly variable with respect to gene number, intergenic distance, and synteny. This lack of formal definition hampers the study of CTDG evolutionary dynamics and the discovery of novel CTDGs in the exponentially growing body of genomic data. To address this gap, we developed a novel homology-based algorithm, CTDGFinder, which formalizes and automates the identification of CTDGs by examining the physical distribution of individual members of families of duplicated genes across chromosomes. Application of CTDGFinder accurately identified CTDGs for many well-known gene clusters (e.g., Hox and beta-globin gene clusters) in the human, mouse and 20 other mammalian genomes. Differences between previously annotated gene clusters and our inferred CTDGs were due to the exclusion of nonhomologs that have historically been considered parts of specific gene clusters, the inclusion or absence of genes between the CTDGs and their corresponding gene clusters, and the splitting of certain gene clusters into distinct CTDGs. Examination of human genes showing tissue-specific enhancement of their expression by CTDGFinder identified members of several well-known gene clusters (e.g., cytochrome P450s and olfactory receptors) and revealed that they were unequally distributed across tissues. By formalizing and automating CTDG identification, CTDGFinder will facilitate understanding of CTDG evolutionary dynamics, their functional implications, and how they are associated with phenotypic diversity.
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Linkage studies of complex genetic diseases have been largely replaced by genome-wide association studies, due in part to limited success in complex trait discovery. However, recent interest in rare and low-frequency variants motivates re-examination of family-based methods. In this study, we investigated the performance of two-point linkage analysis for over 1.6 million single-nucleotide polymorphisms (SNPs) combined with single variant association analysis to identify high impact variants, which are both strongly linked and associated with cardiometabolic traits in up to 1414 Hispanics from the Insulin Resistance Atherosclerosis Family Study (IRASFS). Evaluation of all 50 phenotypes yielded 83 557 000 LOD (logarithm of the odds) scores, with 9214 LOD scores ⩾3.0, 845 ⩾4.0 and 89 ⩾5.0, with a maximal LOD score of 6.49 (rs12956744 in the LAMA1 gene for tumor necrosis factor-α (TNFα) receptor 2). Twenty-seven variants were associated with P<0.005 as well as having an LOD score >4, including variants in the NFIB gene under a linkage peak with TNFα receptor 2 levels on chromosome 9. Linkage regions of interest included a broad peak (31 Mb) on chromosome 1q with acute insulin response (max LOD=5.37). This region was previously documented with type 2 diabetes in family-based studies, providing support for the validity of these results. Overall, we have demonstrated the utility of two-point linkage and association in comprehensive genome-wide array-based SNP genotypes.
It has been suggested that pharmacogenomic phenotypes are influenced by genetic variants with larger effect sizes than other phenotypes, such as complex disease risk. This is presumed to reflect the fact that relevant environmental factors (drug exposure) are appropriately measured and taken into account. To test this hypothesis, we performed a systematic comparison of effect sizes between pharmacogenomic and non-pharmacogenomic phenotypes across all genome-wide association studies (GWAS) reported in the NHGRI GWAS catalog. We found significantly larger effect sizes for studies focused on pharmacogenomic phenotypes, as compared with complex disease risk, morphological phenotypes and endophenotypes. We found no significant differences in effect sizes between pharmacogenomic studies focused on adverse events versus those focused on drug efficacy. Furthermore, we found that this pattern persists among sample size-matched studies, suggesting that this pattern does not reflect overestimation of effect sizes due to smaller sample sizes in pharmacogenomic studies.The Pharmacogenomics Journal advance online publication, 7 July 2015; doi:10.1038/tpj.2015.47.
Although there is considerable evidence that individual differences in language development are highly heritable, there have been few genome-wide scans to locate genes associated with the trait. Previous analyses of language impairment have yielded replicable evidence for linkage to regions on chromosomes 16q, 19q, 13q (within lab) and at 13q (between labs). Here we report the first linkage study to screen the continuum of language ability, from normal to disordered, as found in the general population. 383 children from 147 sib-ships (214 sib-pairs) were genotyped on the Illumina(®) Linkage IVb Marker Panel using three composite language-related phenotypes and a measure of phonological memory (PM). Two regions (10q23.33; 13q33.3) yielded genome-wide significant peaks for linkage with PM. A peak suggestive of linkage was also found at 17q12 for the overall language composite. This study presents two novel genetic loci for the study of language development and disorders, but fails to replicate findings by previous groups. Possible reasons for this are discussed.
© 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
Whole human genome sequencing of individuals is becoming rapid and inexpensive, enabling new strategies for using personal genome information to help diagnose, treat, and even prevent human disorders for which genetic variations are causative or are known to be risk factors. Many of the exploding number of newly discovered genetic variations alter the structure, function, dynamics, stability, and/or interactions of specific proteins and RNA molecules. Accordingly, there are a host of opportunities for biochemists and biophysicists to participate in (1) developing tools to allow accurate and sometimes medically actionable assessment of the potential pathogenicity of individual variations and (2) establishing the mechanistic linkage between pathogenic variations and their physiological consequences, providing a rational basis for treatment or preventive care. In this review, we provide an overview of these opportunities and their associated challenges in light of the current status of genomic science and personalized medicine, the latter often termed precision medicine.
Reduced metabolic efficiency, toxic intermediate accumulation, and deficits of molecular building blocks, which all stem from disruptions of flux through metabolic pathways, reduce organismal fitness. Although these represent shared selection pressures across organisms, the genetic signatures of the responses to them may differ. In fungi, a frequently observed signature is the physical linkage of genes from the same metabolic pathway. In contrast, human metabolic genes are rarely tightly linked; rather, they tend to show tissue-specific coexpression. We hypothesized that the physical linkage of fungal metabolic genes and the tissue-specific coexpression of human metabolic genes are divergent yet analogous responses to the range of selective pressures imposed by disruptions of flux. To test this, we examined the degree to which the human homologs of physically linked metabolic genes in fungi (fungal linked homologs or FLOs) are coexpressed across six human tissues. We found that FLOs are significantly more correlated in their expression profiles across human tissues than other metabolic genes. We obtained similar results in analyses of the same six tissues from chimps, gorillas, orangutans, and macaques. We suggest that when selective pressures remain stable across large evolutionary distances, evidence of selection in a given evolutionary lineage can become a highly reliable predictor of the signature of selection in another, even though the specific adaptive response in each lineage is markedly different.
© The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: email@example.com.
We previously identified a low-frequency (1.1 %) coding variant (G45R; rs200573126) in the adiponectin gene (ADIPOQ) which was the basis for a multipoint microsatellite linkage signal (LOD = 8.2) for plasma adiponectin levels in Hispanic families. We have empirically evaluated the ability of data from targeted common variants, exome chip genotyping, and genome-wide association study data to detect linkage and association to adiponectin protein levels at this locus. Simple two-point linkage and association analyses were performed in 88 Hispanic families (1,150 individuals) using 10,958 SNPs on chromosome 3. Approaches were compared for their ability to map the functional variant, G45R, which was strongly linked (two-point LOD = 20.98) and powerfully associated (p value = 8.1 × 10(-50)). Over 450 SNPs within a broad 61 Mb interval around rs200573126 showed nominal evidence of linkage (LOD > 3) but only four other SNPs in this region were associated with p values < 1.0 × 10(-4). When G45R was accounted for, the maximum LOD score across the interval dropped to 4.39 and the best p value was 1.1 × 10(-5). Linked and/or associated variants ranged in frequency (0.0018-0.50) and type (coding, non-coding) and had little detectable linkage disequilibrium with rs200573126 (r (2) < 0.20). In addition, the two-point linkage approach empirically outperformed multipoint microsatellite and multipoint SNP analysis. In the absence of data for rs200573126, family-based linkage analysis using a moderately dense SNP dataset, including both common and low-frequency variants, resulted in stronger evidence for an adiponectin locus than association data alone. Thus, linkage analysis can be a useful tool to facilitate identification of high-impact genetic variants.