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Biomedical subjects

Sarah Bertelsen

Publications and source records attributed to Sarah Bertelsen.

11 recordsLinked to original sources

Association of CHRM2 with IQ: converging evidence for a gene influencing intelligence.

The cholinergic neurotransmitter system is thought to be involved in many aspects of memory, attention, and higher cognition. In the Collaborative Study on the Genetics of Alcoholism (COGA) sample, we have previously reported linkage and association to the cholinergic muscarinic 2 receptor gene (CHRM2) on chromosome 7 with evoked EEG oscillations (Jones et al. 2004), providing evidence that this gene may be involved in human brain dynamics and cognition. In addition, a small number of genetic markers were genotyped in CHRM2 in the Minnesota Twin and Family Study (Comings et al. 2003) and a Dutch family study (Gosso et al. 2006, in press) and both research groups found evidence that this gene may be involved in intelligence. In the COGA sample, we have extensively genotyped SNPs within and flanking the CHRM2 gene. We find evidence of association with multiple SNPs across CHRM2 and Performance IQ, as measured by the Wechsler Adult Intelligence Scale-Revised (WAIS-R). These results remain significant after taking into account alcohol dependence and depression diagnoses in the sample.

Alcoholism↗

Novel genes identified in a high-density genome wide association study for nicotine dependence.

Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.

Case-Control Studies↗

Cholinergic nicotinic receptor genes implicated in a nicotine dependence association study targeting 348 candidate genes with 3713 SNPs.

Nicotine dependence is one of the world's leading causes of preventable death. To discover genetic variants that influence risk for nicotine dependence, we targeted over 300 candidate genes and analyzed 3713 single nucleotide polymorphisms (SNPs) in 1050 cases and 879 controls. The Fagerström test for nicotine dependence (FTND) was used to assess dependence, in which cases were required to have an FTND of 4 or more. The control criterion was strict: control subjects must have smoked at least 100 cigarettes in their lifetimes and had an FTND of 0 during the heaviest period of smoking. After correcting for multiple testing by controlling the false discovery rate, several cholinergic nicotinic receptor genes dominated the top signals. The strongest association was from an SNP representing CHRNB3, the beta3 nicotinic receptor subunit gene (P = 9.4 x 10(-5)). Biologically, the most compelling evidence for a risk variant came from a non-synonymous SNP in the alpha5 nicotinic receptor subunit gene CHRNA5 (P = 6.4 x 10(-4)). This SNP exhibited evidence of a recessive mode of inheritance, resulting in individuals having a 2-fold increase in risk of developing nicotine dependence once exposed to cigarette smoking. Other genes among the top signals were KCNJ6 and GABRA4. This study represents one of the most powerful and extensive studies of nicotine dependence to date and has found novel risk loci that require confirmation by replication studies.

Adult↗

Microsatellites versus single-nucleotide polymorphisms in linkage analysis for quantitative and qualitative measures.

BACKGROUND: Genetic maps based on single-nucleotide polymorphisms (SNP) are increasingly being used as an alternative to microsatellite maps. This study compares linkage results for both types of maps for a neurophysiology phenotype and for an alcohol dependence phenotype. Our analysis used two SNP maps on the Illumina and Affymetrix platforms. We also considered the effect of high linkage disequilibrium (LD) in regions near the linkage peaks by analysing a "sparse" SNP map obtained by dropping some markers in high LD with other markers in those regions. RESULTS: The neurophysiology phenotype at the main linkage peak near 130 MB gave LOD scores of 2.76, 2.53, 3.22, and 2.68 for the microsatellite, Affymetrix, Illumina, and Illumina-sparse maps, respectively. The alcohol dependence phenotype at the main linkage peak near 101 MB gave LOD scores of 3.09, 3.69, 4.08, and 4.11 for the microsatellite, Affymetrix, Illumina, and Illumina-sparse maps, respectively. CONCLUSION: The linkage results were stronger overall for SNPs than for microsatellites for both phenotypes. However, LOD scores may be artificially elevated in regions of high LD. Our analysis indicates that appropriately thinning a SNP map in regions of high LD should give more accurate LOD scores. These results suggest that SNPs can be an efficient substitute for microsatellites for linkage analysis of both quantitative and qualitative phenotypes.

Alcoholism↗

An analysis of identical single-nucleotide polymorphisms genotyped by two different platforms.

The overlap of 94 single-nucleotide polymorphisms (SNP) among the 4,720 and 11,120 SNPs contained in the linkage panels of Illumina and Affymetrix, respectively, allows an assessment of the discrepancy rate produced by these two platforms. Although the no-call rate for the Affymetrix platform is approximately 8.6 times greater than for the Illumina platform, when both platforms make a genotypic call, the agreement is an impressive 99.85%. To determine if disputed genotypes can be resolved without sequencing, we studied recombination in the region of the discrepancy for the most discrepant SNP rs958883 (typed by Illumina) and tsc02060848 (typed by Affymetrix). We find that the number of inferred recombinants is substantially higher for the Affymetrix genotypes compared to the Illumina genotypes. We illustrate this with pedigree 10043, in which 3 of 7 versus 0 of 7 offspring must be double recombinants using the genotypes from the Affymetrix and the Illumina platforms, respectively. Of the 36 SNPs with one or more discrepancies, we identified a subset that appears to cluster in families. Some of this clustering may be due to the presence of a second segregating SNP that obliterates a XbaI site (the restriction enzyme used in the Affymetrix platform), resulting in a fragment too long (>1,000 bp) to be amplified.

Female↗

Multipoint identity-by-descent computations for single-point polymorphism and microsatellite maps.

We used the LOKI software to generate multipoint identity-by-descent matrices for a microsatellite map (with 31 markers) and two single-nucleotide polymorphism (SNP) maps to examine information content across chromosome 7 in the Collaborative Study on the Genetics of Alcoholism dataset. Despite the lower information provided by a single SNP, SNP maps overall had higher and more uniform information content across the chromosome. The Affymetrix map (578 SNPs) and the Illumina map (271 SNPs) provided almost identical information. However, increased information has a computational cost: SNP maps require 100 times as many iterations as microsatellites to produce stable estimates.

Chromosome Mapping↗

The efficacy of short tandem repeat polymorphisms versus single-nucleotide polymorphisms for resolving population structure.

Accurately resolving population structure in a sample is important for both linkage and association studies. In this study we investigated the power of single-nucleotide polymorphisms (SNPs) in detecting population structure in a sample of 286 unrelated individuals. We varied the number of SNPs to determine how many are required to approach the degree of resolution obtained with the Collaborative Study on the Genetics of Alcoholism (COGA) short tandem repeat polymorphisms (STRPs). In addition, we selected SNPs with varying minor allele frequencies (MAFs) to determine whether low or high frequency SNPs are more efficient in resolving population structure. We conclude that a set of at least 100 evenly spaced SNPs with MAFs of 40-50% is required to resolve population structure in this dataset. If SNPs with lower MAFs are used, then more than 250 SNPs may be required to obtain reliable results.

Alcoholism↗

Linkage analyses of IQ in the collaborative study on the genetics of alcoholism (COGA) sample.

Intelligence, as measured by standardized psychological tests, has been shown to be highly heritable, though identifying specific genes influencing general intelligence has proven difficult. We conducted genome-wide linkage analyses to identify chromosomal regions containing genes influencing intelligence, as measured by WAIS full-scale IQ (FSIQ), performance IQ (PIQ) and verbal IQ (VIQ). Non-parametric multipoint linkage analyses were conducted with Merlin-regress software, using a sample of 1,111 genotyped and phenotyped individuals from 201 families, ascertained as part of the Collaborative Study on the Genetics of Alcoholism (COGA). The strongest evidence of linkage was obtained for FSIQ on chromosome 6 (LOD=3.28, 12 cM) near the marker D6S1006. This region was also implicated with suggestive linkage in a recently published genome screen of IQ in Australian and Dutch twin pairs, and it has been implicated in linkage studies of developmental dyslexia. Our findings provide further support that chromosome 6p contains gene(s) affecting intelligence.

Alcoholism↗

Functional variant in a bitter-taste receptor (hTAS2R16) influences risk of alcohol dependence.

A coding single-nucleotide polymorphism (cSNP), K172N, in hTAS2R16, a gene encoding a taste receptor for bitter beta -glucopyranosides, shows significant association with alcohol dependence (P = .00018). This gene is located on chromosome 7q in a region reported elsewhere to exhibit linkage with alcohol dependence. The SNP is located in the putative ligand-binding domain and is associated with an increased sensitivity to many bitter beta -glucopyranosides in the presence of the N172 allele. Individuals with the ancestral allele K172 are at increased risk of alcohol dependence, regardless of ethnicity. However, this risk allele is uncommon in European Americans (minor-allele frequency [MAF] 0.6%), whereas 45% of African Americans carry the allele (MAF 26%), which makes it a much more significant risk factor in the African American population.

Black or African American↗

Evidence of common and specific genetic effects: association of the muscarinic acetylcholine receptor M2 (CHRM2) gene with alcohol dependence and major depressive syndrome.

Several correlated phenotypes, alcohol dependence, major depressive syndrome, and an endophenotype of electrophysiological measurements, event-related oscillations (EROs), have demonstrated linkage on the long arm of chromosome 7. Recently, we reported both linkage and association between polymorphisms in the gene encoding the muscarinic acetylcholine receptor M2 (CHRM2) and EROs. In this study, we evaluated whether genetic variation in the CHRM2 gene is also a risk factor for the correlated clinical characteristics of alcoholism and depression. The CHRM2 gene contains a single coding exon and a large 5' untranslated region encoded by multiple exons that can be alternatively spliced. Families were recruited through an alcohol dependent proband, and multiplex pedigrees were selected for genetic analyses. We examined 11 single nucleotide polymorphisms (SNPs) spanning the CHRM2 gene in these families. Using the UNPHASED pedigree disequilibrium test (PDTPHASE), three SNPs (one in intron 4 and two in intron 5) showed highly significant association with alcoholism (P=0.004-0.007). Two SNPs (both in intron 4) were significantly associated with major depressive syndrome (P=0.004 and 0.017). Haplotype analyses revealed that the most common haplotype (>40% frequency), T-T-T (rs1824024-rs2061174-rs324650), was under-transmitted to affected individuals with alcohol dependence and major depressive syndrome. Different complementary haplotypes were over-transmitted in alcohol dependent and depressed individuals. These findings provide strong evidence that variants within or close to the CHRM2 locus influence risk for two common psychiatric disorders.

Alcoholism↗

Linkage mapping of total cholesterol level in a young cohort via nonparametric regression.

BACKGROUND: Compared to model-based approaches, nonparametric methods for quantitative trait loci mapping are more robust to deviations in distributional assumptions. In this study, we modify a nonparametric regression method and the "contrast function"- based regression method to analyze total cholesterol level in the younger cohort (the offspring generation) of the Genetic Analysis Workshop 13 simulated data set. RESULTS: We obtained significant evidence of linkage near four of the six non-sex-specific genes in at least 30% of the replicates. CONCLUSIONS: The proposed nonparametric method seems to be a powerful robust alternative to distribution-based methods.

Cardiovascular Diseases↗