The Experts below are selected from a list of 318 Experts worldwide ranked by ideXlab platform

Robert Plomin - One of the best experts on this subject based on the ideXlab platform.

  • Genetic Influence on social outcomes during and after the Soviet era in Estonia
    Nature human behaviour, 2018
    Co-Authors: Kaili Rimfeld, Maciej Trzaskowski, Eva Krapohl, Philip S. Dale, Jonathan R.i. Coleman, Saskia Selzam, Tõnu Esko, Andres Metspalu, Robert Plomin
    Abstract:

    The aetiology of individual differences in educational attainment and occupational status includes Genetic as well as environmental factors1–5 and can change as societies change3,6,7. The extent of Genetic Influence on these social outcomes can be viewed as an index of success in achieving meritocratic values of equality of opportunity by rewarding talent and hard work, which are to a large extent Influenced by Genetic factors, rather than rewarding environmentally driven privilege. To the extent that the end of the Soviet Union and the independence of Estonia led to an increase in meritocratic selection of individuals in education and occupation, Genetic Influence should be higher in the post-Soviet era than in the Soviet era. Here we confirmed this hypothesis: DNA differences (single-nucleotide polymorphisms) explained twice as much variance in educational attainment and occupational status in the post-Soviet era compared with the Soviet era in both polygenic score analyses and single-nucleotide polymorphism heritability analyses of 12,500 Estonians. Our results demonstrate a change in the extent of Genetic Influence in the same population following a massive and abrupt social change—in this case, the shift from a communist to a capitalist society.

  • Genetic Influence on Intergenerational Educational Attainment.
    Psychological science, 2017
    Co-Authors: Ziada Ayorech, Robert Plomin, Eva Krapohl, Sophie Von Stumm
    Abstract:

    Using twin (6,105 twin pairs) and genomic (5,825 unrelated individuals taken from the twin sample) analyses, we tested for Genetic Influences on the parent-offspring correspondence in educational attainment. Genetics accounted for nearly half of the variance in intergenerational educational attainment. A genomewide polygenic score (GPS) for years of education was also associated with intergenerational educational attainment: The highest and lowest GPS means were found for offspring in stably educated families (i.e., who had taken A Levels and had a university-educated parent; M = 0.43, SD = 0.97) and stably uneducated families (i.e., who had not taken A Levels and had no university-educated parent; M = −0.19, SD = 0.97). The average GPSs fell in between for children who were upwardly mobile (i.e., who had taken A Levels but had no university-educated parent; M = 0.05, SD = 0.96) and children who were downwardly mobile (i.e., who had not taken A Levels but had a university-educated parent; M = 0.28, SD = 1.03). Genetic Influences on intergenerational educational attainment can be viewed as an index of equality of educational opportunity.

  • Genetic Influence on family socioeconomic status and children s intelligence
    Intelligence, 2014
    Co-Authors: Maciej Trzaskowski, Eva Krapohl, Philip S. Dale, Nicole Harlaar, Rosalind Arden, Kaili Rimfeld, Andrew Mcmillan, Robert Plomin
    Abstract:

    Environmental measures used widely in the behavioral sciences show nearly as much Genetic Influence as behavioral measures, a critical finding for interpreting associations between environmental factors and children's development. This research depends on the twin method that compares monozygotic and dizygotic twins, but key aspects of children's environment such as socioeconomic status (SES) cannot be investigated in twin studies because they are the same for children growing up together in a family. Here, using a new technique applied to DNA from 3000 unrelated children, we show significant Genetic Influence on family SES, and on its association with children's IQ at ages 7 and 12. In addition to demonstrating the ability to investigate Genetic Influence on between-family environmental measures, our results emphasize the need to consider Genetics in research and policy on family SES and its association with children's IQ.

  • finding the missing heritability in pediatric obesity the contribution of genome wide complex trait analysis
    International Journal of Obesity, 2013
    Co-Authors: Clare H. Llewellyn, Maciej Trzaskowski, Robert Plomin, J Wardle
    Abstract:

    Known single-nucleotide polymorphisms (SNPs) explain 50% heritability from twin and family studies, a phenomenon termed 'missing heritability'. Using DNA alone for unrelated individuals, a novel method (in a software package called Genome-wide Complex Trait Analysis, GCTA) estimates the total additive Genetic Influence due to common SNPs on whole-genome arrays. GCTA has made major inroads into explaining the 'missing heritability' of BMI in adults. This study provides the first GCTA estimate of Genetic Influence on adiposity in children. Participants were from the Twins Early Development Study (TEDS), a British twin birth cohort. BMI s.d. scores (BMI-SDS) were obtained from validated parent-reported anthropometric measures when children were about 10 years old (mean=9.9; s.d.=0.84). Selecting one child per family (n=2269), GCTA results from 1.7 million DNA markers were used to quantify the additive Genetic Influence of common SNPs. For direct comparison, a standard twin analysis in the same families estimated the additive Genetic Influence as 82% (95% CI: 0.74-0.88, P<0.001). GCTA explained 30% of the variance in BMI-SDS (95% CI: 0.02-0.59; P=0.02). These results indicate that 37% of the twin-estimated heritability (30/82%) can be explained by additive effects of multiple common SNPs, and provide compelling evidence for strong Genetic Influence on adiposity in childhood.

  • No Genetic Influence for Childhood Behavior Problems From DNA Analysis
    Journal of the American Academy of Child and Adolescent Psychiatry, 2013
    Co-Authors: Maciej Trzaskowski, Philip S. Dale, Robert Plomin
    Abstract:

    Objective Twin studies of behavior problems in childhood point to substantial Genetic Influence. It is now possible to estimate Genetic Influence using DNA alone in samples of unrelated individuals, not relying on family-based designs such as twins. A linear mixed model, which incorporates DNA microarray data, has confirmed twin results by showing substantial Genetic Influence for diverse traits in adults. Here we present direct comparisons between twin and DNA heritability estimates for childhood behavior problems as rated by parents, teachers, and children themselves. Method Behavior problem data from 2,500 UK-representative 12-year-old twin pairs were used in twin analyses; DNA analyses were based on 1 member of the twin pair with genotype data for 1.7 million DNA markers. Diverse behavior problems were assessed, including autistic, depressive, and hyperactive symptoms. Genetic Influence from DNA was estimated using genome-wide complex trait analysis (GCTA), and the twin estimates of heritability were based on standard twin model fitting. Results Behavior problems in childhood—whether rated by parents, teachers, or children themselves—show no significant Genetic Influence using GCTA, even though twin study estimates of heritability are substantial in the same sample, and even though both GCTA and twin study estimates of Genetic Influence are substantial for cognitive and anthropometric traits. Conclusions We suggest that this new type of "missing heritability," that is, the gap between GCTA and twin study estimates for behavior problems in childhood, is due to nonadditive Genetic Influence, which will make it more difficult to identify genes responsible for heritability.

Wolfgang Sadée - One of the best experts on this subject based on the ideXlab platform.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC Genomics, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    Abstract Background The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. Results We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. Conclusions These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci

Sung-ha Lee - One of the best experts on this subject based on the ideXlab platform.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC Genomics, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    Abstract Background The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. Results We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. Conclusions These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci

Woo-young Ahn - One of the best experts on this subject based on the ideXlab platform.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC Genomics, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    Abstract Background The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. Results We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. Conclusions These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci

Michal Seweryn - One of the best experts on this subject based on the ideXlab platform.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC Genomics, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci.

  • Combined Genetic Influence of the nicotinic receptor gene cluster CHRNA5/A3/B4 on nicotine dependence
    BMC, 2018
    Co-Authors: Sung-ha Lee, Michal Seweryn, Woo-young Ahn, Wolfgang Sadée
    Abstract:

    Abstract Background The CHRNA5/A3/B4 gene locus is associated with nicotine dependence and other smoking related disorders. While the non-synonymous CHRNA5 variant rs16969968 appears to be the main risk factor, linkage disequilibrium (LD) bins in the gene cluster carry frequent variants that regulate expression. Pairwise LD and haplotype analyses had identified at least three haplotype tagging SNPs including rs16969968 as main Genetic risk factors. Searching for variants with evidence of regulatory functions, we have reported interactions between CHRNA5 and CHRNA3 enhancer variants (tagged by rs880395 and rs1948, respectively) and rs16969968, forming 3-SNP haplotypes and diplotypes that may more accurately reflect the cluster’s combined effects on nicotine dependence (Barrie et al., Hum Mutat 38:112–9, 2017). Here we address further contributions by variants affecting CHRNB4, a possibly limiting component of nicotinic receptors. Results We identify an LD bin (tagged by rs4887074) associated with expression of CHRNB4. Additive logistic regression models indicate that rs4887074 is associated with nicotine dependence and modulates the effect of rs16969968 in GWAS datasets (COGEND, UW-TTURC, SAGE). 4-SNP haplotype and diplotype analyses (rs880395-rs16969968-rs1948 -rs4887074) yield nicotine dependence risk values that further differentiate those obtained with the 3-SNP model. Moreover, both the main G allele of rs16969968 and the minor G allele of rs4887074 (associated with reduced expression of CHRNB4), residing predominantly on common haplotypes that are protective, represent significant allele-specific variance QTLs, indicating that they interact with each other. Conclusions These results indicate rs4887074 is associated with CHRNB4 expression, and along with two regulatory variants of CHRNA3 and CHRNA5, modulates the effect of rs16969968 on nicotine dependence risk. Assignable to individuals because of strong LD structures, 4-SNP haplotypes and diplotypes serve to assess the combined Genetic Influence of this multi-gene cluster on complex traits, accounting for complex LD relationships and tissue-specific Genetic effects (CHRNA5/3) relevant to the traits analyzed. The 4-SNP haplotypes account at least in part for previous tagging SNPs, including the highly GWAS-significant rs6495308, located in a distinct pair-wise LD bin but included in protective 4-SNP haplotypes. Our approach refines and integrates the cluster’s overall Genetic Influence, an important variable when integrating the Genetics of multiple genomic loci