Recent developments in sequencing technology have allowed the investigation of the common disease/rare variant hypothesis. In the Genetic Analysis Workshop 17 data set, we have sequence data on both unrelated individuals and eight large extended pedigrees with simulated quantitative and qualitative phenotypes. Group 11, whose focus was incorporating linkage information, considered several different ways to use the extended pedigrees to identify causal genes and variants. The first issue was the use of standard linkage or identity-by-descent information to identify regions containing causal rare variants. We found that rare variants of large effect segregating through pedigrees were precisely the bailiwick of linkage analysis. For a common disease, we anticipate many risk loci, so a heterogeneity linkage analysis or an analysis of a single pedigree at a time may be useful. The second issue was using pedigree data to identify individuals for sequencing. If one can identify linked regions and even carriers of risk haplotypes, the sequencing will be substantially more efficient. In fact, sequencing only 2.5% of the genome in carefully selected individuals can detect 52% of the risk variants that would be detected through whole-exome sequencing in a large number of unrelated individuals. Finally, we found that linkage information from pedigrees can provide weights for case-control association tests. We also found that pedigree-based association tests have the same issues of binning variants and variant counting as those in tests of unrelated individuals. Clearly, when pedigrees are available, they can provide great assistance in the search for rare variants that influence common disorders.
linkage analysis; sequencing; LOD; heterogeneity LOD (HLOD); association tests
The age at onset of alcohol dependence (AD) is a critical moderator of genetic associations for alcohol dependence. The present study evaluated whether single nucleotide polymorphisms (SNPs) can influence the age at onset of AD in large high-risk families from the Collaborative Study on the Genetics of Alcoholism (COGA).
Genomewide SNP genotyping was performed in 1788 regular drinkers from 118 large European American families densely affected with alcoholism. We used a genome-wide Cox proportional hazards regression model to test for association between age at onset of AD and SNPs.
This family-based analysis identified an intergenic SNP, rs2168784 on chromosome 3 that showed strong evidence of association (p= 5 × 10−9) with age at onset of AD among regular drinkers. Carriers of the minor allele of rs2168784 had 1.5 times the hazard of AD onset as compared with those homozygous for the major allele. By the age of 20 years, nearly 30% of subjects homozygous for the minor allele were alcohol dependent while only 19% of those homozygous for the major allele were. We also identified intronic SNPs in the ADP-ribosylation factor like 15 (ARL15) gene on chromosome 5 (P = 1.11 × 10−8) and the UTP20 small subunit (UTP20) gene on chromosome 12 (P = 4.32 × 10−8) that were associated with age at onset of AD.
This extended family based genome-wide cox-proportional hazards analysis identified several loci that might be associated with age at onset of AD.
GWAS; alcohol dependence; age at onset; survival analysis; SNP
Maximum number of alcoholic drinks consumed in a 24-h period (maxdrinks) is a heritable (> 50%) trait and is strongly correlated with vulnerability to excessive alcohol consumption and subsequent alcohol dependence (AD). Several genome-wide association studies (GWAS) have studied alcohol dependence, but few have concentrated on excessive alcohol consumption. We performed two GWAS using maxdrinks as an excessive alcohol consumption phenotype: one in 118 extended families (N=2322) selected from the Collaborative Study on the Genetics of Alcoholism (COGA), and the other in a case-control sample (N=2593) derived from the Study of Addiction: Genes and Environment (SAGE). The strongest association in the COGA families was detected with rs9523562 (p = 2.1×10−6) located in an intergenic region on chromosome 13q31.1; the strongest association in the SAGE dataset was with rs67666182 (p = 7.1×10−7), located in an intergenic region on chromosome 8. We also performed a meta-analysis with these two GWAS and demonstrated evidence of association in both datasets for the LMO1 (p = 7.2×10−7) and PLCL1 genes (p = 4.1×10−6) with increased maxdrinks. A variant in AUTS2 and variants in INADL, C15orf32 and HIP1 that were associated with measures of alcohol consumption in a meta-analysis of GWAS studies and a GWAS of alcohol consumption factor score also showed nominal association in the current meta-analysis. The present study has identified several loci that warrant further examination in independent samples. Among the top SNPs in each of the dataset (p≤10−4) far more showed the same direction of effect in the other dataset than would be expected by chance (p = 2×10−3, 3×10−6), suggesting that there are true signals among these top SNPs, even though no SNP reached genome-wide levels of significance.
Alcohol consumption; maximum number of alcoholic drinks; GWAS; COGA; SAGE
The ideal genetic analysis of family data would include whole genome sequence on all family members. A strategy of combining sequence data from a subset of key individuals with inexpensive, genome-wide association study (GWAS) chip genotypes on all individuals to infer sequence level genotypes throughout the families has been suggested as a highly accurate alternative. This strategy was followed by the Genetic Analysis Workshop 18 data providers. We examined the quality of the imputation to identify potential consequences of this strategy by comparing discrepancies between GWAS genotype calls and imputed calls for the same variants. Overall, the inference and imputation process worked very well. However, we find that discrepancies occurred at an increased rate when imputation was used to infer missing data in sequenced individuals. Although this may be an artifact of this particular instantiation of these analytic methods, there may be general genetic or algorithmic reasons to avoid trying to fill in missing sequence data. This is especially true given the risk of false positives and reduction in power for family-based transmission tests when founders are incorrectly imputed as heterozygotes. Finally, we note a higher rate of discrepancies when unsequenced individuals are inferred using sequenced individuals from other pedigrees drawn from the same admixed population.
Cryptic population structure can increase both type I and type II errors. This is particularly problematic in case-control association studies of unrelated individuals. Some researchers believe that these problems are obviated in families. We argue here that this may not be the case, especially if families are drawn from a known admixed population such as Mexican Americans. We use a principal component approach to evaluate and visualize the results of three different approaches to searching for cryptic structure in the 20 multigenerational families of the Genetic Analysis Workshop 18 (GAW18). Approach 1 uses all family members in the sample to identify what might be considered "outlier" kindreds. Because families are likely to differ in size (in the GAW18 families, there is about a 4-fold difference in the number of typed individuals), approach 2 uses a weighting system that equalizes pedigree size. Approach 3 concentrates on the founders and the "marry-ins" because, in principle, the entire pedigree can be reconstructed with knowledge of the sequence of these unrelated individuals and genome-wide association study (GWAS) data on everyone else (to identify the position of recombinations). We demonstrate that these three approaches can yield very different insights about cryptic structure in a sample of families.
Several studies have identified genes associated with alcohol use disorders, but the variation in each of these genes explains only a small portion of the genetic vulnerability. The goal of the present study was to perform a genome-wide association study (GWAS) in extended families from the Collaborative Study on the Genetics of Alcoholism (COGA) to identify novel genes affecting risk for alcohol dependence. To maximize the power of the extended family design we used a quantitative endophenotype, measured in all individuals: number of alcohol dependence symptoms endorsed (symptom count). Secondary analyses were performed to determine if the single nucleotide polymorphisms (SNPs) associated with symptom count were also associated with the dichotomous phenotype, DSM-IV alcohol dependence. This family-based GWAS identified SNPs in C15orf53 that are strongly associated with DSM-IV alcohol (p=4.5×10−8, inflation corrected p=9.4×10−7). Results with DSM-IV alcohol dependence in the regions of interest support our findings with symptom count, though the associations were less significant. Attempted replications of the most promising association results were conducted in two independent samples: non-overlapping subjects from the Study of Addiction: Genes and Environment (SAGE) and the Australian twin-family study of alcohol use disorders (OZALC). Nominal association of C15orf53 with symptom count was observed in SAGE. The variant that showed strongest association with symptom count, rs12912251 and its highly correlated variants (D′=1, r2≥ 0.95), has previously been associated with risk for bipolar disorder.
DSM-IV alcohol dependence symptoms; Family-based GWAS; C15orf53; Quantitative traits
Older adults are among the most vulnerable to adverse cognitive effects of psychotropic medications and, therefore, the personalization of psychotropic treatment based on adverse drug reactions in this demographic is of great importance. We examined changes on neuropsychological tests of attention attributable to selective serotonin reuptake inhibitor (SSRI) treatment in anxious older adults. We also examined whether variation in serotonin receptor genes was associated with reduced attentional performance with SSRIs. We examined change from pre- to post-treatment in two attention measures – digit span and coding – in 133 adults aged ≥60 yr with generalized anxiety disorder in a 12-wk trial of escitalopram vs. placebo. We also examined attentional change in relation to genetic variability in four central serotonin receptors: the serotonin transporter and serotonin 1A, 2A and 1B receptors. Digit span scores were significantly lowered in patients receiving escitalopram relative to placebo, indicating reduced attentional performance attributable to the SSRI. Individuals with high-transcription variants in the receptors 5-HTR2A rs6311 and 5-HTR1B rs11568817 had greater reductions in attention with SSRI treatment compared to placebo. We conclude that SSRIs reduce attention in older adults, particularly in those with high-expression genetic variants at the serotonin 2A and 1B receptors. Analysing neuropsychological changes with SSRIs in relation to genetic variation in the serotonin system may be a useful strategy for detecting subgroups of older adults who are more susceptible to side-effects of SSRIs. These results, if confirmed, could lead to the personalization of SSRI use to reduce adverse neurocognitive effects.
Anxiety; antidepressant; elderly; neuropsychological functioning; pharmacogenomics
Chromosome 7 has shown consistent evidence of linkage with a variety of phenotypes related to alcohol dependence in the Collaborative Study on the Genetics of Alcoholism (COGA) project. Using a sample of 262 densely affected families, a peak lod score for alcohol dependence of 2.9 was observed at D7S1799 (Wang et al., 2004, Hum Mol Genet). The lod score in the region increased to 4.1 when a subset of the sample was genotyped with the Illumina Linkage III panel for the Genetic Analysis Workshop 14 (GAW14; Dunn et al., 2005, BMC Genetics). To follow-up on this linkage region, we systematically screened SNPs across a 2 LOD support interval surrounding the alcohol dependence peak.
SNPs were selected from the HapMap Phase I CEPH data to tag linkage disequilibrium bins across the region. 1340 across the 18Mb region, genotyped by the Center for Inherited Disease Research (CIDR), were analyzed. Family-based association analyses were performed on a sample of 1172 individuals from 217 Caucasian families. Results: Eight SNPs showed association with alcohol dependence at p<0.01. Four of the eight most significant SNPs were located in or very near the ACN9 gene. We conducted additional genotyping across ACN9 and identified multiple variants with significant evidence of association with alcohol dependence.
These analyses suggest that ACN9 is involved in the predisposition to alcohol dependence. Data from yeast suggest that ACN9 is involved in gluconeogenesis and the assimilation of ethanol or acetate into carbohydrate.
genetics; association; linkage disequilibrium; alcohol dependence; ACN9
The apolipoprotein E (APOE) genotype is the major genetic risk factor for Alzheimer's disease (AD). We have access to cerebrospinal fluid (CSF) and plasma APOE protein levels from 641 individuals and genome-wide genotyped data from 570 of these samples. The aim of this study was to test whether CSF or plasma APOE levels could be a useful endophenotype for AD and to identify genetic variants associated with APOE levels. We found that CSF (P = 8.15 × 10−4) but not plasma (P = 0.071) APOE protein levels are significantly associated with CSF Aβ42 levels. We used Mendelian randomization and genetic variants as instrumental variables to confirm that the association of CSF APOE with CSF Aβ42 levels and clinical dementia rating (CDR) is not because of a reverse causation or confounding effect. In addition the association of CSF APOE with Aβ42 levels was independent of the APOE ɛ4 genotype, suggesting that APOE levels in CSF may be a useful endophenotype for AD. We performed a genome-wide association study to identify genetic variants associated with CSF APOE levels: the APOE ɛ4 genotype was the strongest single-genetic factor associated with CSF APOE protein levels (P = 6.9 × 10−13). In aggregate, the Illumina chip single nucleotide polymorphisms explain 72% of the variability in CSF APOE protein levels, whereas the APOE ɛ4 genotype alone explains 8% of the variability. No other genetic variant reached the genome-wide significance threshold, but nine additional variants exhibited a P-value <10−6. Pathway mining analysis indicated that these nine additional loci are involved in lipid metabolism (P = 4.49 × 10−9).
Apolipoprotein E (APOE) is the most statistically significant genetic risk factor for late-onset Alzheimer’s disease (LOAD). The linkage disequilibrium pattern around the APOE gene has made it difficult to determine whether all of the association signal is derived from APOE or if there is an independent signal from a nearby gene. In this study we attempted to replicate a recently reported association of APOE 3-TOMM40 haplotypes with risk and age at onset.
We used standard techniques to genotype several polymorphisms in the APOE-TOMM40 region in a large case-control series, in a series with cerebrospinal fluid biomarker data and in brain tissue.
We failed to replicate the previously reported association of the polyT polymorphism (rs10524523) with risk and age at onset. We found a significant association between rs10524523 and risk for LOAD among APOE 33 homozygotes but in the opposite direction to the previously reported association (the very-long allele was underrepresented in cases compared to controls in our study (allele frequency: 0.41 vs. 0.48 respectively; p=0.004)). We found no association between rs10524523 and CSF tau or Aβ42 levels or TOMM40 or APOE gene expression.
Although we were not able to replicate the earlier association between the APOE 3-TOMM40 haplotypes and age at onset, we did observe that the polyT polymorphism is associated with risk for LOAD among APOE 33 homozygotes in a large case-control series, but in the opposite direction to the previous report. Additional studies in very large samples will be needed to confirm this association.
Cytochrome P450 2A6 (CYP2A6) is the primary catalyst of nicotine metabolism. To develop a predictive genetic model of nicotine metabolism, the conversion of deuterated (D2)-nicotine to D2-cotinine was quantified in 189 European Americans and the contribution of CYP2A6 genotype to variability in first-pass nicotine metabolism was assessed. Specifically, 1) single time-point measures of D2-cotinine/(D2-cotinine + D2-nicotine) following oral administration were used as a metric of CYP2A6 activity; 2) the impact of CYP2A6 haplotype was treated as acting multiplicatively; 3) parameter estimates were calculated for all haplotypes in the subject pool, defined by a set of polymorphisms previously reported to affect function, including gene copy number; and 4) a minimum number of predictive polymorphisms are justified to be included in the model based on statistical evidence of differences between haplotypes. The final model includes seven polymorphisms and fits the phenotype, 30 minutes following D2-nicotine oral administration, with R2=0.719. The predictive power of the model is robust: parameter estimates calculated in men (n=89) predict the phenotype in women (n=100) with R2=0.758 and vice versa with R2=0.617; estimates calculated in current smokers (n=102) predict phenotype in former smokers (n=86) with R2=0.690 and vice versa with R2=0.703. Comparisons of haplotypes also demonstrate that CYP2A6*12 is a loss of function allele indistinguishable from CYP2A6*4 and CYP2A6*2 and that the CYP2A6*1B 5′ UTR conversion has negligible impact on metabolism. After controlling for CYP2A6 genotype modest associations were found between increased metabolism and both female gender (p= 4.8×10−4) and current smoking (p=0.02).
CYP2A6; nicotine metabolism; cotinine
Despite twin studies showing that 50–70% of variation in DSM-IV cannabis dependence is attributable to heritable influences, little is known of specific genotypes that influence vulnerability to cannabis dependence. We conducted a genomewide association study of DSM-IV cannabis dependence. Association analyses of 708 DSM-IV cannabis dependent cases with 2,346 cannabis exposed nondependent controls was conducted using logistic regression in PLINK. None of the 948,142 SNPs met genomewide significance (p < E−8). The lowest p-values were obtained for polymorphisms on chromosome 17 (rs1019238 and rs1431318, p-values at E−7) in the ANKFN1 gene. While replication is required, this study represents an important first step towards clarifying the biological underpinnings of cannabis dependence.
Cigarette smoking and other forms of tobacco use are the leading cause of preventable mortality in the world. A better understanding of the etiology of nicotine addiction may help increase the success rate of cessation and decrease the massive morbidity and mortality associated with smoking.
In order to identify genetic polymorphisms that contribute to nicotine dependence, our group undertook a genetic association study including three enzyme families that potentially influence nicotine metabolism: cytochrome P450 enzymes (CYP P450s), flavin monooxygenases (FMOs) and UDP-glucuronosyl transferases (UGTs).
Several polymorphisms in FMO1 showed association in a discovery sample and were tested in an independent replication sample. One polymorphism, rs10912765, showed association that remained significant after Bonferroni correction (nominal p=0.0067, corrected p=0.0134). Several additional polymorphisms in linkage disequilibrium with this SNP also showed association. Subsequent in vitro experiments characterized FMO1 as a more efficient catalyst of nicotine N-oxidation than FMO3. In adult humans, FMO1 is primarily expressed in the kidney and is likely to be a major contributor to the renal metabolism and clearance of therapeutic drugs. FMO1 is also expressed in the brain and could contribute to the nicotine concentration in this tissue.
These findings suggest that polymorphisms in FMO1 are significant risk factors in the development of nicotine dependence and that the mechanism may involve variation in nicotine pharmacology.
FMO1; nicotine dependence; nicotine metabolism
A recent genome-wide association study for frontotemporal lobar degeneration with TAR DNA-binding protein inclusions (FTLD-TDP), identified rs1990622 (TMEM106B) as a risk factor for FTLD-TDP. In this study we tested whether rs1990622 is associated with age at onset (AAO) in granulin (GRN) mutation carriers and with plasma GRN levels in mutation carriers and healthy elderly individuals.
Rs1990622 was genotyped in GRN mutation carriers and tested for association with AAO using the Kaplan-Meier and a Cox proportional hazards model.
We analyzed 50 affected and unaffected GRN mutation carriers from four previously reported FTLD-TDP families (HDDD1, FD1, HDDD2 and the Karolinska family). GRN plasma levels were also measured in 73 healthy, elderly individuals.
The risk allele of rs1990622 is associated with a mean decrease of the age at onset of thirteen years (p=9.9×10−7), with lower plasma granulin levels in both healthy older adults (p = 4×10−4) and GRN mutation carriers (p=0.0027). Analysis of the HAPMAP database identified a non-synonymous single nucleotide polymorphism, rs3173615 (T185S) in perfect linkage disequilibrium with rs1990622.
The association of rs1990622 with AAO explains, in part, the wide range in the age at onset of disease among GRN mutation carriers. We hypothesize that rs1990622 or another variant in linkage disequilibrium could act in a manner similar to APOE in Alzheimer’s disease, increasing risk for disease in the general population and modifying AAO in mutation carriers. Our results also suggest that genetic variation in TMEM106B may influence risk for FTLD-TDP by modulating secreted levels of GRN.
Several genome-wide association and candidate gene studies have linked chromosome 15q24–q25.1 (a region including the CHRNA5-CHRNA3-CHRNB4 gene cluster) with alcohol dependence, nicotine dependence and smoking-related illnesses such as lung cancer and chronic obstructive pulmonary disease. To further examine the impact of these genes on the development of substance use disorders, we tested whether variants within and flanking the CHRNA5-CHRNA3-CHRNB4 gene cluster affect the transition to daily smoking (individuals who smoked cigarettes 4 or more days per week) in a cross sectional sample of adolescents and young adults from the COGA (Collaborative Study of the Genetics of Alcoholism) families. Subjects were recruited from families affected with alcoholism (either as a first or second degree relative) and the comparison families. Participants completed the SSAGA interview, a comprehensive assessment of alcohol and other substance use and related behaviors. Using the Quantitative trait disequilibrium test (QTDT) significant association was detected between age at onset of daily smoking and variants located upstream of CHRNB4. Multivariate analysis using a Cox proportional hazards model further revealed that these variants significantly predict the age at onset of habitual smoking among daily smokers. These variants were not in high linkage disequilibrium (0.28
Genetic Analysis Workshop 17 (GAW17) provided a platform for evaluating existing statistical genetic methods and for developing novel methods to analyze rare variants that modulate complex traits. In this article, we present an overview of the 1000 Genomes Project exome data and simulated phenotype data that were distributed to GAW17 participants for analyses, the different issues addressed by the participants, and the process of preparation of manuscripts resulting from the discussions during the workshop.
The unrelated individuals sample from Genetic Analysis Workshop 17 consists of a small number of subjects from eight population samples and genetic data composed mostly of rare variants. We compare two simple approaches to collapsing rare variants within genes for their utility in identifying genes that affect phenotype. We also compare results from stratified analyses to those from a pooled analysis that uses ethnicity as a covariate. We found that the two collapsing approaches were similarly effective in identifying genes that contain causative variants in these data. However, including population as a covariate was not an effective substitute for analyzing the subpopulations separately when only one subpopulation contained a rare variant linked to the phenotype.
We report two approaches for linkage analysis of data consisting of replicate phenotypes. The first approach is specifically designed for the unusual (in human data) replicate structure of the Genetic Analysis Workshop 17 pedigree data. The second approach consists of a standard linkage analysis that, although not specifically tailored to data consisting of replicate genotypes, was envisioned as providing a sounding board against which our novel approach could be assessed. Both approaches are applied to the analysis of three quantitative phenotypes (Q1, Q2, and Q4) in two sets of African families. All analyses were carried out blind to the generating model (i.e., the “answers”). Using both methods, we found numerous significant linkage signals for Q1, although population colocalization was absent for most of these signals. The linkage analysis of Q2 and Q4 failed to reveal any strong linkage signals.
Although the importance of selecting cases and controls from the same population has been recognized for decades, the recent advent of genome-wide association studies has heightened awareness of this issue. Because these studies typically deal with large samples, small differences in allele frequencies between cases and controls can easily reach statistical significance. When, unbeknownst to a researcher, cases and controls have different substructures, the number of false-positive findings is inflated. There have been three recent developments of purely statistical approaches to assessing the ancestral comparability of case and control samples: genomic control, structured association, and multivariate reduction analyses. The widespread use of high-throughput technology has allowed the quick and accurate genotyping of the large number of markers required by these methods.
Group 13 dealt with four population stratification issues: single-nucleotide polymorphism marker selection, association testing, non-standard methods, and linkage disequilibrium calculations in stratified or mixed ethnicity samples. We demonstrated that there are continuous axes of ethnic variation in both datasets of Genetic Analysis Workshop 16. Furthermore, ignoring this structure created p-value inflation for a variety of phenotypes. Principal-components analysis (or multidimensional scaling) can control inflation as covariates in a logistic regression. One can weight for local ancestry estimation and allow the use of related individuals. Problems arise in the presence of extremely high association or unusually strong linkage disequilibrium (e.g., in chromosomal inversions). Our group also reported a method for performing an association test controlling for substructure when genome-wide markers are not available to explicitly compute stratification.
genetic association; genome-wide association study; principal components; multidimensional scaling; ethnic substructure
Alcohol dependence is a complex disease, and although linkage and candidate gene studies have identified several genes associated with the risk for alcoholism, these explain only a portion of the risk.
We carried out a genome-wide association study (GWAS) on a case-control sample drawn from the families in the Collaborative Study on the Genetics of Alcoholism. The cases all met diagnostic criteria for alcohol dependence according to the Diagnostic and Statistical Manual of the American Psychiatric Association Fourth Edition (DSM-IV); controls all consumed alcohol but were not dependent on alcohol or illicit drugs. To prioritize among the strongest candidates, we genotyped most of the top 199 SNPs (p ≤ 2.1 × 10−4) in a sample of alcohol dependent families and performed pedigree-based association analysis. We also examined whether the genes harboring the top SNPs were expressed in human brain or were differentially expressed in the presence of ethanol in lymphoblastoid cells.
Although no single SNP met genome-wide criteria for significance, there were several clusters of SNPs that provided mutual support. Combining evidence from the case-control study, the followup in families, and gene expression provided strongest support for the association of a cluster of genes on chromosome 11 (SLC22A18, PHLDA2, NAP1L4, SNORA54, CARS, and OSBPL5) with alcohol dependence. Several SNPs nominated as candidates in earlier GWAS studies replicated in ours, including CPE, DNASE2B, SLC10A2,ARL6IP5, ID4, GATA4, SYNE1 and ADCY3.
We have identified several promising associations that warrant further examination in independent samples.
alcohol dependence; genome-wide association study; case-control study; family study; gene expression
To date, all known Alzheimer's disease genes influence amyloid beta (Aβ). The development of in vivo imaging of Aβ deposition in the human brain using Pittsburgh compound B (PIB) offers the possibility of using cortical PIB binding as a quantitative endophenotype for genetic studies of late-onset Alzheimer's disease (LOAD).
Heritability of Aβ deposition was determined using 82 elderly siblings from 35 families. Correlation with other Aβ related traits was determined using an unrelated sample of 112 individuals. For both samples, APOE ε4 was genotyped and PET imaging was performed using the PIB ligand. Mean cortical binding potential (MCBP) was computed from several regions-of-interest.
MCBP has a high heritability (0.61, p=0.043). Furthermore, most of the heritable component (74%) cannot be explained by APOE ε4 genotype. Analysis of the unrelated sample reveals that a third of the variance of MCBP cannot be predicted by other biological traits, including CSF Aβ42 levels.
These findings demonstrate that MCBP is a genetic trait and that other more easily measured Aβ related traits such as CSF Aβ42 do not fully explain the variance in MCBP. Thus, mean cortical PIB binding is a useful trait for large-scale genetic studies of LOAD.
Recent large-scale genetic studies of late-onset Alzheimer’s disease (LOAD) have identified risk variants in CALHM1, GAB2 and SORL1. The mechanisms by which these genes might modulate risk are not definitively known. CALHM1 and SORL1 may alter amyloid-beta (Aβ) levels and GAB2 may influence phosphorylation of the tau protein. In this study we have analyzed disease associated genetic variants in each of these genes for association with cerebrospinal fluid (CSF) Aβ or tau levels in 602 samples from two independent CSF series. We failed to detect association between CSF Aβ42 levels and SNPs in SORL1 despite substantial statistical power to detect association. While we also failed to detect association between variants in GAB2 and CSF tau levels, power to detect this association was limited. Finally, our data suggest that the minor allele of rs2986017, in CALHM1, is marginally associated with CSF Aβ42 levels. This association is consistent with previous reports that this non-synonymous coding substitution results in increased Aβ levels in vitro and provides support for an Aβ-related mechanism for modulating risk for AD.
Alzheimer’s disease; genetics; association; endophenotypes; amyloid; tau; CALHM1; SORL1; GAB2
Several studies have found replicable associations between nicotine dependence and specific variants in the nicotinic receptor genes CHRNA5(rs16969968) and CHRNA3(rs3743078). How these newly identified genetic risks combine with known environmental risks is unknown. This study examined whether the level of parent monitoring during early adolescence modified the risk of nicotine dependence associated with these genetic variants.
In a cross-sectional case control study of US-based community sample of 2027 subjects, we use a systematic series of regression models to examine the effect of parent monitoring on risk associated with two distinct variants in the nicotinic receptor genes CHRNA5(rs16969968) and CHRNA3(rs3743078).
Low parent monitoring as well as the previously identified genetic variants were associated with an increased risk of nicotine dependence. An interaction was found between the SNP(rs16969968) and parent monitoring (p=0.034). The risk for nicotine dependence increased significantly with the risk genotype of SNP(rs16969968) when combined with lowest quartile parent monitoring. In contrast, there was no evidence of an interaction between SNP(rs3743078) and parent monitoring (p=0.80).
The genetic risk of nicotine dependent associated with rs16969968 was modified by level of parent monitoring, while the genetic risk associated with rs3743078 was not, suggesting that the increased risk due to some genes may be mitigated by environmental factors such as parent monitoring.
nicotine dependence; parent monitoring; phenotype; gene-environmental interaction; nicotinic receptor genes; case control study
Genetic association studies have demonstrated the importance of variants in the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit gene cluster on chromosome 15q24-25.1 in risk for nicotine dependence, smoking, and lung cancer in populations of European descent. We have now carried out a detailed study of this region using dense genotyping in both European- and African-Americans.
We genotyped 75 known single-nucleotide-polymorphisms (SNPs) and one sequencing-discovered SNP in an African-American (AA) sample (N = 710) and European-American (EA) sample (N = 2062). Cases were nicotine-dependent and controls were non-dependent smokers.
The non-synonymous CHRNA5 SNP rs16969968 is the most significant SNP associated with nicotine dependence in the full sample of 2772 subjects (p = 4.49×10−8, OR 1.42 (1.25–1.61)) as well as in AAs only (p = 0.015, OR = 2.04 (1.15–3.62)) and EAs only (p = 4.14×10−7, OR = 1.40 (1.23–1.59)). Other SNPs that have been shown to affect mRNA levels of CHRNA5 in EAs are associated with nicotine dependence in AAs but not in EAs. The CHRNA3 SNP rs578776, which has low correlation with rs16969968, is associated with nicotine dependence in EAs but not in AAs. Less common SNPs (frequency ≤ 5%) also are associated with nicotine dependence.
In summary, multiple variants in this gene cluster contribute to nicotine dependence risk, and some are also associated with functional effects on CHRNA5. The non-synonymous SNP rs16969968, a known risk variant in European-descent populations, is also significantly associated with risk in African-Americans. Additional SNPs contribute in distinct ways to risk in these two populations.
genetic association; smoking; cholinergic nicotinic receptors; nicotinic acetylcholine receptors
Genomic studies of cannabis use disorders have been limited. The cannabinoid receptor 1 gene (CNR1) on chromosome 6q14–15 is an excellent candidate gene for cannabis dependence due to the important role of the G-protein coupled receptor encoded by this gene in the rewarding effects of Δ9-tetrahydrocannabinol. Previous studies have found equivocal evidence for an association between SNPs in CNR1 and a general vulnerability to substance use disorders. We investigate the association between 9 SNPs spanning CNR1 and cannabis dependence in 1,923 individuals. Two SNPs that were previously associated with cannabis dependence in other studies were also significant with this phenotype in our analyses [rs806368 (p = 0.05) and rs806380 (p = 0.009)]. Haplotype analyses revealed the association to be largely driven by the SNP rs806380. These results suggest a role for the cannabinoid receptor 1 gene in cannabis dependence.
CNR1; cannabis dependence; COGA; pedigree disequilibrium test; association
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