What the I don't even - yes, I know everything is heritable and that I've said this is a golden age for behavioral genetics and of course coffee-drinking has genetic influence (since the twin studies have always shown that http://scholar.google.com/scholar?q=heritability%20coffee ) but who on earth gave these maniacs 90k samples to do this analysis‽
"Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption", The Coffee and Caffeine Genetics Consortium et al 2014 https://www.dropbox.com/s/0v7bzyzu1kjv0jo/2014-cornelis.pdf / http://sci-hub.org/downloads/8bca/cornelis2014.pdf
"We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91 462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~ 30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log 10 Bayes factor (BF)45.64) with per-allele effect sizes of 0.03–0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P o 5 × 10 − 8 ).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.
Heritability estimates for coffee and caffeine use range between 36 and 58%. 6 Genome-wide association studies (GWAS) of habitual caffeine and coffee intake have identified variants near CYP1A2 and aryl hydrocarbon receptor (AHR). 7–9 Cytochrome P450 (CYP)1A2 is responsible for ~ 95% of caffeine metabolism in humans and AHR has a regulatory role in basal and substrateinduced expression of target genes, including CYP1A1 and CYP1A2. 10,11
To identify additional loci, we conducted a staged genomewide (GW) meta-analysis of coffee consumption including over 120 000 coffee consumers sourced from population-based studies of European and African-American ancestry.
- Yang A, Palmer AA, de Wit H. "Genetics of caffeine consumption and responses to caffeine". Psychopharmacology 2010; 211: 245–257.
Supplementary Figure S1 depicts an overview of the current study. We performed a meta-analysis of GWAS summary statistics from 28 populationbased studies of European ancestry to detect single-nucleotide polymorphisms (SNPs) that are associated with coffee consumption. Top loci were followed-up in studies of European (13 studies) and African-American (7 studies) ancestry and confirmed loci were explored in a single Pakistani population. Detailed information on study design, participant characteristics, genotyping and imputation for all contributing studies are provided in the Supplementary Information and Supplementary Tables S1–S6.
Phenotype
All phenotype data were previously collected via interviewer- or selfadministered questionnaires (Supplementary Table S1). Our primary phenotype (‘phenotype 1’) was cups of predominately regular-type coffee consumed per day among coffee consumers. Coffee data collected categorically (for example, 2–3 cups per day) were converted to cups per day by taking the median value of each category (for example, 2.5 cups per day). A secondary analysis was performed comparing high with infrequent/non-coffee consumers (‘phenotype 2’). A subset of stage 1 studies collected information on decaffeinated coffee consumption; which was examined in follow-up analysis of the confirmed loci.
For both phenotypes, GW meta-analysis was conducted using a fixedeffects model and inverse-variance weighting with a single genomic control correction as implemented in METAL 12 and GWAMA 13 (r40.99 for correlation between METAL and GWAMA results). The phenotypic variance explained by additive SNP effects was estimated in the Women’s Genome Health Study (WGHS, n = 15 987 with identity-by-state o 0.025) using GCTA. 14 Stage 1 summary statistics were also subjected to pathway analysis using MAGENTA 15 (Supplementary Information).
Forty-four SNPs spanning thirty-three genomic regions met significance criteria for candidate associations and were followed-up in stage 2 (Supplementary Tables S8–S13). Eight loci, including six novel, met our criteria for GW significance (log 10 BF45.64) in a transethnic meta-analysis of all discovery and replication studies (Table 1; Supplementary Tables S14–S16; Supplementary Figures S7 and S8). Confirmed loci have effect sizes of 0.03–0.14 cups per day per allele and together explain ~ 1.3% of the phenotypic variance of coffee intake. We were underpowered to replicate these associations in a Pakistani population (Supplementary Information).
Nevertheless, the eight loci together explain ~ 1.3% of the phenotypic variance, a value at least as great as that reported for smoking behavior and alcohol consumption which are subjected to similar limitations in GWAS. 40,41 The additive genetic variance (or narrow-sense heritability) of coffee intake as estimated by GCTA in WGHS (7%) is considerably lower than estimates based on pedigrees (36–57%). 6 The marked discrepancies between the GCTA and pedigree estimates of heritability may be due to one or more of the following: the potential contribution of rare variants to heritability (not captured by GCTA’s ‘chip-based heritability’), biases in pedigree analysis resulting in overestimates of heritability, differences in phenotype ascertainment or definition and cultural differences in the populations studied. 42"
#coffee #gwas #genetics #behavioralgenetics
"Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption", The Coffee and Caffeine Genetics Consortium et al 2014 https://www.dropbox.com/s/0v7bzyzu1kjv0jo/2014-cornelis.pdf / http://sci-hub.org/downloads/8bca/cornelis2014.pdf
"We conducted a genome-wide (GW) meta-analysis of predominately regular-type coffee consumption (cups per day) among up to 91 462 coffee consumers of European ancestry with top single-nucleotide polymorphisms (SNPs) followed-up in ~ 30 062 and 7964 coffee consumers of European and African-American ancestry, respectively. Studies from both stages were combined in a trans-ethnic meta-analysis. Confirmed loci were examined for putative functional and biological relevance. Eight loci, including six novel loci, met GW significance (log 10 Bayes factor (BF)45.64) with per-allele effect sizes of 0.03–0.14 cups per day. Six are located in or near genes potentially involved in pharmacokinetics (ABCG2, AHR, POR and CYP1A2) and pharmacodynamics (BDNF and SLC6A4) of caffeine. Two map to GCKR and MLXIPL genes related to metabolic traits but lacking known roles in coffee consumption. Enhancer and promoter histone marks populate the regions of many confirmed loci and several potential regulatory SNPs are highly correlated with the lead SNP of each. SNP alleles near GCKR, MLXIPL, BDNF and CYP1A2 that were associated with higher coffee consumption have previously been associated with smoking initiation, higher adiposity and fasting insulin and glucose but lower blood pressure and favorable lipid, inflammatory and liver enzyme profiles (P o 5 × 10 − 8 ).Our genetic findings among European and African-American adults reinforce the role of caffeine in mediating habitual coffee consumption and may point to molecular mechanisms underlying inter-individual variability in pharmacological and health effects of coffee.
Heritability estimates for coffee and caffeine use range between 36 and 58%. 6 Genome-wide association studies (GWAS) of habitual caffeine and coffee intake have identified variants near CYP1A2 and aryl hydrocarbon receptor (AHR). 7–9 Cytochrome P450 (CYP)1A2 is responsible for ~ 95% of caffeine metabolism in humans and AHR has a regulatory role in basal and substrateinduced expression of target genes, including CYP1A1 and CYP1A2. 10,11
To identify additional loci, we conducted a staged genomewide (GW) meta-analysis of coffee consumption including over 120 000 coffee consumers sourced from population-based studies of European and African-American ancestry.
- Yang A, Palmer AA, de Wit H. "Genetics of caffeine consumption and responses to caffeine". Psychopharmacology 2010; 211: 245–257.
Supplementary Figure S1 depicts an overview of the current study. We performed a meta-analysis of GWAS summary statistics from 28 populationbased studies of European ancestry to detect single-nucleotide polymorphisms (SNPs) that are associated with coffee consumption. Top loci were followed-up in studies of European (13 studies) and African-American (7 studies) ancestry and confirmed loci were explored in a single Pakistani population. Detailed information on study design, participant characteristics, genotyping and imputation for all contributing studies are provided in the Supplementary Information and Supplementary Tables S1–S6.
Phenotype
All phenotype data were previously collected via interviewer- or selfadministered questionnaires (Supplementary Table S1). Our primary phenotype (‘phenotype 1’) was cups of predominately regular-type coffee consumed per day among coffee consumers. Coffee data collected categorically (for example, 2–3 cups per day) were converted to cups per day by taking the median value of each category (for example, 2.5 cups per day). A secondary analysis was performed comparing high with infrequent/non-coffee consumers (‘phenotype 2’). A subset of stage 1 studies collected information on decaffeinated coffee consumption; which was examined in follow-up analysis of the confirmed loci.
For both phenotypes, GW meta-analysis was conducted using a fixedeffects model and inverse-variance weighting with a single genomic control correction as implemented in METAL 12 and GWAMA 13 (r40.99 for correlation between METAL and GWAMA results). The phenotypic variance explained by additive SNP effects was estimated in the Women’s Genome Health Study (WGHS, n = 15 987 with identity-by-state o 0.025) using GCTA. 14 Stage 1 summary statistics were also subjected to pathway analysis using MAGENTA 15 (Supplementary Information).
Forty-four SNPs spanning thirty-three genomic regions met significance criteria for candidate associations and were followed-up in stage 2 (Supplementary Tables S8–S13). Eight loci, including six novel, met our criteria for GW significance (log 10 BF45.64) in a transethnic meta-analysis of all discovery and replication studies (Table 1; Supplementary Tables S14–S16; Supplementary Figures S7 and S8). Confirmed loci have effect sizes of 0.03–0.14 cups per day per allele and together explain ~ 1.3% of the phenotypic variance of coffee intake. We were underpowered to replicate these associations in a Pakistani population (Supplementary Information).
Nevertheless, the eight loci together explain ~ 1.3% of the phenotypic variance, a value at least as great as that reported for smoking behavior and alcohol consumption which are subjected to similar limitations in GWAS. 40,41 The additive genetic variance (or narrow-sense heritability) of coffee intake as estimated by GCTA in WGHS (7%) is considerably lower than estimates based on pedigrees (36–57%). 6 The marked discrepancies between the GCTA and pedigree estimates of heritability may be due to one or more of the following: the potential contribution of rare variants to heritability (not captured by GCTA’s ‘chip-based heritability’), biases in pedigree analysis resulting in overestimates of heritability, differences in phenotype ascertainment or definition and cultural differences in the populations studied. 42"
#coffee #gwas #genetics #behavioralgenetics
I've basically stopped bothering reading GWAS papers. This is a golden age for labs with large budgets to get irreproducible results published in Nature. I'll be back in twenty years when the dust has settled.Oct 12, 2014
What makes you think this will be irreproducible?Oct 12, 2014- Just prejudice, I'm afraid, :-) I didn't read it in detail.Oct 13, 2014
