Pamela A. F. Madden

Common SNPs explain a large proportion of the heritability for human height

SNPs discovered by genome-wide association studies (GWASs) account for only a small fraction of the genetic variation of complex traits in human populations. Where is the remaining heritability? We estimated the proportion of variance for human height explained by 294,831 SNPs genotyped on 3,925 unrelated individuals using a linear model analysis, and validated the estimation method with simulations based on the observed genotype data. We show that 45% of variance can be explained by considering all SNPs simultaneously. Thus, most of the heritability is not missing but has not previously been detected because the individual effects are too small to pass stringent significance tests. We provide evidence that the remaining heritability is due to incomplete linkage disequilibrium between causal variants and genotyped SNPs, exacerbated by causal variants having lower minor allele frequency than the SNPs explored to date.

Conditional and joint multiple-SNP analysis of GWAS summary statistics identifies additional variants influencing complex traits

We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.

Genome-wide meta-analysis identifies new susceptibility loci for migraine

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P < 5 × 10−8). Five loci are new: near AJAP1 at 1p36, near TSPAN2 at 1p13, within FHL5 at 6q16, within C7orf10 at 7p14 and near MMP16 at 8q21. Three of these loci were identified in disease subgroup analyses. Brain tissue expression quantitative trait locus analysis suggests potential functional candidate genes at four loci: APOA1BP, TBC1D7, FUT9, STAT6 and ATP5B.

A Genetically Informed Study of the Processes Underlying the Association Between Parental Marital Instability and Offspring Adjustment

Parental divorce is associated with problematic offspring adjustment, but the relation may be due to shared genetic or environmental factors. One way to test for these confounds is to study offspring of twins discordant for divorce. The current analyses used this design to separate the mechanisms responsible for the association between parental divorce, experienced either before or after the age of 16, and offspring well-being. The results were consistent with a causal role of divorce in earlier initiation of sexual intercourse and emotional difficulties, in addition to a greater probability of educational problems, depressed mood, and suicidal ideation. In contrast, the increased risk for cohabitation and earlier initiation of drug use was explained by selection factors, including genetic confounds. ((c) 2006 APA, all rights reserved).

Effects of Maternal Smoking during Pregnancy on Offspring Externalizing Problems: Contextual Effects in a Sample of Female Twins

Studies of maternal smoking during pregnancy (MSDP) suggest increased risk for cognitive impairment and psychiatric outcomes. However, it is uncertain whether these associations are the direct result of MSDP or related to confounding familial variables associated with MSDP. The current study employed propensity score analysis to examine the effects of MSDP on offspring EXT using data from a large sample of 979 unrelated mothers. Logistic regression models were used to determine the propensity that the offspring of these mothers were likely to be exposed to MSDP [i.e., smoked during only the first trimester (MSDP-EARLY[E]) or smoked throughout their pregnancy (MSDP-THROUGHOUT[T])] given known familial confounders. Analyses focused on the effect of MSDP-E/T on the EXT behavior in offspring of these mothers (Nxa0=xa01616) were conducted across the distribution of liability for MSDP-E/T and at different levels of risk for MSDP-E/T. MSDP-E/T was associated with offspring EXT problems, but the effects were partly confounded by the familial liability for MSDP. Further, the observed effects were not consistent across all levels of the MSDP risk distribution. These findings suggest a direct association between MSDP and offspring EXT behaviors, and that varied associations observed across studies may be the result of differences in the level of familial confounders that also have an effect on offspring EXT.

Does Childhood Trauma Moderate Polygenic Risk for Depression?: A Meta-analysis of 5765 Subjects From the Psychiatric Genomics Consortium

BACKGROUNDnThe heterogeneity of genetic effects on major depressive disorder (MDD) may be partly attributable to moderation of genetic effects by environment, such as exposure to childhood trauma (CT). Indeed, previous findings in two independent cohorts showed evidence for interaction between polygenic risk scores (PRSs) and CT, albeit in opposing directions. This study aims to meta-analyze MDD-PRSxa0× CT interaction results across these two and other cohorts, while applying more accurate PRSs based on a larger discovery sample.nnnMETHODSnData were combined from 3024 MDD cases and 2741 control subjects from nine cohorts contributing to the MDD Working Group of the Psychiatric Genomics Consortium. MDD-PRS were based on a discovery sample of ∼110,000 independent individuals. CT was assessed as exposure to sexual or physical abuse during childhood. In a subset of 1957 cases and 2002 control subjects, a more detailed five-domain measure additionally included emotional abuse, physical neglect, and emotional neglect.nnnRESULTSnMDD was associated with the MDD-PRS (odds ratio [OR]xa0= 1.24, pxa0= 3.6xa0× 10-5, R2xa0= 1.18%) and with CT (ORxa0= 2.63, pxa0= 3.5xa0× 10-18 and ORxa0= 2.62, pxa0= 1.4xa0×10-5 for the two- and five-domain measures, respectively). No interaction was found between MDD-PRS and the two-domain and five-domain CT measure (ORxa0= 1.00, pxa0= .89 and ORxa0= 1.05, pxa0= .66).nnnCONCLUSIONSnNo meta-analytic evidence for interaction between MDD-PRS and CT was found. This suggests that the previously reported interaction effects, although both statistically significant, can best be interpreted as chance findings. Further research is required, but this study suggests that the genetic heterogeneity of MDD is not attributable to genome-wide moderation of genetic effects by CT.

Adolescent cannabis use and repeated voluntary unprotected sex in women

BACKGROUND AND AIMSnSubstance use has been implicated in the onset and maintenance of risky sexual behaviors, which have particularly devastating consequences in young women. This study examined whether (i) adolescent onset of cannabis use is associated with repeated voluntary unprotected sex in women and (ii) whether this association persists after accounting for correlated familial influences.nnnDESIGNnGeneral population sample of female twins.nnnSETTINGnMidwestern United States.nnnPARTICIPANTSnA total of 2784 sexually active twin women (15.5% African American) aged 18-27xa0years (assessed 2002-05), including 119 dizygotic (DZ) and 115 monozygotic (MZ) discordant pairs.nnnMEASUREMENTSnSelf-report interview data on cannabis use that first occurred prior to age 17 (27.1%) and repeated voluntary unprotected sex (27.2%). Key covariates included early onset of regular drinking, regular smoking, sexual debut and menstruation as well as conduct disorder symptoms and childhood sexual abuse.nnnFINDINGSnCompared with never users and those who started using cannabis at a later age, adolescent cannabis users were more likely to report repeated voluntary unprotected sex [odds ratio (OR)xa0=xa02.69; 95% confidence interval (CI)xa0=xa02.24-3.22]. Genetic (rg xa0=xa00.57, 95% CIxa0=xa00.38-0.87) and non-shared environmental (re xa0=xa00.21, 95% CIxa0=xa00.02-0.38) factors contributed to the association. After accounting for correlated familial factors, there was a consistent elevation in the likelihood of repeated voluntary unprotected sex in the exposed twin relative to her genetically identical never/late-onset user co-twin (unadjusted ORxa0=xa02.25, 95% CIxa0=xa01.14-4.44), even after adjustment for covariates (adjusted ORxa0=xa02.27, 95% CIxa0=xa01.08-4.80).nnnCONCLUSIONSnWomen who start using cannabis during adolescence appear to be more likely to report voluntary engagement in repeated unprotected sex than women who never use cannabis or who initiate cannabis use after adolescence. The results appear to be independent of shared genetic influences.

Trans-ethnic genome-wide association study provides insight into effector genes and molecular mechanisms for kidney function and highlights a causal effect on kidney-specific disease aetiologies

Chronic kidney disease (CKD) affects ∼10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS)1-3 of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for protein-coding exons, kidney-specific histone modifications, and transcription factor binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations and highlighted potential causal genes with cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) supported causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure (DBP) and hypertension. These results define novel molecular mechanisms and effector genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.Chronic kidney disease (CKD) affects ~10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS) of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for coding exons, kidney-specific histone modifications, and binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations, and highlighted potential causal genes with kidney cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) highlighted causal effects of eGFR on overall and cause-specific CKD, kidney stone formation and diastolic blood pressure (DBP). These results define novel molecular mechanisms and effector genes for eGFR, offering insight into downstream clinical outcomes and potential routes to CKD treatment development.

Exome chip meta-analysis elucidates the genetic architecture of rare coding variants in smoking and drinking behavior

Background Smoking and alcohol use behaviors in humans have been associated with common genetic variants within multiple genomic loci. Investigation of rare variation within these loci holds promise for identifying causal variants impacting biological mechanisms in the etiology of disordered behavior. Microarrays have been designed to genotype rare nonsynonymous and putative loss of function variants. Such variants are expected to have greater deleterious consequences on gene function than other variants, and significantly contribute to disease risk. Methods In the present study, we analyzed ∼250,000 rare variants from 17 independent studies. Each variant was tested for association with five addiction-related phenotypes: cigarettes per day, pack years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted single variant tests of all variants, and gene-based burden tests of nonsynonymous or putative loss of function variants with minor allele frequency less than 1%. Results Meta-analytic sample sizes ranged from 70,847 to 164,142 individuals, depending on the phenotype. Known loci tagged by common variants replicated, but there was no robust evidence for individually associated rare variants, either in gene based or single variant tests. Using a modified method-of-moment approach, we found that all low frequency coding variants, in aggregate, contributed 1.7% to 3.6% of the phenotypic variation for the five traits (p<.05). Conclusions The findings indicate that rare coding variants contribute to phenotypic variation, but that much larger samples and/or denser genotyping of rare variants will be required to successfully identify associations with these phenotypes, whether individual variants or gene‐ based associations.