Polygenic Score Analysis Research Articles

Gwas Meta-Analysis Reveals Novel Loci And Genetic Correlates For General Cognitive Function: A Report From The Cogent Consortium

Background The complex nature of the human cognitive phenotype has resulted in cognitive genomics lagging behind many other fields in terms of gene discovery using genome-wide association study (GWAS) methods. There were two major aims of the current study: (1) conduct a large-scale GWAS meta-analysis of general cognitive function in 24 independent cohorts (N=35,298), to identify SNP-based and gene-based loci associated with cognition; and (2) determine the extent of genetic correlation between general cognitive function and published neurobehavioral phenotypes of interest. These aims were executed within the context of the Cognitive Genomics Consortium (COGENT), an international collaborative effort designed to study the molecular genetics of cognitive function. Methods To date, COGENT has acquired individual-level neuropsychological, demographic, clinical and SNP array data from 24 studies (comprised of 35 sub-cohorts) with 35,298 individuals (46.8% females, mean age of 45.3±8.6 years) of European ancestry drawn from the general population. Genotype data underwent common QC and imputation procedures, resulting in ~8M high-quality SNPs. The GWAS phenotype was general cognitive function (“g”), derived from the first principal component of a PCA performed on an average of 8±4 neuropsychological tests. Allelic association analysis was conducted with imputed allele dosages using Plink 1.9, except for 8 sub-cohorts including related individuals, which were analyzed with BOLT-LMM. GWAS results were combined for meta-analysis using the inverse-variance weighted Z-score method in METAL, with subsequebt gene-based analysis using MAGMA Additionally, we utilized individual SNP lookups and polygenic score analyses (using the LD score regression method) to identify genetic overlap with other relevant neurobehavioral phenotypes. Results Our primary GWAS meta-analysis identified two novel SNP loci associated with cognitive performance at the genomewide significance level (P Discussion These data provide new insight into the genetics of neurocognitive function that are applicable to genetic research of neuropsychiatric illness. Novel genes implicated include CENPO, TP53, ATXN7L2, ARPP21, and RPL31P12. Our results also support several loci derived from the recent CHARGE meta-analysis of general cognitive function, the UK Biobank GWAS of verbal-numerical reasoning, and the SSGAC analysis of educational attainment. Polygenic overlap analyses demonstrate the significance of understanding the genetics of general cognitive function to unraveling the etiology of numerous psychiatric illness and health-relevant conditions.

Heritability of Working in a Creative Profession

Creativity is the tendency to generate or recognize ideas, alternatives, or possibilities. Following a study on the genetic contribution to working in a creative profession, based on polygenic score analysis, we report the total heritability of this trait in a large sample of adult twins and their siblings registered with the Netherlands Twin Register. Data from 6755 twins and 1817 siblings were analyzed using genetic structural equation modeling. Working in a creative profession is relatively rare in our sample (2.6% of twins and 3.2% of siblings). Twin correlations (identical 0.68 and fraternal 0.40) commended a model with additive genetic factors (full model estimate 0.56), shared (full model estimate 0.12), and unique environmental factors (full model estimate 0.32). Genetic model fitting resulted in a best-fitting model existing of additive genetic factors and unique environmental factors, resulting in a heritability of 0.70.

Common susceptibility variants are shared between schizophrenia and psoriasis in the Han Chinese population.

Previous studies have shown that individuals with schizophrenia have a greater risk for psoriasis than a typical person. This suggests that there might be a shared genetic etiology between the 2 conditions. We aimed to characterize the potential shared genetic susceptibility between schizophrenia and psoriasis using genome-wide marker genotype data. We obtained genetic data on individuals with psoriasis, schizophrenia and control individuals. We applied a marker-based coheritability estimation procedure, polygenic score analysis, a gene set enrichment test and a least absolute shrinkage and selection operator regression model to estimate the potential shared genetic etiology between the 2 diseases. We validated the results in independent schizophrenia and psoriasis cohorts from Singapore. We included 1139 individuals with psoriasis, 744 with schizophrenia and 1678 controls in our analysis, and we validated the results in independent cohorts, including 441 individuals with psoriasis (and 2420 controls) and 1630 with schizophrenia (and 1860 controls). We estimated that a large fraction of schizophrenia and psoriasis risk could be attributed to common variants (h2SNP = 29% ± 5.0%, p = 2.00 × 10-8), with a coheritability estimate between the traits of 21%. We identified 5 variants within the human leukocyte antigen (HLA) gene region, which were most likely to be associated with both diseases and collectively conferred a significant risk effect (odds ratio of highest risk quartile = 6.03, p < 2.00 × 10-16). We discovered that variants contributing most to the shared heritable component between psoriasis and schizophrenia were enriched in antigen processing and cell endoplasmic reticulum. Our sample size was relatively small. The findings of 5 HLA gene variants were complicated by the complex structure in the HLA region. We found evidence for a shared genetic etiology between schizophrenia and psoriasis. The mechanism for this shared genetic basis likely involves immune and calcium signalling pathways.

Genome-wide Association for Major Depression Through Age at Onset Stratification: Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium

BackgroundMajor depressive disorder (MDD) is a disabling mood disorder, and despite a known heritable component, a large meta-analysis of genome-wide association studies revealed no replicable genetic risk variants. Given prior evidence of heterogeneity by age at onset in MDD, we tested whether genome-wide significant risk variants for MDD could be identified in cases subdivided by age at onset. MethodsDiscovery case-control genome-wide association studies were performed where cases were stratified using increasing/decreasing age-at-onset cutoffs; significant single nucleotide polymorphisms were tested in nine independent replication samples, giving a total sample of 22,158 cases and 133,749 control subjects for subsetting. Polygenic score analysis was used to examine whether differences in shared genetic risk exists between earlier and adult-onset MDD with commonly comorbid disorders of schizophrenia, bipolar disorder, Alzheimer’s disease, and coronary artery disease. ResultsWe identified one replicated genome-wide significant locus associated with adult-onset (>27 years) MDD (rs7647854, odds ratio: 1.16, 95% confidence interval: 1.11–1.21, p = 5.2 × 10-11). Using polygenic score analyses, we show that earlier-onset MDD is genetically more similar to schizophrenia and bipolar disorder than adult-onset MDD. ConclusionsWe demonstrate that using additional phenotype data previously collected by genetic studies to tackle phenotypic heterogeneity in MDD can successfully lead to the discovery of genetic risk factor despite reduced sample size. Furthermore, our results suggest that the genetic susceptibility to MDD differs between adult- and earlier-onset MDD, with earlier-onset cases having a greater genetic overlap with schizophrenia and bipolar disorder.

Genome-wide association study of cognitive functions and educational attainment in UK Biobank (N=112 151).

People's differences in cognitive functions are partly heritable and are associated with important life outcomes. Previous genome-wide association (GWA) studies of cognitive functions have found evidence for polygenic effects yet, to date, there are few replicated genetic associations. Here we use data from the UK Biobank sample to investigate the genetic contributions to variation in tests of three cognitive functions and in educational attainment. GWA analyses were performed for verbal–numerical reasoning (N=36 035), memory (N=112 067), reaction time (N=111 483) and for the attainment of a college or a university degree (N=111 114). We report genome-wide significant single-nucleotide polymorphism (SNP)-based associations in 20 genomic regions, and significant gene-based findings in 46 regions. These include findings in the ATXN2, CYP2DG, APBA1 and CADM2 genes. We report replication of these hits in published GWA studies of cognitive function, educational attainment and childhood intelligence. There is also replication, in UK Biobank, of SNP hits reported previously in GWA studies of educational attainment and cognitive function. GCTA-GREML analyses, using common SNPs (minor allele frequency>0.01), indicated significant SNP-based heritabilities of 31% (s.e.m.=1.8%) for verbal–numerical reasoning, 5% (s.e.m.=0.6%) for memory, 11% (s.e.m.=0.6%) for reaction time and 21% (s.e.m.=0.6%) for educational attainment. Polygenic score analyses indicate that up to 5% of the variance in cognitive test scores can be predicted in an independent cohort. The genomic regions identified include several novel loci, some of which have been associated with intracranial volume, neurodegeneration, Alzheimer's disease and schizophrenia.

Common polygenic variation enhances risk prediction for Alzheimer's disease.

The identification of subjects at high risk for Alzheimer's disease is important for prognosis and early intervention. We investigated the polygenic architecture of Alzheimer's disease and the accuracy of Alzheimer's disease prediction models, including and excluding the polygenic component in the model. This study used genotype data from the powerful dataset comprising 17 008 cases and 37 154 controls obtained from the International Genomics of Alzheimer's Project (IGAP). Polygenic score analysis tested whether the alleles identified to associate with disease in one sample set were significantly enriched in the cases relative to the controls in an independent sample. The disease prediction accuracy was investigated in a subset of the IGAP data, a sample of 3049 cases and 1554 controls (for whom APOE genotype data were available) by means of sensitivity, specificity, area under the receiver operating characteristic curve (AUC) and positive and negative predictive values. We observed significant evidence for a polygenic component enriched in Alzheimer's disease (P = 4.9 × 10(-26)). This enrichment remained significant after APOE and other genome-wide associated regions were excluded (P = 3.4 × 10(-19)). The best prediction accuracy AUC = 78.2% (95% confidence interval 77-80%) was achieved by a logistic regression model with APOE, the polygenic score, sex and age as predictors. In conclusion, Alzheimer's disease has a significant polygenic component, which has predictive utility for Alzheimer's disease risk and could be a valuable research tool complementing experimental designs, including preventative clinical trials, stem cell selection and high/low risk clinical studies. In modelling a range of sample disease prevalences, we found that polygenic scores almost doubles case prediction from chance with increased prediction at polygenic extremes.

Systematic Evaluation of Genetic Variants for Polycystic Ovary Syndrome in a Chinese Population.

To date, eleven genome-wide significant (GWS) loci (P < 5×10−8) for polycystic ovary syndrome (PCOS) have been identified through genome-wide association studies (GWAS). Some of the risk loci have been selected for replications and validated in multiple ethnicities, however, few previous studies investigated all loci. Scanning all the GWAS variants would demonstrate a more informative profile of variance they explained. Thus, we analyzed all the 17 single nucleotide polymorphisms (SNPs) mapping to the 11 GWAS loci in an independent sample set of 800 Chinese subjects with PCOS and 1110 healthy controls systematically. Variants of rs3802457 in C9orf3 locus (P = 5.99×10−4) and rs13405728 in LHCGR locus (P = 3.73×10−4) were significantly associated with PCOS after the strict Bonferroni correction in our data set. The further haplotype analysis indicated that in the block of C9orf3 gene (rs4385527 and rs3802457), GA haplotype played a protective role in PCOS (8.7 vs 5.0, P = 9.85×10−6, OR = 0.548, 95%CI = 0.418–0.717), while GG haplotype was found suffering from an extraordinarily increased risk of PCOS (73.6% vs79.2%, P = 3.41×10−5, OR = 1.394, 95%CI = 1.191–1.632). Moreover, the directions of effects for all SNPs were consistent with previous GWAS reports (P = 1.53×10−5). Polygenic score analysis demonstrated that these 17 SNPs have a significant capacity on predicting case-control status in our samples (P = 7.17×10−9), meanwhile all these gathered 17 SNPs explained about 2.40% of variance. Our findings supported that C9orf3 and LHCGR loci variants were vital susceptibility of PCOS.

Phenome-wide analysis of genome-wide polygenic scores.

Genome-wide polygenic scores (GPS), which aggregate the effects of thousands of DNA variants from genome-wide association studies (GWAS), have the potential to make genetic predictions for individuals. We conducted a systematic investigation of associations between GPS and many behavioral traits, the behavioral phenome. For 3152 unrelated 16-year-old individuals representative of the United Kingdom, we created 13 GPS from the largest GWAS for psychiatric disorders (for example, schizophrenia, depression and dementia) and cognitive traits (for example, intelligence, educational attainment and intracranial volume). The behavioral phenome included 50 traits from the domains of psychopathology, personality, cognitive abilities and educational achievement. We examined phenome-wide profiles of associations for the entire distribution of each GPS and for the extremes of the GPS distributions. The cognitive GPS yielded stronger predictive power than the psychiatric GPS in our UK-representative sample of adolescents. For example, education GPS explained variation in adolescents' behavior problems (~0.6%) and in educational achievement (~2%) but psychiatric GPS were associated with neither. Despite the modest effect sizes of current GPS, quantile analyses illustrate the ability to stratify individuals by GPS and opportunities for research. For example, the highest and lowest septiles for the education GPS yielded a 0.5 s.d. difference in mean math grade and a 0.25 s.d. difference in mean behavior problems. We discuss the usefulness and limitations of GPS based on adult GWAS to predict genetic propensities earlier in development.

Longevity GWAS Using the Drosophila Genetic Reference Panel.

We used 197 Drosophila melanogaster Genetic Reference Panel (DGRP) lines to perform a genome-wide association analysis for virgin female lifespan, using ~2M common single nucleotide polymorphisms (SNPs). We found considerable genetic variation in lifespan in the DGRP, with a broad-sense heritability of 0.413. There was little power to detect signals at a genome-wide level in single-SNP and gene-based analyses. Polygenic score analysis revealed that a small proportion of the variation in lifespan (~4.7%) was explicable in terms of additive effects of common SNPs (≥2% minor allele frequency). However, several of the top associated genes are involved in the processes previously shown to impact ageing (eg, carbohydrate-related metabolism, regulation of cell death, proteolysis). Other top-ranked genes are of unknown function and provide promising candidates for experimental examination. Genes in the target of rapamycin pathway (TOR; Chrb, slif, mipp2, dredd, RpS9, dm) contributed to the significant enrichment of this pathway among the top-ranked 100 genes (p = 4.79×10−06). Gene Ontology analysis suggested that genes involved in carbohydrate metabolism are important for lifespan; including the InterPro term DUF227, which has been previously associated with lifespan determination. This analysis suggests that our understanding of the genetic basis of natural variation in lifespan from induced mutations is incomplete.

Polygenic risk of Parkinson disease is correlated with disease age at onset.

ObjectiveWe have investigated the polygenic architecture of Parkinson disease (PD) and have also explored the potential relationship between an individual's polygenic risk score and their disease age at onset.MethodsThis study used genotypic data from 4,294 cases and 10,340 controls obtained from the meta‐analysis of PD genome‐wide association studies. Polygenic score analysis was performed as previously described by the International Schizophrenia Consortium, testing whether the polygenic score alleles identified in 1 association study were significantly enriched in the cases relative to the controls of 3 independent studies. Linear regression was used to investigate the relationship between an individual's polygenic score for PD risk alleles and disease age at onset.ResultsOur polygenic score analysis has identified significant evidence for a polygenic component enriched in the cases of each of 3 independent PD genome‐wide association cohorts (minimum p = 3.76 × 10−6). Further analysis identified compelling evidence that the average polygenic score in patients with an early disease age at onset was significantly higher than in those with a late age at onset (p = 0.00014).InterpretationThis provides strong support for a large polygenic contribution to the overall heritable risk of PD and also suggests that early onset forms of the illness are not exclusively caused by highly penetrant Mendelian mutations, but can also be contributed to by an accumulation of common polygenic alleles with relatively low effect sizes. Ann Neurol 2015;77:582–591

Polygenic risk, stressful life events and depressive symptoms in older adults: a polygenic score analysis.

Previous studies suggest that the relationship between genetic risk and depression may be moderated by stressful life events (SLEs). The goal of this study was to assess whether SLEs moderate the association between polygenic risk of major depressive disorder (MDD) and depressive symptoms in older adults. We used logistic and negative binomial regressions to assess the associations between polygenic risk, SLEs and depressive symptoms in a sample of 8761 participants from the Health and Retirement Study. Polygenic scores were derived from the Psychiatric Genomics Consortium genome-wide association study of MDD. SLEs were operationalized as a dichotomous variable indicating whether participants had experienced at least one stressful event during the previous 2 years. Depressive symptoms were measured using an eight-item Center for Epidemiologic Studies Depression Scale subscale and operationalized as both a dichotomous and a count variable. The odds of reporting four or more depressive symptoms were over twice as high among individuals who experienced at least one SLE (odds ratio 2.19, 95% confidence interval 1.86-2.58). Polygenic scores were significantly associated with depressive symptoms (β = 0.21, p ⩽ 0.0001), although the variance explained was modest (pseudo r 2 = 0.0095). None of the interaction terms for polygenic scores and SLEs was statistically significant. Polygenic risk and SLEs are robust, independent predictors of depressive symptoms in older adults. Consistent with an additive model, we found no evidence that SLEs moderated the association between common variant polygenic risk and depressive symptoms.

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD. The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders. Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01). Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.

Genomic predictors of combat stress vulnerability and resilience in U.S. Marines: A genome-wide association study across multiple ancestries implicates PRTFDC1 as a potential PTSD gene

Research on the etiology of post-traumatic stress disorder (PTSD) has rapidly matured, moving from candidate gene studies to interrogation of the entire human genome in genome-wide association studies (GWAS). Here we present the results of a GWAS performed on samples from combat-exposed U.S. Marines and Sailors from the Marine Resiliency Study (MRS) scheduled for deployment to Iraq and/or Afghanistan. The MRS is a large, prospective study with longitudinal follow-up designed to identify risk and resiliency factors for combat-induced stress-related symptoms. Previously implicated PTSD risk loci from the literature and polygenic risk scores across psychiatric disorders were also evaluated in the MRS cohort. Participants (N=3494) were assessed using the Clinician-Administered PTSD Scale and diagnosed using the DSM-IV diagnostic criterion. Subjects with partial and/or full PTSD diagnosis were called cases, all other subjects were designated controls, and study-wide maximum CAPS scores were used for longitudinal assessments. Genomic DNA was genotyped on the Illumina HumanOmniExpressExome array. Individual genetic ancestry was determined by supervised cluster analysis for subjects of European, African, Hispanic/Native American, and other descent. To test for association of SNPs with PTSD, logistic regressions were performed within each ancestry group and results were combined in meta-analyses. Measures of childhood and adult trauma were included to test for gene-by-environment (GxE) interactions. Polygenic risk scores from the Psychiatric Genomic Consortium were used for major depressive disorder (MDD), bipolar disorder (BPD), and schizophrenia (SCZ). The array produced >800K directly genotyped and >21M imputed markers in 3494 unrelated, trauma-exposed males, of which 940 were diagnosed with partial or full PTSD. The GWAS meta-analysis identified the phosphoribosyl transferase domain containing 1 gene (PRTFDC1) as a genome-wide significant PTSD locus (rs6482463; OR=1.47, SE=0.06, p=2.04×10(-9)), with a similar effect across ancestry groups. Association of PRTFDC1 with PTSD in an independent military cohort showed some evidence for replication. Loci with suggestive evidence of association (n=25 genes, p<5×10(-6)) further implicated genes related to immune response and the ubiquitin system, but these findings remain to be replicated in larger GWASs. A replication analysis of 25 putative PTSD genes from the literature found nominally significant SNPs for the majority of these genes, but associations did not remain significant after correction for multiple comparison. A cross-disorder analysis of polygenic risk scores from GWASs of BPD, MDD, and SCZ found that PTSD diagnosis was associated with risk sores of BPD, but not with MDD or SCZ. This first multi-ethnic/racial GWAS of PTSD highlights the potential to increase power through meta-analyses across ancestry groups. We found evidence for PRTFDC1 as a potential novel PTSD gene, a finding that awaits further replication. Our findings indicate that the genetic architecture of PTSD may be determined by many SNPs with small effects, and overlap with other neuropsychiatric disorders, consistent with current findings from large GWAS of other psychiatric disorders.

Replication of previous genome-wide association studies of psychiatric diseases in a large schizophrenia case–control sample from Spain

Genome wide association studies (GWAS) has allowed the discovery of some interesting risk variants for schizophrenia (SCZ). However, this high-throughput approach presents some limitations, being the most important the necessity of highly restrictive statistical corrections as well as the loss of statistical power inherent to the use of a Single Nucleotide Polymorphism (SNP) analysis approach. These problems can be partially solved through the use of a polygenic approach. We performed a genotyping study in SCZ using 86 previously associated SNPs identified by GWAS of SCZ, bipolar disorder (BPD) and autistic spectrum disorder (ASD) patients. The sample consisted of 3063 independent cases with DSM-IV-TR diagnosis of SCZ and 2847 independent controls of European origin from Spain. A polygenic score analysis was also used to test the overall effect on the SCZ status. One SNP, rs12290811, located in the ODZ4 gene reached statistical significance (p=1.7×10−4, Allelic odds ratio=1.21), a value very near to those reported in previous GWAS of BPD patients. In addition, 4 SNPs were close to the significant threshold: rs3850333, in the NRXN1 gene; rs6932590, at MHC; rs2314398, located in an intergenic region on chromosome 2; and rs1006737, in the CACNA1C gene. We also found that 74% of the studied SNPs showed the same tendency (risk or protection alleles) previously reported in the original GWAS (p<0.001). Our data strengthen the polygenic component of susceptibility to SCZ. Our findings show ODZ4 as a risk gene for SCZ, emphasizing the existence of common vulnerability in psychosis.

Muscle tenderness and psychiatric comorbidity: a vicious cycle in migraine chronicization.

Muscle tenderness and psychiatric comorbidity: a vicious cycle in migraine chronicization.

Genetic relationships between suicide attempts, suicidal ideation and major psychiatric disorders: A genome‐wide association and polygenic scoring study

Epidemiological studies have recognized a genetic diathesis for suicidal behavior, which is independent of other psychiatric disorders. Genome-wide association studies (GWAS) on suicide attempt (SA) and ideation have failed to identify specific genetic variants. Here, we conduct further GWAS and for the first time, use polygenic score analysis in cohorts of patients with mood disorders, to test for common genetic variants for mood disorders and suicide phenotypes. Genome-wide studies for SA were conducted in the RADIANT and GSK-Munich recurrent depression samples and London Bipolar Affective Disorder Case-Control Study (BACCs) then meta-analysis was performed. A GWAS on suicidal ideation during antidepressant treatment had previously been conducted in the Genome Based Therapeutic Drugs for Depression (GENDEP) study. We derived polygenic scores from each sample and tested their ability to predict SA in the mood disorder cohorts or ideation status in the GENDEP study. Polygenic scores for major depressive disorder, bipolar disorder and schizophrenia from the Psychiatric Genomics Consortium were used to investigate pleiotropy between psychiatric disorders and suicide phenotypes. No significant evidence for association was detected at any SNP in GWAS or meta-analysis. Polygenic scores for major depressive disorder significantly predicted suicidal ideation in the GENDEP pharmacogenetics study and also predicted SA in a combined validation dataset. Polygenic scores for SA showed no predictive ability for suicidal ideation. Polygenic score analysis suggests pleiotropy between psychiatric disorders and suicidal ideation whereas the tendency to act on such thoughts may have a partially independent genetic diathesis. © 2014 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics published by Wiley Periodicals, Inc.

Single-marker and multi-marker mixed models for polygenic score analysis in family-based data

Genome-wide association studies have proven successful but they remain underpowered for detecting variants of weaker effect. Alternative methods propose to test for association by using an aggregate score that combines the effects of the most associated variants. The set of variants that are to be aggregated may come from either of two modeling approaches: single-marker or multi-marker. The goal of this paper is to evaluate this alternative strategy by using sets of single-nucleotide polymorphisms identified by the two modeling approaches in the simulated pedigree data set provided for the Genetic Analysis Workshop 18. We focused on quantitative traits association analysis of diastolic blood pressure and of Q1, which served to control the statistical significance of our results. We carried out all analyses with knowledge of the underlying simulation model. We found that the probability to replicate association with the aggregate score depends on the single-nucleotide polymorphism set size and, for smaller sets (≤100), on the modeling approach. Nonetheless, assessing the statistical significance of these results in this data set was challenging, likely because of linkage because we are analyzing pedigree data, and also because the genotypes were the same across the replicates. Further methods need to be developed to facilitate the application of this alternative strategy in pedigree data.

Genetic risk score analysis indicates migraine with and without comorbid depression are genetically different disorders.

Migraine and major depressive disorder (MDD) are comorbid, moderately heritable and to some extent influenced by the same genes. In a previous paper, we suggested the possibility of causality (one trait causing the other) underlying this comorbidity. We present a new application of polygenic (genetic risk) score analysis to investigate the mechanisms underlying the genetic overlap of migraine and MDD. Genetic risk scores were constructed based on data from two discovery samples in which genome-wide association analyses (GWA) were performed for migraine and MDD, respectively. The Australian Twin Migraine GWA study (N = 6,350) included 2,825 migraine cases and 3,525 controls, 805 of whom met the diagnostic criteria for MDD. The RADIANT GWA study (N = 3,230) included 1,636 MDD cases and 1,594 controls. Genetic risk scores for migraine and for MDD were used to predict pure and comorbid forms of migraine and MDD in an independent Dutch target sample (NTR-NESDA, N = 2,966), which included 1,476 MDD cases and 1,058 migraine cases (723 of these individuals had both disorders concurrently). The observed patterns of prediction suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid MDD and migraine were genetically most similar to MDD patients. These results indicate that in at least a subset of migraine patients with MDD, migraine may be a symptom or consequence of MDD.

Evidence for a polygenic contribution to androgenetic alopecia

Male pattern baldness (androgenetic alopecia, AGA) is a highly heritable trait and the most common form of hair loss in humans. Eight genome-wide significant risk loci for AGA have been identified. To determine whether a polygenic component contributes to the genetic risk for AGA. This study used a German case-control sample for AGA, which comprised 581 severely affected patients and 617 controls, to determine the contribution of polygenic variance to AGA risk. The sample was divided evenly into discovery and test samples. An additive polygenic risk score was calculated from risk alleles with increasingly liberal P-values in the discovery dataset, which was then used to test for the enrichment of AGA risk score alleles in the independent test samples. The polygenic score analysis provided significant evidence for a polygenic contribution to AGA where the amount of variance explained was 1·4-4·5%. This study provides evidence for the specific contribution of a polygenic component to the overall heritable risk for AGA. To some degree, the polygenic architecture of AGA might reflect the complexity of the biological pathways involved. Further analyses and strategies that complement conventional genome-wide association studies are needed to identify these factors. These may include pathway-based analyses, the analysis of functional candidate genes and tests for epistatic effects with known loci.

A Genome-wide Association Analysis of a Broad Psychosis Phenotype Identifies Three Loci for Further Investigation

BackgroundGenome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories.Methods1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls).ResultsNo individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium’s panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10–14) and explained approximately 2% of the phenotypic variance.ConclusionsAlthough narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data.