Genome-wide association studies (GWAS) implicate single nucleotide polymorphisms (SNPs) on chromosome 6p21.3-22.1, the human leukocyte antigen (HLA) region, as common risk factors for schizophrenia (SZ). Other studies implicate viral and protozoan exposure. Our study tests chromosome 6p SNPs for effects on SZ risk with and without exposure. Method: GWAS-significant SNPs and ancestry-informative marker SNPs were analyzed among African American patients with SZ (n = 604) and controls (n = 404). Exposure to herpes simplex virus, type 1 (HSV-1), cytomegalovirus (CMV), and Toxoplasma gondii (TOX) was assayed using specific antibody assays. Results: Five SNPs were nominally associated with SZ, adjusted for population admixture (P < .05, uncorrected for multiple comparisons). These SNPs were next analyzed in relation to infectious exposure. Multivariate analysis indicated significant association between rs3130297 genotype and HSV-1 exposure; the associated allele was different from the SZ risk allele. Conclusions: We propose a model for the genesis of SZ incorporating genomic variation in the HLA region and neurotropic viral exposure for testing in additional, independent African American samples.
HLA; gene; HSV-1; cytomegalovirus; schizophrenia; African American; kwd>
We evaluated the hypothesis that dopaminergic polymorphisms are risk factors for schizophrenia (SZ). In stage I, we screened 18 dopamine-related genes in two independent US Caucasian samples: 150 trios and 328 cases/501 controls. The most promising associations were detected with SLC6A3 (alias DAT), DRD3, COMT and SLC18A2 (alias VMAT2). In stage II, we comprehensively evaluated these four genes by genotyping 68 SNPs in all 478 cases and 501 controls from stage I. Fifteen (23.1%) significant associations were found (p ≤ 0.05). We sought epistasis between pairs of SNPs providing evidence of a main effect and observed 17 significant interactions (169 tests); 41.2% of significant interactions involved rs3756450 (5′ near promoter) or rs464049 (intron 4) at SLC6A3. In stage III, we confirmed our findings by genotyping 65 SNPs among 659 Bulgarian trios. Both SLC6A3 variants implicated in the US interactions were overtransmitted in this cohort (rs3756450, p = 0.035; rs464049, p = 0.011). Joint analyses from stages II and III identified associations at all four genes (pjoint < 0.05). We tested 29 putative interactions from stage II and detected replication between seven locus pairs (p ≤ 0.05). Simulations suggested our stage II and stage III interaction results were unlikely to have occurred by chance (p = 0.008 and 0.001, respectively). In stage IV we evaluasted rs464049 and rs3756450 for functional effects and found significant allele-specific differences at rs3756450 using electrophoretic mobility shift assays and dualluciferase promoter assays. Our data suggest that a network of dopaminergic polymorphisms increase risk for SZ.
Supported by National Institute of Mental Health (NIMH), this 12-site international collaboration seeks to identify genetic variants that affect risk for anorexia nervosa (AN).
Four hundred families will be ascertained with two or more individuals affected with AN. The assessment battery produces a rich set of phenotypes comprising eating disorder diagnoses and psychological and personality features known to be associated with vulnerability to eating disorders.
We report attributes of the first 200 families, comprising 200 probands and 232 affected relatives.
These results provide context for the genotyping of the first 200 families by the Center for Inherited Disease Research. We will analyze our first 200 families for linkage, complete recruitment of roughly 400 families, and then perform final linkage analyses on the complete cohort. DNA, genotypes, and phenotypes will form a national eating disorder repository maintained by NIMH and available to qualified investigators.
anorexia nervosa; eating disorders; bulimia nervosa; psychiatric disorders; genetics; linkage analysis; genomics
De novo mutations affect risk for many diseases and disorders, especially those with early-onset. An example is autism spectrum disorders (ASD). Four recent whole-exome sequencing (WES) studies of ASD families revealed a handful of novel risk genes, based on independent de novo loss-of-function (LoF) mutations falling in the same gene, and found that de novo LoF mutations occurred at a twofold higher rate than expected by chance. However successful these studies were, they used only a small fraction of the data, excluding other types of de novo mutations and inherited rare variants. Moreover, such analyses cannot readily incorporate data from case-control studies. An important research challenge in gene discovery, therefore, is to develop statistical methods that accommodate a broader class of rare variation. We develop methods that can incorporate WES data regarding de novo mutations, inherited variants present, and variants identified within cases and controls. TADA, for Transmission And De novo Association, integrates these data by a gene-based likelihood model involving parameters for allele frequencies and gene-specific penetrances. Inference is based on a Hierarchical Bayes strategy that borrows information across all genes to infer parameters that would be difficult to estimate for individual genes. In addition to theoretical development we validated TADA using realistic simulations mimicking rare, large-effect mutations affecting risk for ASD and show it has dramatically better power than other common methods of analysis. Thus TADA's integration of various kinds of WES data can be a highly effective means of identifying novel risk genes. Indeed, application of TADA to WES data from subjects with ASD and their families, as well as from a study of ASD subjects and controls, revealed several novel and promising ASD candidate genes with strong statistical support.
The genetic underpinnings of autism spectrum disorder (ASD) have proven difficult to determine, despite a wealth of evidence for genetic causes and ongoing effort to identify genes. Recently investigators sequenced the coding regions of the genomes from ASD children along with their unaffected parents (ASD trios) and identified numerous new candidate genes by pinpointing spontaneously occurring (de novo) mutations in the affected offspring. A gene with a severe (de novo) mutation observed in more than one individual is immediately implicated in ASD; however, the majority of severe mutations are observed only once per gene. These genes create a short list of candidates, and our results suggest about 50% are true risk genes. To strengthen our inferences, we develop a novel statistical method (TADA) that utilizes inherited variation transmitted to affected offspring in conjunction with (de novo) mutations to identify risk genes. Through simulations we show that TADA dramatically increases power. We apply this approach to nearly 1000 ASD trios and 2000 subjects from a case-control study and identify several promising genes. Through simulations and application we show that TADA's integration of sequencing data can be a highly effective means of identifying risk genes.
Psychotic symptoms occur in approximately 40% of subjects with Alzheimer’s disease (AD) and are associated with more rapid cognitive decline and increased functional deficits. They show heritability up to 61% and have been proposed as a marker for a disease subtype suitable for gene mapping efforts. We undertook a combined analysis of three genome-wide association studies (GWAS) to identify loci that a) increase susceptibility to an AD and subsequent psychotic symptoms; or b) modify risk of psychotic symptoms in the presence of neurodegeneration caused by AD. 1299 AD cases with psychosis (AD+P), 735 AD cases without psychosis (AD-P) and 5659 controls were drawn from GERAD1, the NIA-LOAD family study and the University of Pittsburgh ADRC GWAS. Unobserved genotypes were imputed to provide data on > 1.8 million SNPs. Analyses in each dataset were completed comparing a) AD+P to AD-P cases, and b) AD+P cases with controls (GERAD1, ADRC only). Aside from the APOE locus, the strongest evidence for association was observed in an intergenic region on chromosome 4 (rs753129; ‘AD+PvAD-P’ P=2.85 × 10−7; ‘AD+PvControls’ P=1.11 × 10−4). SNPs upstream of SLC2A9 (rs6834555, P=3.0×10−7) and within VSNL1 (rs4038131, P=5.9×10−7) showed strongest evidence for association with AD+P when compared to controls. These findings warrant further investigation in larger, appropriately powered samples in which the presence of psychotic symptoms in AD has been well characterised.
Alzheimer’s disease; psychosis; behavioural symptoms; genome-wide association study; genetic
Multiple studies have confirmed the contribution of rare de novo copy number variations (CNVs) to the risk for Autism Spectrum Disorders (ASD).1-3 While de novo single nucleotide variants (SNVs) have been identified in affected individuals,4 their contribution to risk has yet to be clarified. Specifically, the frequency and distribution of these mutations has not been well characterized in matched unaffected controls, data that are vital to the interpretation of de novo coding mutations observed in probands. Here we show, via whole-exome sequencing of 928 individuals, including 200 phenotypically discordant sibling pairs, that highly disruptive (nonsense and splice-site) de novo mutations in brain-expressed genes are associated with ASD and carry large effects (OR=5.65; CI: 1.44-22.2; p=0.01 asymptotic test). Based on mutation rates in unaffected individuals, we demonstrate that multiple independent de novo SNVs in the same gene among unrelated probands reliably identifies risk alleles, providing a clear path forward for gene discovery. Among a total of 279 identified de novo coding mutations, there is a single instance in probands, and none in siblings, in which two independent nonsense variants disrupt the same gene, SCN2A (Sodium Channel, Voltage-Gated, Type II, Alpha Subunit), a result that is highly unlikely by chance (p=0.005).
We report on results from whole-exome sequencing (WES) of 1,039 subjects diagnosed with autism spectrum disorders (ASD) and 870 controls selected from the NIMH repository to be of similar ancestry to cases. The WES data came from two centers using different methods to produce sequence and to call variants from it. Therefore, an initial goal was to ensure the distribution of rare variation was similar for data from different centers. This proved straightforward by filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. Results were evaluated using seven samples sequenced at both centers and by results from the association study. Next we addressed how the data and/or results from the centers should be combined. Gene-based analyses of association was an obvious choice, but should statistics for association be combined across centers (meta-analysis) or should data be combined and then analyzed (mega-analysis)? Because of the nature of many gene-based tests, we showed by theory and simulations that mega-analysis has better power than meta-analysis. Finally, before analyzing the data for association, we explored the impact of population structure on rare variant analysis in these data. Like other recent studies, we found evidence that population structure can confound case-control studies by the clustering of rare variants in ancestry space; yet, unlike some recent studies, for these data we found that principal component-based analyses were sufficient to control for ancestry and produce test statistics with appropriate distributions. After using a variety of gene-based tests and both meta- and mega-analysis, we found no new risk genes for ASD in this sample. Our results suggest that standard gene-based tests will require much larger samples of cases and controls before being effective for gene discovery, even for a disorder like ASD.
This study evaluates association of rare variants and autism spectrum disorders (ASD) in case and control samples sequenced by two centers. Before doing association analyses, we studied how to combine information across studies. We first harmonized the whole-exome sequence (WES) data, across centers, in terms of the distribution of rare variation. Key features included filtering called variants by fraction of missing data, read depth, and balance of alternative to reference reads. After filtering, the vast majority of variants calls from seven samples sequenced at both centers matched. We also evaluated whether one should combine summary statistics from data from each center (meta-analysis) or combine data and analyze it together (mega-analysis). For many gene-based tests, we showed that mega-analysis yields more power. After quality control of data from 1,039 ASD cases and 870 controls and a range of analyses, no gene showed exome-wide evidence of significant association. Our results comport with recent results demonstrating that hundreds of genes affect risk for ASD; they suggest that rare risk variants are scattered across these many genes, and thus larger samples will be required to identify those genes.
To investigate the underlying phenotypic constructs in autism spectrum disorders (ASD) and to identify genetic loci that are linked to these empirically derived factors.
Exploratory factor analysis was applied to two datasets with 28 selected Autism Diagnostic Interview-Revised (ADI-R) algorithm items. The first dataset was from the Autism Genome Project (AGP) phase I (1,236 ASD subjects from 618 families); the second was from the AGP phase II (804 unrelated ASD subjects). Variables derived from the factor analysis were then used as quantitative traits in genome-wide variance components linkage analyses.
Six factors, joint attention, social interaction and communication, non-verbal communication, repetitive sensory-motor behaviour, peer interaction, and compulsion/restricted interests, were retained for both datasets. There was good agreement between the factor loading patterns from the two datasets. All factors showed familial aggregation. Suggestive evidence for linkage was obtained for the joint attention factor on 11q23. Genome-wide significant evidence for linkage was obtained for the repetitive sensory-motor behaviour factor on 19q13.3.
This study demonstrates that the underlying phenotypic constructs based on the ADI-R algorithm items are replicable in independent datasets; and the empirically derived factors are suitable and informative in genetic studies of ASD.
autism; ADI-R; factor analysis; linkage analysis; quantitative trait
Studies of copy number variation (CNV) have successfully characterized loci and molecular pathways involved in a range of neuropsychiatric conditions. We conducted an analysis of rare CNVs in Tourette Syndrome (TS) to identify novel risk regions and relevant molecular pathways, evaluate the burden of structural variation in cases versus controls, and to assess the overlap of identified variations with those implicated in other neuropsychiatric syndromes.
We conducted a case-control study of 460 individuals with TS, including 148 parent-child trios and 1131 controls. CNV analysis was undertaken using 370K to 1M probe arrays, and genome-wide genotyping data was used to match cases and controls for ancestry. Transmitted and de novo CNVs present in < 1% of the population were evaluated.
While there was no significant increase in the number of de novo or transmitted rare CNVs in cases versus controls, pathway analysis using multiple algorithms showed enrichment of genes within histamine receptor (H1R and H2R) signaling pathways (p=5.8×10-4-1.6×10-2) as well as “axon guidance”, “cell adhesion”, “nervous system development” and “synaptic structure and function” processes. Genes mapping within rare CNVs in TS showed significant overlap with those previously identified in autism spectrum disorders (ASD), but not intellectual disability or schizophrenia. Three large, likely-pathogenic, de novo events were identified, including one disrupting multiple gamma-Aminobutyric acid (GABA) receptor genes.
We identify further evidence supporting recent findings regarding the involvement of histaminergic and GABAergic mechanisms in the etiology of TS and show an overlap of rare CNVs in TS and ASD.
Tourette syndrome; copy number variation; CNV; histamine; GABA; autism
We report on copy number variants (CNVs) found in Palauan subjects ascertained for schizophrenia and related psychotic disorders in extended pedigrees in Palau. We compare CNVs found in this Oceanic population to those seen in other samples, typically of European ancestry. Assessing CNVs in Palauan extended pedigrees yields insight into the evolution of risk CNVs, such as how they arise, are transmitted, and are lost from populations by stochastic or selective processes, none of which is easily measured from case-control samples.
DNA samples from 197 subjects affected with schizophrenia and related psychotic disorders, 185 of their relatives, and 159 controls were successfully characterized for CNVs using Affymetrix Genomewide Human SNP Array 5.0.
CNVs thought to be associated with risk for schizophrenia and related disorders also occur in affected individuals in Palau, specifically 15q11.2 and 1q21.1 deletions, partial duplication of IL1RAPL1 (Xp21.3), and chromosome X duplications (Klinefleter’s syndrome). Partial duplication within A2BP1 appears to convey an 8-fold increased risk in males (95% CI, 0.8–84.4) but not females (OR=0.4, 95% CI, 0.03–4.9). Affected-only linkage analysis using this variant yields a LOD score of 3.5.
This study reveals CNVs that confer risk to schizophrenia and related psychotic disorders in Palau, most of which have been previously observed in samples of European ancestry. Only a few of these CNVs show evidence that they have existed for many generations, consistent with risk variants diminishing reproductive success.
Schizophrenia; Psychotic disorders; Copy Number Variants (CNVs); A2BP1; IL1RAPL1; Palau
Apolipoprotein E (APOE) ε4 alleles increase the risk for late-onset Alzheimer disease (LOAD) and decrease the age of onset. Recently, sequencing the APOE region in a small sample of LOAD subjects identified a variable length poly-T repeat sequence in the nearby gene, TOMM40, which may affect age of onset. We genotyped the TOMM40 poly-T repeat using a novel statistical approach to refine the identification of allele length in 892 LOAD subjects and evaluated its effects on age of onset. Because psychosis in LOAD is a heritable phenotype which has shown conflicting associations with APOE genotype, we also evaluated the association of poly-T repeat length with psychosis. Poly-T repeat lengths had a trimodal distribution which differed between APOE genotype groups. After accounting for APOE ε4 there was no association of poly-T repeat length with age of onset. Neither APOE ε4 nor poly-T repeat length was associated with psychosis. Our findings do not support the association of poly-T repeat length with age of onset in LOAD. The clinical implications of this repeat length polymorphism remain to be elucidated.
Apolipoprotein E (APOE) ε4; late-onset Alzheimer disease (LOAD); psychosis; TOMM40; variable length poly-T repeat sequence
Psychotic symptoms occur in approximately 40% of subjects with Alzheimer’s disease (AD) and are associated with more rapid cognitive decline and increased functional deficits. They show heritability up to 61% and have been proposed as a marker for a disease subtype suitable for gene mapping efforts. We undertook a combined analysis of three genome-wide association studies (GWAS) to identify loci that a) increase susceptibility to an AD and subsequent psychotic symptoms; or b) modify risk of psychotic symptoms in the presence of neurodegeneration caused by AD. 1299 AD cases with psychosis (AD+P), 735 AD cases without psychosis (AD−P) and 5659 controls were drawn from GERAD1, the NIA-LOAD family study and the University of Pittsburgh ADRC GWAS. Unobserved genotypes were imputed to provide data on > 1.8 million SNPs. Analyses in each dataset were completed comparing a) AD+P to AD−P cases, and b) AD+P cases with controls (GERAD1, ADRC only). Aside from the APOE locus, the strongest evidence for association was observed in an intergenic region on chromosome 4 (rs753129; ‘AD+PvAD−P’ P=2.85 × 10−7; ‘AD+PvControls’ P=1.11 × 10−4). SNPs upstream of SLC2A9 (rs6834555, P=3.0×10−7) and within VSNL1 (rs4038131, P=5.9×10−7) showed strongest evidence for association with AD+P when compared to controls. These findings warrant further investigation in larger, appropriately powered samples in which the presence of psychotic symptoms in AD has been well characterised.
Alzheimer’s disease; psychosis; behavioural symptoms; genome-wide association study; genetic
Autism spectrum disorders (ASD) are early onset neurodevelopmental syndromes typified by impairments in reciprocal social interaction and communication, accompanied by restricted and repetitive behaviors. While rare and especially de novo genetic variation are known to affect liability, whether common genetic polymorphism plays a substantial role is an open question and the relative contribution of genes and environment is contentious. It is probable that the relative contributions of rare and common variation, as well as environment, differs between ASD families having only a single affected individual (simplex) versus multiplex families who have two or more affected individuals.
By using quantitative genetics techniques and the contrast of ASD subjects to controls, we estimate what portion of liability can be explained by additive genetic effects, known as narrow-sense heritability. We evaluate relatives of ASD subjects using the same methods to evaluate the assumptions of the additive model and partition families by simplex/multiplex status to determine how heritability changes with status.
By analyzing common variation throughout the genome, we show that common genetic polymorphism exerts substantial additive genetic effects on ASD liability and that simplex/multiplex family status has an impact on the identified composition of that risk. As a fraction of the total variation in liability, the estimated narrow-sense heritability exceeds 60% for ASD individuals from multiplex families and is approximately 40% for simplex families. By analyzing parents, unaffected siblings and alleles not transmitted from parents to their affected children, we conclude that the data for simplex ASD families follow the expectation for additive models closely. The data from multiplex families deviate somewhat from an additive model, possibly due to parental assortative mating.
Our results, when viewed in the context of results from genome-wide association studies, demonstrate that a myriad of common variants of very small effect impacts ASD liability.
Narrow-sense heritability; Multiplex; Simplex; Quantitative genetics
The major histocompatibility complex (MHC) on chromosome 6p is an established risk locus for ulcerative colitis (UC) and Crohn’s disease (CD). We aimed to better define MHC association signals in UC and CD by combining data from dense single nucleotide polymorphism (SNP) genotyping and from imputation of classical HLA types, their constituent SNPs and corresponding amino acids in 562 UC, 611 CD, and 1,428 control subjects. Univariate and multivariate association analyses were performed, controlling for ancestry. In univariate analyses, absence of the rs9269955 C allele was strongly associated with risk for UC (P = 2.67×10−13). rs9269955 is a SNP in the codon for amino acid position 11 of HLA-DRβ1, located in the P6 pocket of the HLA-DR antigen binding cleft. This amino acid position was also the most significantly UC-associated amino acid in omnibus tests (P = 2.68×10−13). Multivariate modeling identified rs9269955-C and 13 other variants in best predicting UC versus control status. In contrast, there was only suggestive association evidence between the MHC and CD. Taken together, these data demonstrate that variation at HLA-DRβ1, amino acid 11 in the P6 pocket of the HLA-DR complex antigen binding cleft is a major determinant of chromosome 6p association with ulcerative colitis.
inflammatory bowel disease genetics; major histocompatibility complex; ulcerative colitis
Published studies suggest associations between circadian gene polymorphisms and bipolar I disorder (BPI), as well as schizoaffective disorder (SZA) and schizophrenia (SZ). The results are plausible, based on prior studies of circadian abnormalities. As replications have not been attempted uniformly, we evaluated representative, common polymorphisms in all three disorders.
We assayed 276 publicly available ‘tag’ single nucleotide polymorphisms (SNPs) at 21 circadian genes among 523 patients with BPI, 527 patients with SZ/SZA, and 477 screened adult controls. Detected associations were evaluated in relation to two published genome-wide association studies (GWAS).
Using gene-based tests, suggestive associations were noted between EGR3 and BPI (p = 0.017), and between NPAS2 and SZ/SZA (p = 0.034). Three SNPs were associated with both sets of disorders (NPAS2: rs13025524 and rs11123857; RORB: rs10491929; p < 0.05). None of the associations remained significant following corrections for multiple comparisons. Approximately 15% of the analyzed SNPs overlapped with an independent study that conducted GWAS for BPI; suggestive overlap between the GWAS analyses and ours was noted at ARNTL.
Several suggestive, novel associations were detected with circadian genes and BPI and SZ/SZA, but the present analyses do not support associations with common polymorphisms that confer risk with odds ratios greater than 1.5. Additional analyses using adequately powered samples are warranted to further evaluate these results.
association; bipolar disorder; circadian; gene; schizoaffective disorder; schizophrenia
Psychotic symptoms occur in approximately 40% of subjects with Alzheimer disease (AD with Psychosis, AD+P) and identify a subgroup with more rapid cognitive decline. We evaluated in 867 AD subjects the association of AD+P with genes which may modify the pathologic process via effects on the accumulation of amyloid beta (Aβ) protein and/or hyperphosphorylated microtubule-associated protein tau (MAPT): amyloid precursor protein (APP), beta-site amyloid precursor protein cleaving enzyme (BACE1), sortilin-related receptor (SORL1), and MAPT. Each gene was thoroughly interrogated with tag SNPs, and gene-based tests were used to enhance power. We found no association of these genes with AD+P.
Alzheimer's disease; psychosis; amyloid precursor protein (APP); beta-site amyloid precursor protein cleaving enzyme (BACE1); sortilin-related receptor (SORL1); microtubule-associated protein tau (MAPT); and Apolipoprotein E e4 (APOE e4)
Objective: Various measures of neurocognitive function show mean differences among individuals with schizophrenia (SZ), their relatives, and population controls. We use eigenvector transformations that maximize heritability of multiple neurocognitive measures, namely principal components of heritability (PCH), and evaluate how they distribute in SZ families and controls. Methods: African-Americans with SZ or schizoaffective disorder (SZA) (n = 514), their relatives (n = 1092), and adult controls (n = 300) completed diagnostic interviews and computerized neurocognitive tests. PCH were estimated from 9 neurocognitive domains. Three PCH, PCH1–PCH3, were modeled to determine if status (SZ, relative, and control), other psychiatric covariates, and education were significant predictors of mean values. A small-scale linkage analysis was also conducted in a subset of the sample. Results: PCH1, PCH2, and PCH3 account for 72% of the genetic variance. PCH1 represents 8 of 9 neurocognitive domains, is most highly correlated with spatial processing and emotion recognition, and has unadjusted heritability of 68%. The means for PCH1 differ significantly among SZ, their relatives, and controls. PCH2, orthogonal to PCH1, is most closely correlated with working memory and has an unadjusted heritability of 45%. Mean PCH2 is different only between SZ families and controls. PCH3 apparently represents a heritable component of neurocognition similar across the 3 diagnostic groups. No significant linkage evidence to PCH1–PCH3 or individual neurocognitive measures was discovered. Conclusions: PCH1 is highly heritable and genetically correlated with SZ. It should prove useful in future genetic analyses. Mean PCH2 differentiates SZ families and controls but not SZ and unaffected family members.
schizophrenia; cognition; heritability; principal components; linkage
Progressive supranuclear palsy (PSP) is a movement disorder with prominent tau neuropathology. Brain diseases with abnormal tau deposits are called tauopathies, the most common being Alzheimer’s disease. Environmental causes of tauopathies include repetitive head trauma associated with some sports. To identify common genetic variation contributing to risk for tauopathies, we carried out a genome-wide association study of 1,114 PSP cases and 3,247 controls (Stage 1) followed up by a second stage where 1,051 cases and 3,560 controls were genotyped for Stage 1 SNPs that yielded P ≤ 10−3. We found significant novel signals (P < 5 × 10−8) associated with PSP risk at STX6, EIF2AK3, and MOBP. We confirmed two independent variants in MAPT affecting risk for PSP, one of which influences MAPT brain expression. The genes implicated encode proteins for vesicle-membrane fusion at the Golgi-endosomal interface, for the endoplasmic reticulum unfolded protein response, and for a myelin structural component.
Discoveries from genome-wide association studies have contributed to our knowledge of the genetic etiology of many complex diseases. However, these account for only a small fraction of each disease's heritability. Here, we comment on approaches currently available to uncover more of the genetic 'dark matter,' including an approach introduced recently by Naukkarinen and colleagues. These authors propose a method for distinguishing between gene expression driven by genetic variation and that driven by non-genetic factors. This dichotomy allows investigators to focus statistical tests and further molecular analyses on a smaller set of genes, thereby discovering new genetic variation affecting risk for disease. We need more methods like this one if we are to shed a powerful light on dark matter. By enhancing our understanding of molecular genetic etiology, such methods will help us to understand disease processes better and will advance the promise of personalized medicine.
Associations between schizophrenia (SCZ) and polymorphisms at the regulator of G-protein signaling 4 (RGS4) gene have been reported (single nucleotide polymorphisms [SNPs] 1, 4, 7, and 18). Yet, similar to other SCZ candidate genes, studies have been inconsistent with respect to the associated alleles.
In an effort to resolve the role for RGS4 in SCZ susceptibility, we undertook a genotype-based meta-analysis using both published and unpublished family-based and case-control samples (total n = 13,807).
The family-based dataset consisted of 10 samples (2160 families). Significant associations with individual SNPs/haplotypes were not observed. In contrast, global analysis revealed significant transmission distortion (p = .0009). Specifically, analyses suggested overtransmission of two common haplotypes that account for the vast majority of all haplotypes. Separate analyses of 3486 cases and 3755 control samples (eight samples) detected a significant association with SNP 4 (p = .01). Individual haplotype analyses were not significant, but evaluation of test statistics from individual samples suggested significant associations.
Our collaborative meta-analysis represents one of the largest SCZ association studies to date. No individual risk factor arose from our analyses, but interpretation of these results is not straightforward. Our analyses suggest risk due to at least two common haplotypes in the presence of heterogeneity. Similar analysis for other putative susceptibility genes is warranted.
PMID: 16631129 CAMSID: cams1794
RGS4; schizophrenia; meta-analysis; association; polymorphism; linkage
Consanguinity has been suggested as a risk factor for psychsoses in some Middle Eastern countries, but adequate control data are unavailable. Our recent studies in Egypt have shown elevated parental consanguinity rates among patients with bipolar I disorder (BP1), compared with controls. We have now extended our analyses to Schizophrenia (SZ) in the same population.
A case-control study was conducted at Mansoura University Hospital, Mansoura, Egypt (SZ, n = 75; controls, n = 126, and their available parents). The prevalence of consanguinity was estimated from family history data (‘self report’), followed by DNA analysis using short tandem repeat polymorphisms (STRPs, n = 63) (‘DNA-based’ rates).
Self reported consanguinity was significantly elevated among the patients (SZ: 46.6%, controls: 19.8%, OR 3.53, 95% CI 1.88, 6.64; p = 0.000058, 1 d.f.). These differences were confirmed using DNA based estimates for coefficients of inbreeding (inbreeding coefficients as means ± standard error, cases: 0.058 ± 0.007, controls: 0.022 ± 0.003).
Consanguinity rates are signifcantly elevated among Egyptian SZ patients in the Nile delta region. The associations are similar to those observed with BP1 in our earlier study. If replicated, the substantial risk associated with consanguinity raises public health concerns. They may also pave the way for gene mapping studies.
Schizophrenia; consanguinity; DNA; genetic; association; inbreeding
Epistasis could be an important source of risk for disease. How interacting loci might be discovered is an open question for genome-wide association studies (GWAS). Most researchers limit their statistical analyses to testing individual pairwise interactions (i.e., marginal tests for association). A more effective means of identifying important predictors is to fit models that include many predictors simultaneously (i.e., higher dimensional models).
We explore a procedure called screen and clean (SC) for identifying liability loci, including interactions, by using the lasso procedure, which is a model selection tool for high dimensional regression. We approach the problem by using a varying dictionary consisting of terms to include in the model. In the first step the lasso dictionary includes only main effects. The most promising SNPs are identified using a screening procedure. Next the lasso dictionary is adjusted to include these main effects and the corresponding interaction terms. Again, promising terms are identified using lasso screening. Then significant terms are identified through the cleaning process. Implementation of SC for GWAS requires algorithms to explore the complex model space induced by the many SNPs genotyped and their interactions. We propose and explore a set of algorithms and find that SC successfully controls Type I error while yielding good power to identify risk loci and their interactions. When the method is applied to data obtained from the Wellcome Trust Case Control Consortium study of Type 1 Diabetes it uncovers evidence supporting interaction within the HLA class II region as well as within Chromosome 12q24.
association test; gene-gene interaction; lasso; model selection
Technological advances make it possible to use high-throughput sequencing as a primary discovery tool of medical genetics, specifically for assaying rare variation. Still this approach faces the analytic challenge that the influence of very rare variants can only be evaluated effectively as a group. A further complication is that any given rare variant could have no effect, could increase risk, or could be protective. We propose here the C-alpha test statistic as a novel approach for testing for the presence of this mixture of effects across a set of rare variants. Unlike existing burden tests, C-alpha, by testing the variance rather than the mean, maintains consistent power when the target set contains both risk and protective variants. Through simulations and analysis of case/control data, we demonstrate good power relative to existing methods that assess the burden of rare variants in individuals.
Developments in sequencing technology now enable us to assay all genetic variation, much of which is extremely rare. We propose to test the distribution of rare variants we observe in cases versus controls. To do so, we present a novel application of the C-alpha statistic to test these rare variants. C-alpha aims to determine whether the set of variants observed in cases and controls is a mixture, such that some of the variants confer risk or protection or are phenotypically neutral. Risk variants are expected to be more common in cases; protective variants more common in controls. C-alpha is sensitive to this imbalance, regardless of its origin—risk, protective, or both—but is ideally suited for a mixture of protective and risk variants. Variation in APOB nicely illustrates a mixture, in that certain rare variants increase triglyceride levels while others decrease it. The hallmark feature of C-alpha is that it uses the distribution of variation observed in cases and controls to detect the presence of a mixture, thus implicating genes or pathways as risk factors for disease.
The authors sought to assess the relationship between candidate genes and two clinical outcomes, namely, symptomatic improvement and the occurrence of suicidal events, in a sample of treatment-resistant depressed adolescents.
A subsample of depressed adolescents participating in the Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) trial, 155 of whom were of European origin, were genotyped with respect to 21 polymorphisms on 12 genes that have a reported association with depression, treatment response, or suicidal events. Participants had not responded to a previous adequate trial with an antidepressant and were randomized to receive either another selective serotonin reuptake inhibitor or venlafaxine, with or without cognitive-behavioral therapy (CBT). Single-nucleotide polymorphism (SNP) analyses were conducted using PLINK with permutation procedures.
No relationship was observed between any polymorphism and response to treatment. The FKBP5 (which codes for a protein causing subsensitivity of the glucocorticoid receptor) rs1360780TT and rs3800373GG genotypes were associated with suicidal events (N=18), even after controlling for treatment effects and relevant covariates. These two SNPs were in significant linkage disequilibrium (r=0.91).
The FKBP5 genotypes associated with suicidal events in this study have been reported by others to cause the greatest degree of glucocorticoid receptor subsensitivity. These results are consistent with those of other studies linking alterations in the hypothalamic-pituitary-adrenal axis with suicidal behavior. The small number of events and lack of a placebo condition make these results preliminary. Replication with a larger sample and a placebo condition is needed to assess whether these events are related to treatment.
Recessive mutations in the Phenylalanine hydroxylase (PAH) gene predispose to phenylketonuria (PKU) in conjunction with dietary exposure to phenylalanine. Previous studies have suggested PAH variations could confer risk for schizophrenia, but comprehensive follow-up has not been reported. We analyzed 15 common PAH “tag” SNPs and 3 exonic variations that are rare in Caucasians but common in African-Americans among four independent samples (total n = 5,414). The samples included two US Caucasian cohorts (260 trios, 230 independent cases, 474 controls), Bulgarian families (659 trios), and an African-American sample (464 families, 401 controls). Analyses of both US Caucasian samples revealed associations with five SNPs; most notably the common allele (G) of rs1522305 from case-control analyses (z = 2.99, p = 0.006). This SNP was independently replicated in the Bulgarian cohort (z = 2.39, p = 0.015). A non-significant trend was also observed among African-American families (z = 1.39, p = 0.165), and combined analyses of all four samples were significant (rs1522305: χ2 = 23.28, 8 d.f., p = 0.003). These results for this SNP met our a priori criteria for statistical significance, namely an association that was robust to multiple testing correction in one sample, a replicated risk allele in multiple samples, and combined analyses that were nominally significant. Case-control results in African-Americans detected an association with L321L (p = 0.047, OR = 1.46). Our analyses suggest several associations at PAH, with consistent evidence for rs1522305. Further analyses, including additional variations and environmental influences such as phenylalanine exposure are warranted.