Family-based genetic risk prediction of multifactorial disease

Genome-wide association studies have detected dozens of variants underlying complex diseases, although it is uncertain how often these discoveries will translate into clinically useful predictors. Here, to improve genetic risk prediction, we consider including phenotypic and genotypic information from related individuals. We develop and evaluate a family-based liability-threshold prediction model and apply it to a simulation of known Crohn's disease risk variants. We show that genotypes of a relative of known phenotype can be informative for an individual's disease risk, over and above the same locus genotyped in the individual. This approach can lead to better-calibrated estimates of disease risk, although the overall benefit for prediction is typically only very modest

Second-generation PLINK: rising to the challenge of larger and richer datasets

PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies (GWAS) and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for even faster and more scalable implementations of key functions. In addition, GWAS and population-genetic data now frequently contain probabilistic calls, phase information, and/or multiallelic variants, none of which can be represented by PLINK 1's primary data format. To address these issues, we are developing a second-generation codebase for PLINK. The first major release from this codebase, PLINK 1.9, introduces extensive use of bit-level parallelism, O(sqrt(n))-time/constant-space Hardy-Weinberg equilibrium and Fisher's exact tests, and many other algorithmic improvements. In combination, these changes accelerate most operations by 1-4 orders of magnitude, and allow the program to handle datasets too large to fit in RAM. This will be followed by PLINK 2.0, which will introduce (a) a new data format capable of efficiently representing probabilities, phase, and multiallelic variants, and (b) extensions of many functions to account for the new types of information. The second-generation versions of PLINK will offer dramatic improvements in performance and compatibility. For the first time, users without access to high-end computing resources can perform several essential analyses of the feature-rich and very large genetic datasets coming into use.Comment: 2 figures, 1 additional fil

Genetic modifiers and subtypes in schizophrenia: Investigations of age at onset, severity, sex and family history

Schizophrenia is a genetically and clinically heterogeneous disorder. Genetic risk factors for the disorder may differ between the sexes or between multiply affected families compared to cases with no family history. Additionally, limited data support a genetic basis for variation in onset and severity, but specific loci have not been identified. We performed genome-wide association studies (GWAS) examining genetic influences on age at onset (AAO) and illness severity as well as specific risk by sex or family history status using up to 2762 cases and 3187 controls from the International Schizophrenia Consortium (ISC)

Cis-Acting Regulation of Brain-Specific ANK3 Gene Expression by a Genetic Variant Associated with Bipolar Disorder

Several genome-wide association studies (GWAS) for bipolar disorder (BD) have found a strong association of the Ankyrin3 (ANK3) gene. This association spans numerous linked single nucleotide polymorphisms (SNPs) in a ~250 kb genomic region overlapping ANK3. The associated region encompasses predicted regulatory elements as well as two of six validated alternative first exons, which encode distinct protein domains at the N-terminus of the protein also known as ankyrin-G (AnkG). Using RNA Ligase-Mediated Rapid Amplification of cDNA Ends (RLM-RACE) to identify novel transcripts in conjunction with a highly sensitive, exon-specific multiplexed mRNA expression assay, we detected differential regulation of distinct ANK3 transcription start sites (TSSs) and coupling of specific 5’ ends with 3’ mRNA splicing events in post-mortem human brain and human stem cell-derived neural progenitors and neurons. Furthermore, allelic variation at the BD–associated SNP rs1938526 correlated with a significant difference in cerebellar expression of a brain-specific ANK3 transcript. These findings suggest a brain-specific cis-regulatory transcriptional effect of ANK3 may be relevant to BD pathophysiology

Non-random mating, parent-of-origin, and maternal–fetal incompatibility effects in schizophrenia

Although the association of common genetic variation in the extended MHC region with schizophrenia is the most significant yet discovered, the MHC region is one of the more complex regions of the human genome, with unusually high gene density and long-range linkage disequilibrium. The statistical test on which the MHC association is based is a relatively simple, additive model which uses logistic regression of SNP genotypes to predict case-control status. However, it is plausible that more complex models underlie this association. Using a well-characterized sample of trios, we evaluated more complex models by looking for evidence for: (a) non-random mating for HLA alleles, schizophrenia risk profiles, and ancestry; (b) parent-of-origin effects for HLA alleles; and (c) maternal-fetal genotype incompatibility in the HLA. We found no evidence for non-random mating in the parents of individuals with schizophrenia in terms of MHC genotypes or schizophrenia risk profile scores. However, there was evidence of non-random mating that appeared mostly to be driven by ancestry. We did not detect over-transmission of HLA alleles to affected offspring via the general TDT test (without regard to parent of origin) or preferential transmission via paternal or maternal inheritance. We evaluated the hypothesis that maternal-fetal HLA incompatibility may increase risk for schizophrenia using eight classical HLA loci. The most significant alleles were in HLA-B, HLA-C, HLA-DQB1, and HLA-DRB1 but none was significant after accounting for multiple comparisons. We did not find evidence to support more complex models of gene action, but statistical power may have been limiting

Polygenic overlap between schizophrenia risk and antipsychotic response: a genomic medicine approach

Therapeutic treatments for schizophrenia do not alleviate symptoms for all patients and efficacy is limited by common, often severe, side-effects. Genetic studies of disease can identify novel drug targets, and drugs for which the mechanism has direct genetic support have increased likelihood of clinical success. Large-scale genetic studies of schizophrenia have increased the number of genes and gene sets associated with risk. We aimed to examine the overlap between schizophrenia risk loci and gene targets of a comprehensive set of medications to potentially inform and improve treatment of schizophrenia

ARTICLE Pooled Association Tests for Rare Variants in Exon-Resequencing Studies

Deep sequencing will soon generate comprehensive sequence information in large disease samples. Although the power to detect association with an individual rare variant is limited, pooling variants by gene or pathway into a composite test provides an alternative strategy for identifying susceptibility genes. We describe a statistical method for detecting association of multiple rare variants in protein-coding genes with a quantitative or dichotomous trait. The approach is based on the regression of phenotypic values on individuals' genotype scores subject to a variable allele-frequency threshold, incorporating computational predictions of the functional effects of missense variants. Statistical significance is assessed by permutation testing with variable thresholds. We used a rigorous population-genetics simulation framework to evaluate the power of the method, and we applied the method to empirical sequencing data from three disease studies

No evidence for rare recessive and compound heterozygous disruptive variants in schizophrenia

Recessive inheritance of gene disrupting alleles, either through homozygosity at a specific site or compound heterozygosity, have been demonstrated to underlie many Mendelian diseases and some complex psychiatric disorders. On the basis of exome sequencing data, an increased burden of complete knockout (homozygous or compound heterozygous) variants has been identified in autism. In addition, using single-nucleotide polymorphism microarray data, an increased rate of homozygosity by descent, or autozygosity, has been linked to the risk of schizophrenia (SCZ). Here, in a large Swedish case-control SCZ sample (11 244 individuals, 5079 of whom have exome sequence data available), we survey the contribution of both autozygosity and complete knockouts to disease risk. We do not find evidence for association with SCZ, either genome wide or at specific loci. However, we note the possible impact of sample size and population genetic factors on the power to detect and quantify any burden that may exist

Additive genetic variation in schizophrenia risk is shared by populations of African and European descent

Previous studies have emphasized ethnically heterogeneous human leukocyte antigen (HLA) classical allele associations to rheumatoid arthritis (RA) risk. We fine-mapped RA risk alleles within the major histocompatibility complex (MHC) in 2782 seropositive RA cases and 4315 controls of Asian descent. We applied imputation to determine genotypes for eight class I and II HLA genes to Asian populations for the first time using a newly constructed pan-Asian reference panel. First, we empirically measured high imputation accuracy in Asian samples. Then we observed the most significant association in HLA-DRβ1 at amino acid position 13, located outside the classical shared epitope (Pomnibus = 6.9 × 10(-135)). The individual residues at position 13 have relative effects that are consistent with published effects in European populations (His > Phe > Arg > Tyr ≅ Gly > Ser)--but the observed effects in Asians are generally smaller. Applying stepwise conditional analysis, we identified additional independent associations at positions 57 (conditional Pomnibus = 2.2 × 10(-33)) and 74 (conditional Pomnibus = 1.1 × 10(-8)). Outside of HLA-DRβ1, we observed independent effects for amino acid polymorphisms within HLA-B (Asp9, conditional P = 3.8 × 10(-6)) and HLA-DPβ1 (Phe9, conditional P = 3.0 × 10(-5)) concordant with European populations. Our trans-ethnic HLA fine-mapping study reveals that (i) a common set of amino acid residues confer shared effects in European and Asian populations and (ii) these same effects can explain ethnically heterogeneous classical allelic associations (e.g. HLA-DRB1*09:01) due to allele frequency differences between populations. Our study illustrates the value of high-resolution imputation for fine-mapping causal variants in the MHC