Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

Background: Velo-cardio-facial syndrome (VCFS), a syndrome characterized by an increased frequency of schizophrenia and bipolar disorder, is associated with small interstitial deletions of chromosome 22q11. Methods:We evaluated 50 adults with VCFS using a structured clinical interview (Schedules for Clinical Assessment in Neuropsychiatry or Psychiatric Assessment Schedule for Adults With Developmental Disability if IQ Ͻ50) to establish a DSM-IV diagnosis. The schizophrenia phenotype in individuals with VCFS and schizophrenia was compared with a matched series of individuals with schizophrenia and without VCFS (n = 12). The King's Schizotypy Questionnaire was administered to individuals with VCFS (n = 41), their first-degree relatives (n = 68), and a series of unrelated normal controls (n = 316). All individuals with VCFS deleted for the N25 probe (n = 48) were genotyped for a genetic polymorphism in the COMT gene that results in variations in enzymatic activity.Results: Fifteen individuals with VCFS (30%) had a psychotic disorder, with 24% (n = 12) fulfilling DSM-IV criteria for schizophrenia. In addition, 6 (12%) had major depression without psychotic features. The individuals with schizophrenia had fewer negative symptoms and a relatively later age of onset compared with those with schizophrenia and without VCFS. We found no evidence that possession of the low-activity COMT allele was associated with schizophrenia in our sample of individuals with VCFS. Conclusions:The high prevalence of schizophrenia in this group suggests that chromosome 22q11 might harbor a gene or genes relevant to the etiology of schizophrenia in the wider population.

About 35% of patients with 22q11 deletion syndrome (22q11DS), which includes DiGeorge and velocardiofacial syndromes, develops psychiatric disorders, mainly schizophrenia and bipolar disorder. We previously reported that mice carrying a multigene deletion (Df1) that models 22q11DS have reduced prepulse inhibition (PPI), a behavioral abnormality and schizophrenia endophenotype. Impaired PPI is associated with several psychiatric disorders, including those that occur in 22q11DS, and recently, reduced PPI was reported in children with 22q11DS. Here, we have mapped PPI deficits in a panel of mouse mutants that carry deletions that partially overlap with Df1 and have defined a PPI critical region encompassing four genes. We then used single-gene mutants to identify the causative genes. We show that PPI deficits in Df1͞؉ mice are caused by haploinsufficiency of two genes, Tbx1 and Gnb1l. Mutation of either gene is sufficient to cause reduced PPI. Tbx1 is a transcription factor, the mutation of which is sufficient to cause most of the physical features of 22q11DS, but the gene had not been previously associated with the behavioral͞psychiatric phenotype. A likely role for Tbx1 haploinsufficiency in psychiatric disease is further suggested by the identification of a family in which the phenotypic features of 22q11DS, including psychiatric disorders, segregate with an inactivating mutation of TBX1. One family member has Asperger syndrome, an autistic spectrum disorder that is associated with reduced PPI. Thus, Tbx1 and Gnb1l are strong candidates for psychiatric disease in 22q11DS patients and candidate susceptibility genes for psychiatric disease in the wider population.mouse model ͉ psychiatric disease ͉ DiGeorge syndrome ͉ sensorimotor gating C aused by a heterozygous multigene deletion, 22q11 deletion syndrome (22q11DS) is a relatively common genetic disorder (1:4,000 live births). Behavioral and psychiatric disorders are a prominent part of the 22q11DS phenotype. In children, these disorders include cognitive defects, anxiety, attention deficit disorder, and problems of social interaction that are increasingly recognized to meet the criteria of autistic spectrum disorder (1, 2), a neurodevelopmental disorder. In adults, high rates of psychotic disorders, especially schizophrenia, have been reported (2-5).It is likely that the pathophysiological basis of many psychiatric disorders is heterogeneous involving multiple genes and environmental factors. Therefore, when they occur frequently in association with a defined genetic defect, as in the case of 22q11DS (3, 4, 6, 7), it offers a unique opportunity to identify causative or contributing genes, especially if a good animal model is available. We developed a mouse model of 22q11DS (8), the Df1͞ϩ mouse, which carries a heterozygous deletion encompassing 22 genes. Df1͞ϩ mice recapitulate many of the cardiovascular defects associated with 22q11DS (8), and they also display abnormal behavior, including impaired sensorimotor gating, as measured by prepulse inhibition (PPI) o...

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Many genetic syndromes involve a facial gestalt that suggests a preliminary diagnosis to an experienced clinical geneticist even before a clinical examination and genotyping are undertaken. Previously, using visualization and pattern recognition, we showed that dense surface models (DSMs) of full face shape characterize facial dysmorphology in Noonan and in 22q11 deletion syndromes. In this much larger study of 696 individuals, we extend the use of DSMs of the full face to establish accurate discrimination between controls and individuals with Williams, Smith-Magenis, 22q11 deletion, or Noonan syndromes and between individuals with different syndromes in these groups. However, the full power of the DSM approach is demonstrated by the comparable discriminating abilities of localized facial features, such as periorbital, perinasal, and perioral patches, and the correlation of DSM-based predictions and molecular findings. This study demonstrates the potential of face shape models to assist clinical training through visualization, to support clinical diagnosis of affected individuals through pattern recognition, and to enable the objective comparison of individuals sharing other phenotypic or genotypic properties.