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.

We examined the role of common genetic variation in schizophrenia in a genome-wide association study of substantial size: a stage 1 discovery sample of 21,856 individuals of European ancestry and a stage 2 replication sample of 29,839 independent subjects. The combined stage 1 and 2 analysis yielded genome-wide significant associations with schizophrenia for seven loci, five of which are new (1p21.3, 2q32.3, 8p23.2, 8q21.3 and 10q24.32-q24.33) and two of which have been previously implicated (6p21.32-p22.1 and 18q21.2). The strongest new finding (P = 1.6 × 10−11) was with rs1625579 within an intron of a putative primary transcript for MIR137 (microRNA 137), a known regulator of neuronal development. Four other schizophrenia loci achieving genome-wide significance contain predicted targets of MIR137, suggesting MIR137-mediated dysregulation as a previously unknown etiologic mechanism in schizophrenia. In a joint analysis with a bipolar disorder sample (16,374 affected individuals and 14,044 controls), three loci reached genome-wide significance: CACNA1C (rs4765905, P = 7.0 × 10−9), ANK3 (rs10994359, P = 2.5 × 10−8) and the ITIH3-ITIH4 region (rs2239547, P = 7.8 × 10−9).

Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Heritability and polygenic predictionIn the EUR sample, the SNP-based heritability (h 2 SNP ) (that is, the proportion of variance in liability attributable to all measured SNPs)

Copy number variants (CNVs) have been strongly implicated in the genetic etiology of schizophrenia (SCZ). However, genome-wide investigation of the contribution of CNV to risk has been hampered by limited sample sizes. We sought to address this obstacle by applying a centralized analysis pipeline to a SCZ cohort of 21,094 cases and 20,227 controls. A global enrichment of CNV burden was observed in cases (OR=1.11, P=5.7×10−15), which persisted after excluding loci implicated in previous studies (OR=1.07, P=1.7 ×10−6). CNV burden was enriched for genes associated with synaptic function (OR = 1.68, P = 2.8 ×10−11) and neurobehavioral phenotypes in mouse (OR = 1.18, P= 7.3 ×10−5). Genome-wide significant evidence was obtained for eight loci, including 1q21.1, 2p16.3 (NRXN1), 3q29, 7q11.2, 15q13.3, distal 16p11.2, proximal 16p11.2 and 22q11.2. Suggestive support was found for eight additional candidate susceptibility and protective loci, which consisted predominantly of CNVs mediated by non-allelic homologous recombination.

Schizophrenia is a common disorder characterized by psychotic symptoms; diagnostic criteria have been established. Family, twin and adoption studies suggest that both genetic and environmental factors influence susceptibility (heritability is approximately 71%; ref. 2), however, little is known about the aetiology of schizophrenia. Clinical and family studies suggest aetiological heterogeneity. Previously, we reported that regions on chromosomes 22, 3 and 8 may be associated with susceptibility to schizophrenia, and collaborations provided some support for regions on chromosomes 8 and 22 (refs 9-13). We present here a genome-wide scan for schizophrenia susceptibility loci (SSL) using 452 microsatellite markers on 54 multiplex pedigrees. Non-parametric linkage (NPL) analysis provided significant evidence for an SSL on chromosome 13q32 (NPL score=4.18; P=0.00002), and suggestive evidence for another SSL on chromosome 8p21-22 (NPL=3.64; P=0.0001). Parametric linkage analysis provided additional support for these SSL. Linkage evidence at chromosome 8 is weaker than that at chromosome 13, so it is more probable that chromosome 8 may be a false positive linkage. Additional putative SSL were noted on chromosomes 14q13 (NPL=2.57; P=0.005), 7q11 (NPL=2.50, P=0.007) and 22q11 (NPL=2.42, P=0.009). Verification of suggestive SSL on chromosomes 13q and 8p was attempted in a follow-up sample of 51 multiplex pedigrees. This analysis confirmed the SSL in 13q14-q33 (NPL=2.36, P=0.007) and supported the SSL in 8p22-p21 (NPL=1.95, P=0.023).

Regarding pain reduction, PRP treatment seems to be an effective treatment for chronic lateral elbow epicondylitis and superior to autologous blood in the short term. Defining details of indications, best PRP concentration, number and time of injections, as well as rehabilitation protocol might increase the method's effectiveness. Additionally, the possibility of cost reduction of the method might justify the use of PRP over autologous whole blood for chronic or refractory tennis elbow.

Schizophrenia and bipolar disorder are two distinct diagnoses that share symptomology. Understanding the genetic factors contributing to the shared and disorder-specific symptoms will be crucial for improving diagnosis and treatment. In genetic data consisting of 53,555 cases (20,129 bipolar disorder [BD], 33,426 schizophrenia [SCZ]) and 54,065 controls, we identified 114 genome-wide significant loci implicating synaptic and neuronal pathways shared between disorders. Comparing SCZ to BD (23,585 SCZ, 15,270 BD) identified four genomic regions including one with disorder-independent causal variants and potassium ion response genes as contributing to differences in biology between the disorders. Polygenic risk score (PRS) analyses identified several significant correlations within case-only phenotypes including SCZ PRS with psychotic features and age of onset in BD. For the first time, we discover specific loci that distinguish between BD and SCZ and identify polygenic components underlying multiple symptom dimensions. These results point to the utility of genetics to inform symptomology and potential treatment.

Many patients suffering from the majority of anxiety disorders complain about their sleep by reporting difficulties in initiating and maintaining it. Polysomnographic studies have shown that, in comparison to normal subjects, the sleep of patients with panic disorder is characterized by longer sleep latency, increased time awake and reduced sleep efficiency. Sleep architecture is normal and there are no significant changes in REM sleep measures. Nocturnal panic attacks are non-REM-related events and occur without an obvious trigger in 18-45% of panic disorder patients. Regarding generalized anxiety disorder, the patients complain of 'trouble sleeping' in 60-70%, while polysomnography has shown increased sleep latency and decreased sleep continuity measures. The findings in REM sleep and sleep architecture generally do not show any aberration to exist. In patients with obsessive-compulsive disorder (OCD) and post-traumatic stress disorder (PTSD), results from the sleep laboratory do not seem to support the subjective complaints of poor sleep. The early reports of shortened REM latency in OCD could not be replicated by recent studies. A dysregulation of the REM sleep control system has been reported for patients with PTSD. Finally, no significant differences were found in all sleep parameters between social phobia patients and controls.