Nonsocial and social cognition in schizophrenia: current evidence and future directions

Cognitive impairment in schizophrenia involves a broad array of nonsocial and social cognitive domains. It is a core feature of the illness, and one with substantial implications for treatment and prognosis. Our understanding of the causes, consequences and interventions for cognitive impairment in schizophrenia has grown substantially in recent years. Here we review a range of topics, including: a) the types of nonsocial cognitive, social cognitive, and perceptual deficits in schizophrenia; b) how deficits in schizophrenia are similar or different from those in other disorders; c) cognitive impairments in the prodromal period and over the lifespan in schizophrenia; d) neuroimaging of the neural substrates of nonsocial and social cognition, and e) relationships of nonsocial and social cognition to functional outcome. The paper also reviews the considerable efforts that have been directed to improve cognitive impairments in schizophrenia through novel psychopharmacology, cognitive remediation, social cognitive training, and alternative approaches. In the final section, we consider areas that are emerging and have the potential to provide future insights, including the interface of motivation and cognition, the influence of childhood adversity, metacognition, the role of neuroinflammation, computational modelling, the application of remote digital technology, and novel methods to evaluate brain network organization. The study of cognitive impairment has provided a way to approach, examine and comprehend a wide range of features of schizophrenia, and it may ultimately affect how we define and diagnose this complex disorder.     

Intergenerational transmission of trauma effects: putative role of epigenetic mechanisms

This paper reviews the research evidence concerning the intergenerational transmission of trauma effects and the possible role of epigenetic mechanisms in this transmission. Two broad categories of epigenetically mediated effects are highlighted. The first involves developmentally programmed effects. These can result from the influence of the offspring's early environmental exposures, including postnatal maternal care as well as in utero exposure reflecting maternal stress during pregnancy. The second includes epigenetic changes associated with a preconception trauma in parents that may affect the germline, and impact fetoplacental interactions. Several factors, such as sex‐specific epigenetic effects following trauma exposure and parental developmental stage at the time of exposure, explain different effects of maternal and paternal trauma. The most compelling work to date has been done in animal models, where the opportunity for controlled designs enables clear interpretations of transmissible effects. Given the paucity of human studies and the methodological challenges in conducting such studies, it is not possible to attribute intergenerational effects in humans to a single set of biological or other determinants at this time. Elucidating the role of epigenetic mechanisms in intergenerational effects through prospective, multi‐generational studies may ultimately yield a cogent understanding of how individual, cultural and societal experiences permeate our biology.     

Genome-wide association studies on prostate cancer: the end or the beginning?

Prostate cancer (PCa) is the second most frequently diagnosed malignancy in men. Ge nome-wide association st udies (GWAS) has been highly successful in discovering susceptibility loci for prostate cancer. Currently, more than twenty GWAS have identified more than fifty common variants associated with susceptibility with PCa. Yet with the increase in loci, voices from the scientific society are calling for more. In this review, we summarize current findings, discuss the common problems troubling current studies and shed light upon possible breakthroughs in the future. GWAS is the beginning of something wonderful. Although we are quite near the end of the beginning, post-GWAS studies are just taking off and future studies are needed extensively. It is believed that in the future GWAS information will be helpful to build a comprehensive system intergraded with PCa prevention, diagnosis, molecular classification, personalized therapy.     

人类身高的遗传学研究进展

人类身高是由环境和遗传因素共同决定的,遗传学研究发现遗传因素对身高差异的影响更大。身高是典型的多基因遗传性状,科研人员试图运用传统的连锁分析和关联分析寻找和发现对人类身高具有显著影响的常见DNA序列变异,但进展缓慢。近年来,随着基因分型和DNA测序技术的发展,人类身高的遗传学研究取得了很多突破性进展。全基因组关联分析(GWAS)的应用,发现和证实了上百个与人类身高相关的单核苷酸多态性位点(SNPs),拓展了人们对人类生长和发育的相关遗传学认识,同时也为研究人类其他复杂性状提供了理论依据和借鉴。本文综述了人类身高的遗传学研究进展,探讨了目前该研究领域所存在的问题和未来发展方向,以期为今后人类身高相关的遗传学研究提供参考和借鉴。     

桃基因组及全基因组关/联分析研究进展

桃(Prunus persica [L.] Batsch)是蔷薇科重要的核果类果树, 适应性强, 栽培范围广, 果实口感好, 深受消费者喜欢。提高桃果实品质及增加抗病、抗虫性一直是桃遗传育种者关注的焦点。文章对近年来桃遗传分子标记连锁图谱和物理图谱构建、分子标记开发应用、全基因组和转录组测序工作中所取得的最新成果进行综述, 同时阐述了高密度SNP芯片标记技术在桃以及其它作物上所开展的全基因组关联分析应用实例, 为桃进一步开展全基因组关联分析, 挖掘目标性状QTLs以及高效育种选择标记提供理论基础     

宿主遗传背景与肠道微生物互作研究进展

“微生物”这一名词指非常小的生物,如古菌、细菌、原生生物、真菌和病毒,肠道“微生物组”表示的是肠道微生物集合体。它们实际上共享宿主的身体空间,但作为宿主健康和疾病的决定因素却几乎被忽视。作为信息的集合,微生物组包括微生物的基因组数据、结构元件、代谢物和环境条件。最近对肠道微生物组的研究表明,微生物群落在维持宿主稳态和调节宿主表型上发挥着重要作用。随着包括二代测序(next-generation sequencing, NGS)在内的新技术的出现以及微生物群落序列谱等深入测定技术出现,人们对肠道微生物组与宿主遗传背景之间的关系有了许多见解。本文通过肠道微生物组学的概述,基于全基因组关联分析技术建立肠道微生物组学与宿主遗传之间联系,并对宿主遗传学与肠道微生物组的关系及未来发展前景进行探讨。     

Genome-wide associations for fertility traits in Holstein–Friesian dairy cows using data from experimental research herds in four European countries

Genome-wide association studies for difficult-to-measure traits are generally limited by the sample population size with accurate phenotypic data. The objective of this study was to utilise data on primiparous Holstein–Friesian cows from experimental farms in Ireland, the United Kingdom, the Netherlands and Sweden to identify genomic regions associated with traditional measures of fertility, as well as a fertility phenotype derived from milk progesterone profiles. Traditional fertility measures investigated were days to first heat, days to first service, pregnancy rate to first service, number of services and calving interval (CI); post-partum interval to the commencement of luteal activity (CLA) was derived using routine milk progesterone assays. Phenotypic and genotypic data on 37 590 single nucleotide polymorphisms (SNPs) were available for up to 1570 primiparous cows. Genetic parameters were estimated using linear animal models, and univariate and bivariate genome-wide association analyses were undertaken using Bayesian stochastic search variable selection performed using Gibbs sampling. Heritability estimates of the traditional fertility traits varied from 0.03 to 0.16; the heritability for CLA was 0.13. The posterior quantitative trait locus (QTL) probabilities, across the genome, for the traditional fertility measures were all <0.021. Posterior QTL probabilities of 0.060 and 0.045 were observed for CLA on SNPs each on chromosome 2 and chromosome 21, respectively, in the univariate analyses; these probabilities increased when CLA was included in the bivariate analyses with the traditional fertility traits. For example, in the bivariate analysis with CI, the posterior QTL probability of the two aforementioned SNPs were 0.662 and 0.123. Candidate genes in the vicinity of these SNPs are discussed. The results from this study suggest that the power of genome-wide association studies in cattle may be increased by sharing of data and also possibly by using physiological measures of the trait under investigation.     

Genome-wide association study of porcine hematological parameters in a Large White × Minzhu F2 resource population

Hematological traits, which are important indicators of immune function in animals, have been commonly examined as biomarkers of disease and disease severity in humans and animals. Genome-wide significant quantitative trait loci (QTLs) provide important information for use in breeding programs of animals such as pigs. QTLs for hematological parameters (hematological traits) have been detected in pig chromosomes, although these are often mapped by linkage analysis to large intervals making identification of the underlying mutation problematic. Single nucleotide polymorphisms (SNPs) are the common form of genetic variation among individuals and are thought to account for the majority of inherited traits. In this study, a genome-wide association study (GWAS) was performed to detect regions of association with hematological traits in a three-generation resource population produced by intercrossing Large White boars and Minzhu sows during the period from 2007 to 2011. Illumina PorcineSNP60 BeadChip technology was used to genotype each animal and seven hematological parameters were measured (hematocrit (HCT), hemoglobin (HGB), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), mean corpuscular volume (MCV), red blood cell count (RBC) and red blood cell volume distribution width (RDW)). Data were analyzed in a three step Genome-wide Rapid Association using the Mixed Model and Regression-Genomic Control (GRAMMAR-GC) method. A total of 62 genome-wide significant and three chromosome-wide significant SNPs associated with hematological parameters were detected in this GWAS. Seven and five SNPs were associated with HCT and HGB, respectively. These SNPs were all located within the region of 34.6-36.5 Mb on SSC7. Four SNPs within the region of 43.7-47.0 Mb and fifty-five SNPs within the region of 42.2-73.8 Mb on SSC8 showed significant association with MCH and MCV, respectively. At chromosome-wide significant level, one SNP at 29.2 Mb on SSC1 and two SNPs within the region of 26.0-26.2 Mb were found to be significantly associated with RBC and RDW, respectively. Many of the SNPs were located within previously reported QTL regions and appeared to narrow down the regions compared with previously described QTL intervals. In current research, a total of seven significant SNPs were found within six candidate genes SCUBE3, KDR, TDO, IGFBP7, ADAMTS3 and AFP. In addition, the KIT gene, which has been previously reported to relate to hematological parameters, was located within the region significantly associated with MCH and MCV and could be a candidate gene. These results of this study may lead to a better understanding of the molecular mechanisms of hematological parameters in pigs.     

基于全基因组关联的中国常见肿瘤遗传病因学研究

肿瘤是基因-环境交互作用引起的复杂性疾病.在同样的环境暴露下,不同遗传背景的个体发生肿瘤的风险有很大差异.研究肿瘤相关遗传因素对理解肿瘤发生发展乃至诊断治疗都有重要意义.近年来发展的全基因组关联研究(genome-wide association study,GWAS)可在全基因组范围内发现与复杂疾病或表型关联的遗传因素,为复杂疾病遗传学研究提供了强有力的手段.欧美研究者运用全基因组关联研究的方法,对各种常见肿瘤进行了研究,获得了重要成果.2010年以来,中国科学家在国际核心期刊发表了一系列高水平的肿瘤全基因组关联研究成果,在中国常见肿瘤的遗传病因学研究方面取得了重要进展.     

Entering the second century of maize quantitative genetics

Maize is the most widely grown cereal in the world. In addition to its role in global agriculture, it has also long served as a model organism for genetic research. Maize stands at a genetic crossroads, as it has access to all the tools available for plant genetics but exhibits a genetic architecture more similar to other outcrossing organisms than to self-pollinating crops and model plants. In this review, we summarize recent advances in maize genetics, including the development of powerful populations for genetic mapping and genome-wide association studies (GWAS), and the insights these studies yield on the mechanisms underlying complex maize traits. Most maize traits are controlled by a large number of genes, and linkage analysis of several traits implicates a ‘common gene, rare allele'' model of genetic variation where some genes have many individually rare alleles contributing. Most natural alleles exhibit small effect sizes with little-to-no detectable pleiotropy or epistasis. Additionally, many of these genes are locked away in low-recombination regions that encourage the formation of multi-gene blocks that may underlie maize''s strong heterotic effect. Domestication left strong marks on the maize genome, and some of the differences in trait architectures may be due to different selective pressures over time. Overall, maize''s advantages as a model system make it highly desirable for studying the genetics of outcrossing species, and results from it can provide insight into other such species, including humans.     

Genome-wide associations for feed utilisation complex in primiparous Holstein–Friesian dairy cows from experimental research herds in four European countries

Genome-wide association studies for difficult-to-measure traits are generally limited by the sample size with accurate phenotypic data. The objective of this study was to utilise data on primiparous Holstein–Friesian cows from experimental farms in Ireland, the United Kingdom, the Netherlands and Sweden to identify genomic regions associated with the feed utilisation complex: fat and protein corrected milk yield (FPCM), dry matter intake (DMI), body condition score (BCS) and live-weight (LW). Phenotypic data and 37 590 single nucleotide polymorphisms (SNPs) were available on up to 1629 animals. Genetic parameters of the traits were estimated using a linear animal model with pedigree information, and univariate genome-wide association analyses were undertaken using Bayesian stochastic search variable selection performed using Gibbs sampling. The variation in the phenotypes explained by the SNPs on each chromosome was related to the size of the chromosome and was relatively consistent for each trait with the possible exceptions of BTA4 for BCS, BTA7, BTA13, BTA14, BTA18 for LW and BTA27 for DMI. For LW, BCS, DMI and FPCM, 266, 178, 206 and 254 SNPs had a Bayes factor >3, respectively. Olfactory genes and genes involved in the sensory smell process were overrepresented in a 500 kbp window around the significant SNPs. Potential candidate genes were involved with functions linked to insulin, epidermal growth factor and tryptophan.