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Schizophrenia

Schizophrenia is a chronic and debilitating mental disorder characterized by disturbances in perception, thought, mood, and behavior.
Individuals with schizophrenia may experience hallucinations, delusions, disorganized speech, and impaired cognitive functioning, which can significantly impact their daily lives.
The exact causes of schizophrenia are not fully understood, but it is believed to involve a complex interplay of genetic, neurobiological, and environmental factors.
Early diagnosis and effective treatment, often involving a combination of medication and psychosocial interventions, are crucial for managing the symptoms and improving the quality of life for those affected by this challenging condition.
Researchers continue to explore new avenues for understanding and treating schizophrenia, with the goal of developing more effective therapies and improving outcomes for those living with this disruptive mental illness.

Most cited protocols related to «Schizophrenia»

1
Genetic Architecture of Major Depression
Cited 325 times
Genotyping procedures can be found in the primary reports for each cohort (summarized in Supplementary Table 3). Individual genotype data for all PGC29 samples, GERA, and iPSYCH were processed using the PGC “ricopili” pipeline (URLs) for standardized quality control, imputation, and analysis19 (link). The cohorts from deCODE, Generation Scotland, UK Biobank, and 23andMeD were processed by the collaborating research teams using comparable procedures. SNPs and insertion-deletion polymorphisms were imputed using the 1000 Genomes Project multi-ancestry reference panel (URLs)86 (link). More detailed information on sample QC is provided in the Supplementary Note.
Linkage disequilibrium (LD) score regression (LDSC)22 (link),24 (link) was used to estimate
hSNP2 from GWA summary statistics. Estimates of
hSNP2 on the liability scale depend on the assumed lifetime prevalence of MDD in the population (K), and we assumed K=0.15 but also evaluated a range of estimates of K to explore sensitivity including 95% confidence intervals (Supplementary Fig. 1). LDSC bivariate genetic correlations attributable to genome-wide SNPs (rg) were estimated across all MDD and major depression cohorts and between the full meta-analyzed cohort and other traits and disorders.
LDSC was also used to partition
hSNP2 by genomic features24 (link),46 (link). We tested for enrichment of
hSNP2 based on genomic annotations partitioning
hSNP2 proportional to bp length represented by each annotation. We used the “baseline model” which consists of 53 functional categories. The categories are fully described elsewhere46 (link), and included conserved regions47 (link), USCC gene models (exons, introns, promoters, UTRs), and functional genomic annotations constructed using data from ENCODE 87 (link) and the Roadmap Epigenomics Consortium88 (link). We complemented these annotations by adding introgressed regions from the Neanderthal genome in European populations89 (link) and open chromatin regions from the brain dorsolateral prefrontal cortex. The open chromatin regions were obtained from an ATAC-seq experiment performed in 288 samples (N=135 controls, N=137 schizophrenia, N=10 bipolar, and N=6 affective disorder)90 . Peaks called with MACS91 (link) (1% FDR) were retained if their coordinates overlapped in at least two samples. The peaks were re-centered and set to a fixed width of 300bp using the diffbind R package92 (link). To prevent upward bias in heritability enrichment estimation, we added two categories created by expanding both the Neanderthal introgressed regions and open chromatin regions by 250bp on each side.
We used LDSC to estimate rg between major depression and a range of other disorders, diseases, and human traits22 (link). The intent of these comparisons was to evaluate the extent of shared common variant genetic architectures in order to suggest hypotheses about the fundamental genetic basis of major depression (given its extensive comorbidity with psychiatric and medical conditions and its association with anthropometric and other risk factors). Subject overlap of itself does not bias rg. These rg are mostly based on studies of independent subjects and the estimates should be unbiased by confounding of genetic and non-genetic effects (except if there is genotype by environment correlation). When GWA studies include overlapping samples, rg remains unbiased but the intercept of the LDSC regression is an estimate of the correlation between association statistics attributable to sample overlap. These calculations were done using the internal PGC GWA library and with LD-Hub (URLs)60 (link).
Wray N.R., Ripke S., Mattheisen M., Trzaskowski M., Byrne E.M., Abdellaoui A., Adams M.J., Agerbo E., Air T.M., Andlauer T.F., Bacanu S.A., Bækvad-Hansen M., Beekman A.T., Bigdeli T.B., Binder E.B., Blackwood D.H., Bryois J., Buttenschøn H.N., Bybjerg-Grauholm J., Cai N., Castelao E., Christensen J.H., Clarke T.K., Coleman J.R., Colodro-Conde L., Couvy-Duchesne B., Craddock N., Crawford G.E., Crowley C.A., Dashti H.S., Davies G., Deary I.J., Degenhardt F., Derks E.M., Direk N., Dolan C.V., Dunn E.C., Eley T.C., Eriksson N., Escott-Price V., Kiadeh F.F., Finucane H.K., Forstner A.J., Frank J., Gaspar H.A., Gill M., Giusti-Rodríguez P., Goes F.S., Gordon S.D., Grove J., Hall L.S., Hannon E., Hansen C.S., Hansen T.F., Herms S., Hickie I.B., Hoffmann P., Homuth G., Horn C., Hottenga J.J., Hougaard D.M., Hu M., Hyde C.L., Ising M., Jansen R., Jin F., Jorgenson E., Knowles J.A., Kohane I.S., Kraft J., Kretzschmar W.W., Krogh J., Kutalik Z., Lane J.M., Li Y., Li Y., Lind P.A., Liu X., Lu L., MacIntyre D.J., MacKinnon D.F., Maier R.M., Maier W., Marchini J., Mbarek H., McGrath P., McGuffin P., Medland S.E., Mehta D., Middeldorp C.M., Mihailov E., Milaneschi Y., Milani L., Mill J., Mondimore F.M., Montgomery G.W., Mostafavi S., Mullins N., Nauck M., Ng B., Nivard M.G., Nyholt D.R., O’Reilly P.F., Oskarsson H., Owen M.J., Painter J.N., Pedersen C.B., Pedersen M.G., Peterson R.E., Pettersson E., Peyrot W.J., Pistis G., Posthuma D., Purcell S.M., Quiroz J.A., Qvist P., Rice J.P., Riley B.P., Rivera M., Mirza S.S., Saxena R., Schoevers R., Schulte E.C., Shen L., Shi J., Shyn S.I., Sigurdsson E., Sinnamon G.C., Smit J.H., Smith D.J., Stefansson H., Steinberg S., Stockmeier C.A., Streit F., Strohmaier J., Tansey K.E., Teismann H., Teumer A., Thompson W., Thomson P.A., Thorgeirsson T.E., Tian C., Traylor M., Treutlein J., Trubetskoy V., Uitterlinden A.G., Umbricht D., Van der Auwera S., van Hemert A.M., Viktorin A., Visscher P.M., Wang Y., Webb B.T., Weinsheimer S.M., Wellmann J., Willemsen G., Witt S.H., Wu Y., Xi H.S., Yang J., Zhang F., Arolt V., Baune B.T., Berger K., Boomsma D.I., Cichon S., Dannlowski U., de Geus E., DePaulo J.R., Domenici E., Domschke K., Esko T., Grabe H.J., Hamilton S.P., Hayward C., Heath A.C., Hinds D.A., Kendler K.S., Kloiber S., Lewis G., Li Q.S., Lucae S., Madden P.A., Magnusson P.K., Martin N.G., McIntosh A.M., Metspalu A., Mors O., Mortensen P.B., Müller-Myhsok B., Nordentoft M., Nöthen M.M., O’Donovan M.C., Paciga S.A., Pedersen N.L., Penninx B.W., Perlis R.H., Porteous D.J., Potash J.B., Preisig M., Rietschel M., Schaefer C., Schulze T.G., Smoller J.W., Stefansson K., Tiemeier H., Uher R., Völzke H., Weissman M.M., Werge T., Winslow A.R., Lewis C.M., Levinson D.F., Breen G., Børglum A.D, & Sullivan P.F. (2018). Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nature genetics, 50(5), 668-681.
Publication 2018
ATAC-Seq Brain Chromatin DNA Library Dorsolateral Prefrontal Cortex Europeans Exons Genetic Diversity Genetic Polymorphism Genome Genome-Wide Association Study Genotype Genotyping Techniques Homo sapiens Hypersensitivity INDEL Mutation Introns Mood Disorders Neanderthals Reproduction Schizophrenia Single Nucleotide Polymorphism Unipolar Depression Untranslated Regions
2
Genetic Factors in Schizophrenia Symptomatology
Cited 138 times

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Publication 2012
Brain Diseases Childbirth Craniocerebral Trauma Diagnosis Drug Abuse Ethanol Ethics Committees, Research Nervous System Disorder Schizoaffective Disorder Schizophrenia Visually Impaired Persons
3
Exome Sequencing of Schizophrenic Trios
Cited 128 times
Parent proband trios (N=623), where the proband had a history of hospitalization for schizophrenia or schizoaffective disorder, were recruited from psychiatric hospitals in Bulgaria. Probands attended mainstream schools which excluded people with ID (intellectual disability); all graduated with a pass. Exome DNA was captured from genomic DNA (whole blood), using either Agilent or Nimblegen array-based capture, and subjected to paired-end sequencing on Illumina HiSeq sequencers. The BWA/Picard/GATK pipeline was used for sequence alignment and variant calling. Putative de novo mutations were identified using Plink/Seq (http://atgu.mgh.harvard.edu/plinkseq) and were validated using Sanger sequencing. We used Plink/Seq to annotate mutations according to RefSeq gene transcripts (UCSC Genome Browser, http://genome.ucsc.edu). Mutation rate was tested for association with clinical and other covariates using a generalized linear model. Rates of functional classes of mutations in probands were compared with those in published controls using Fisher’s exact test. Mutations were tested for recurrence, enrichment in candidate gene sets, and enrichment in genes affected by de novo mutations in previous studies using dnenrich (Supplementary Text). Dnenrich calculates one-sided p-values under a binomial model of greater than expected hits using randomly placed mutations accounting for gene size, sequencing coverage, tri-nucleotide contexts, and functional effects of the observed mutations. Candidate gene sets and studies of neuropsychiatric disease are described in the main and Supplementary Text. Primary hypotheses (Table 1) were Bonferroni corrected for multiple testing.
Full Methods and associated references are available in the Supplementary Text.
Fromer M., Pocklington A.J., Kavanagh D.H., Williams H.J., Dwyer S., Gormley P., Georgieva L., Rees E., Palta P., Ruderfer D.M., Carrera N., Humphreys I., Johnson J.S., Roussos P., Barker D.D., Banks E., Milanova V., Grant S.G., Hannon E., Rose S.A., Chambert K., Mahajan M., Scolnick E.M., Moran J.L., Kirov G., Palotie A., McCarroll S.A., Holmans P., Sklar P., Owen M.J., Purcell S.M, & O’Donovan M.C. (2014). De novo mutations in schizophrenia implicate synaptic networks. Nature, 506(7487), 179-184.
Publication 2014
BLOOD Exome Genes Genome Hospitalization Intellectual Disability Mainstreaming, Education Mutation Nucleotides Parent Recurrence Schizoaffective Disorder Schizophrenia Sequence Alignment TRIO protein, human
4
Schizophrenia Genetic Association Analysis
Cited 82 times
Details of MGS subject recruitment and sample characteristics are provided in the online Full Methods (section A1). DNA samples were genotyped using the Affymetrix 6.0 array at the Broad Institute. Samples (5.3%) were excluded for high missing data rates, outlier proportions of heterozygous genotypes, incorrect sex or genotypic relatedness to other subjects. SNPs (7% for African American, 25% for European-ancestry and 27% for combined analyses) were excluded for minor allele frequencies less than 1%, high missing data rates, Hardy-Weinberg deviation (controls), or excessive Mendelian errors (trios), discordant genotypes (duplicate samples) or large allele frequency differences among DNA plates. Principal component scores reflecting continental and within-Europe ancestries of each subject were computed and outliers excluded. Genomic control λ values for autosomes after QC were 1.042 for African American and 1.087 for the larger European-ancestry and combined analyses.
For MGS, association of single SNPs to schizophrenia was tested by logistic regression (trend test) using PLINK10 (link), separately for European-ancestry, African American and combined datasets, correcting for principal component scores that reflected geographical gradients or that differed between cases and controls, and for sex for chromosome X and pseudoautosomal SNPs. Genotypic data were imputed for 192 regions surrounding the best findings, and for additional regions selected for meta-analysis.11 (link) Detailed results are available in Supplementary Datafiles 1 and 2, and complete results from dbGAP (www.ncbi.nlm.nih.gov/sites/entrez?db=gap).
Meta-analysis of the MGS, ISC and SGENE datasets was carried out by combining P-values for all SNPs (in the selected regions) for which genotyped or imputed data were available for all datasets, with weights computed from case-control sample sizes. See the companion papers for details of the ISC and SGENE analyses.
Shi J., Levinson D.F., Duan J., Sanders A.R., Zheng Y., Pe'er I., Dudbridge F., Holmans P.A., Whittemore A.S., Mowry B.J., Olincy A., Amin F., Cloninger C.R., Silverman J.M., Buccola N.G., Byerley W.F., Black D.W., Crowe R.R., Oksenberg J.R., Mirel D.B., Kendler K.S., Freedman R, & Gejman P.V. (2009). Common variants on chromosome 6p22.1 are associated with schizophrenia. Nature, 460(7256), 753-757.
Publication 2009
African American Europeans Genome Heterozygote Pets Schizophrenia Single Nucleotide Polymorphism TRIO protein, human X Chromosome
5
Largest Schizophrenia GWAS Meta-Analysis
Cited 78 times
Details of each of the samples (including sample size, ancestry, and whether included in the previous publication by the PGC) are given in Supplementary Cohort Descriptions. The core PGC dataset included 90 cohorts for which we had individual level genotype data fully processed under a uniform pipeline. This core dataset contains genotypes on 161,405 unrelated subjects; 67,390 schizophrenia/schizoaffective disorder cases and 94,015 controls, equivalent in power to 73,189 of each. A parent-proband trio is considered to comprise one case and one control. Approximately half (31,914 cases and 47,176 controls) of the samples were not included in the previous GWAS of the PGC1 . Around 80% of the probands (53,386 cases and 77,258 controls) were of European Ancestry, and the remainder (14,004 cases and 16757 controls) were of East Asian ancestry2 . We additionally included in the Primary GWAS summary statistics from 9 cohorts comprising African-American (AA; 6152 cases 3918 controls) and Latino (1234 cases, 3090 controls) participants; the combined sample is equivalent in power to 6,551 each of cases and controls. 1249 LD – independent (r2 > 0.1) Variants showing evidence for association (P< 1×10−5) were further meta-analysed with an additional dataset of 1,979 cases and 142,626 controls of European ancestry obtained from deCODE genetics, thus the final analysis represents 320,404 diploid genomes.
Trubetskoy V., Panagiotaropoulou G., Awasthi S., Braun A., Kraft J., Skarabis N., Walter H., Ripke S., Pardiñas A.F., Dennison C.A., Hall L.S., Harwood J.C., Richards A.L., Legge S.E., Lynham A., Williams N.M., Bray N.J., Escott-Price V., Kirov G., Holmans P.A., Pocklington A.J., Owen M.J., Walters J.T., O’Donovan M.C., Qi T., Sidorenko J., Wu Y., Zeng J., Gratten J., Visscher P.M., Yang J., Wray N.R., Qi T., Yang J., Bigdeli T.B., Fanous A.H., Bryois J., Bergen S.E., Kähler A.K., Magnusson P.K., Hultman C.M., Sullivan P.F., Chen C.Y., Atkinson E.G., Goldstein J.I., Howrigan D.P., Martin A.R., Daly M.J., Huang H., Neale B.M., Ripke S., Ge T., Lam M., Ge T., Atkinson E.G., Belliveau R.A., Chambert K.D., Genovese G., Lee P.H., Martin A.R., Pietiläinen O., McCarroll S.A., Moran J.L., Smoller J.W., Brown T.C., Feng G., Hyman S.E., Sheng M., Hyman S.E., Huang H., Neale B.M., Lam M., Chong S.A., Subramaniam M., Lam M., Lencz T., Malhotra A.K., Watanabe K., Frei O., Agartz I., Athanasiu L., Melle I., Andreassen O.A., Frei O., Athanasiu L., Melle I., Steen N.E., Andreassen O.A., Frei O., Ge T., DeLisi L.E., Mesholam-Gately R.I., Seidman L.J., Koopmans F., Magnusson S., Stefánsson H., Stefansson K., Grove J., Agerbo E., Als T.D., Bybjerg-Grauholm J., Demontis D., Hougaard D.M., Mors O., Mortensen P.B., Nordentoft M., Børglum A.D., Grove J., Als T.D., Demontis D., Mattheisen M., Børglum A.D., Grove J., Als T.D., Demontis D., Børglum A.D., Kim M., Gandal M.J., Li Z., Shi Y., Shi Y., Li Z., Zhou W., Qin S., Shi Y., Shi Y., Voloudakis G., Zhang W., Roussos P., Zhang W., Adams M., McIntosh A., Agartz I., Agartz I., Söderman E., Jönsson E.G., McGrath J.J., Al Eissa M., Bass N.J., Fiorentino A., O’Brien N.L., Pimm J., Sharp S.I., McQuillin A., Albus M., Alexander M., Alizadeh B.Z., Bruggeman R., Alizadeh B.Z., Alptekin K., Alptekin K., Amin F., Arolt V., Lencer R., Rothermundt M., Baune B.T., Arrojo M., Azevedo M.H., Bacanu S.A., Webb B.T., Wormley B.K., Riley B.P., Kendler K.S., Begemann M., Mitjans M., Steixner-Kumar A.A., Ehrenreich H., Bene J., Benyamin B., Benyamin B., Benyamin B., Blasi G., Rampino A., Torretta S., Bertolino A., Bobes J., Bobes J., Bobes J., Bonassi S., Bressan R.A., Gadelha A., Noto C., Bressan R.A., Gadelha A., Noto C., Ota V.K., Santoro M.L., Belangero S.I., Bromet E.J., Bruggeman R., Buckley P.F., Buckner R.L., Bybjerg-Grauholm J., Hougaard D.M., Cahn W., Kahn R.S., Cahn W., Cairns M.J., Scott R.J., Tooney P.A., Cairns M.J., Schall U., Scott R.J., Tooney P.A., Cairns M.J., Tooney P.A., Calkins M.E., Gur R.E., Gur R.C., Turetsky B.I., Carr V.J., Carr V.J., Carr V.J., Castle D., Harvey C., Castle D., Catts S.V., Catts S.V., Chan R.C., Chan R.C., Chaumette B., Kebir O., Krebs M.O., Chaumette B., Cheng W., Cheung E.F., Chong S.A., Subramaniam M., Cohen D., Consoli A., Giannitelli M., Laurent-Levinson C., Cohen D., Consoli A., Giannitelli M., Laurent-Levinson C., Cohen D., Cordeiro Q., Costas J., Curtis C., Quattrone D., Breen G., Collier D.A., Di Forti M., Vassos E., Curtis C., Mondelli V., Quattrone D., van Amelsvoort T., Di Forti M., Murray R.M., Vassos E., van Amelsvoort T., Davidson M., Davis K.L., Haroutunian V., Malaspina D., Reichenberg A., Siever L.J., Silverman J.M., Buxbaum J.D., Kahn R.S., de Haan L., de Haan L., de Haan L., de Haan L., Degenhardt F., Forstner A., Nöthen M.M., DeLisi L.E., Dickerson F., Dikeos D., Papadimitriou G.N., Dinan T., Dinan T., Djurovic S., Djurovic S., Duan J., Gejman P.V., Sanders A.R., Duan J., Gejman P.V., Sanders A.R., Ducci G., Dudbridge F., Eriksson J.G., Eriksson J.G., Eriksson J.G., Fañanás L., Fañanás L., Peñas J.G., González-Pinto A., Molto M.D., Moreno C., Parellada M., Sanjuan J., Crepo-Facorro B., Mata I., Arango C., Faraone S.V., Forstner A., Frank J., Streit F., Witt S.H., Rietschel M., Freimer N.B., Ophoff R.A., Freimer N.B., Fromer M., Stahl E.A., Frustaci A., Gershon E.S., Giegling I., Hartmann A.M., Konte B., Rujescu D., Giusti-Rodríguez P., Szatkiewicz J.P., Sullivan P.F., Godard S., González Peñas J., Moreno C., Parellada M., Arango C., González-Pinto A., Gopal S., Savitz A., Li Q.S., Gratten J., Green M.F., Nuechterlein K.H., Sugar C.A., Green M.F., Greenwood T.A., Light G.A., Swerdlow N.R., Braff D., Guillin O., Campion D., Guillin O., Campion D., Guillin O., Gülöksüz S., Luykx J.J., Rutten B.P., van Amelsvoort T., van Winkel R., van Amelsvoort T., van Winkel R., Gülöksüz S., Gutiérrez B., Hahn E., Hakonarson H., Pellegrino R., Haroutunian V., Haroutunian V., Harvey C., Pantelis C., Hayward C., Henskens F.A., Kelly B.J., Herms S., Hoffmann P., Howrigan D.P., Fromer M., Daly M.J., Ikeda M., Iwata N., Iyegbe C., van Os J., Joa I., Julià A., Marsal S., Kam-Thong T., Rautanen A., Kamatani Y., Kamatani Y., Karachanak-Yankova S., Toncheva D., Karachanak-Yankova S., Keller M.C., Khrunin A., Limborska S., Slominsky P., Kim S.W., Klovins J., Nikitina-Zake L., Kondratiev N., Golimbet V., Kraft J., Kubo M., Kučinskas V., Kučinskiene Z.A., Kusumawardhani A., Kuzelova-Ptackova H., Landi S., Lazzeroni L.C., Levinson D.F., Lazzeroni L.C., Lee P.H., Petryshen T.L., Smoller J.W., Lehrer D.S., Lerer B., Li M., Lieberman J., Stroup T.S., Light G.A., Braff D., Liu C.M., Liu C.M., Hwu H.G., Lönnqvist J., Lönnqvist J., Loughland C.M., Lubinski J., Luykx J.J., Bakker S., Kahn R., Luykx J.J., Luykx J.J., Macek M J.r., Mackinnon A., Mackinnon A., Maher B.S., Maier W., Malaspina D., Atbaşoğlu E.C., Mallet J., Marder S.R., Martin A.R., Huang H., Martorell L., Muntané G., Vilella E., Mattheisen M., Meier S., Mattheisen M., Mattheisen M., Schulze T.G., McCarley R.W., McDonald C., Donohoe G., Morris D.W., McGrath J.J., Periyasamy S., Mowry B.J., Wray N.R., McGrath J.J., Medeiros H., Sobell J.L., Medeiros H., Meier S., Melegh B., Mesholam-Gately R.I., Seidman L.J., Metspalu A., Milani L., Esko T., Michie P.T., Milanova V., Molden E., Molden E., Molina E., Molto M.D., Molto M.D., Sanjuan J., Mondelli V., Morley C.P., Muntané G., Murphy K.C., Myin-Germeys I., Nenadić I., Nenadić I., Nestadt G., Pulver A.E., O’Neill F.A., Oh S.Y., Oh S.Y., Olincy A., Freedman R., Ota V.K., Santoro M.L., Belangero S.I., Pantelis C., Pantelis C., Baune B.T., Pantelis C., Baune B.T., Paunio T., Paunio T., Periyasamy S., Mowry B.J., Perkins D.O., Sullivan P.F., Pfuhlmann B., Pietiläinen O., Hyman S.E., Pietiläinen O., Benner C., Pirinen M., Palotie A., Daly M.J., Porteous D., Powell J., Quattrone D., Di Forti M., Quested D., Quested D., Radant A.D., Tsuang D.W., Radant A.D., Tsuang D.W., Rapaport M.H., Roe C., Liu C., Roffman J.L., Moran J.L., Roth J., Gawlik M., Saker-Delye S., Salomaa V., Suvisaari J., Sanjuan J., Schall U., Scott R.J., Shi J., Siever L.J., Silverman J.M., Sigurdsson E., Sigurdsson E., Sim K., Sim K., Sim K., So H.C., So H.C., Stain H.J., Stain H.J., Steen N.E., Jönsson E.G., Stögmann E., Zimprich F., Stone W.S., Stone W.S., Straub R.E., Hyde T., Jaffe A., Weinberger D.R., Strengman E., Sugar C.A., Svrakic D.M., Cloninger C.R., Ta T.M., Ta T.M., Takahashi A., Terao C., Thibaut F., Thibaut F., Toncheva D., Tosato S., Tura G.B., Üçok A., Vaaler A., Vaaler A., van Winkel R., Veijola J., van Winkel R., Veijola J., Waddington J., Waterreus A., Morgan V.A., Waterreus A., Jablensky A.V., Morgan V.A., Weiser M., Wu J.Q., Xu Z., Yolken R., Zai C.C., Kennedy J.L., Zai C.C., Kennedy J.L., Zhu F., Zhu F., Atbaşoğlu E.C., Saka M.C., Ayub M., Black D.W., Buccola N.G., Byerley W.F., Chen W.J., Chen W.J., Crespo-Facorro B., Crespo-Facorro B., Galletly C., Galletly C., Galletly C., Gennarelli M., Gennarelli M., Hwu H.G., Mors O., Müller-Myhsok B., Müller-Myhsok B., Müller-Myhsok B., Neil A.L., Nordentoft M., Pato M.T., Pato C.N., Pato M.T., Pato C.N., Pirinen M., Pirinen M., Schulze T.G., Schulze T.G., Schulze T.G., Stahl E.A., Esko T., Stahl E.A., Wang S.H., Xu S., Xu S., Xu S., Adolfsson R., Bramon E., Cervilla J.A., Cichon S., Cichon S., Cichon S., Collier D.A., Collier D.A., Corvin A., Gill M., Curtis D., Curtis D., Domenici E., Escott-Price V., Fanous A.H., Fanous A.H., Gareeva A., Khusnutdinova E., Gareeva A., Gareeva A., Khusnutdinova E., Gareeva A., Glatt S.J., Hong K.S., Knowles J.A., Knowles J.A., Lee J., Lee J., Lencz T., Malhotra A.K., Lencz T., Malhotra A.K., Liu J., Liu J., Malhotra D., Menezes P.R., Nimgaonkar V., Ophoff R.A., Ophoff R.A., Paciga S.A., Palotie A., Palotie A., Ripke S., Qin S., Rivera M., Rivera M., Schwab S.G., Schwab S.G., Serretti A., Sham P.C., Sham P.C., Sham P.C., Sham P.C., Sham P.C., Sham P.C., Clair D.S., Tsuang M.T., Tsuang M.T., van Os J., Vawter M.P., Werge T., Werge T., Clair D.S., Werge T., Werge T., van Os J., Wildenauer D.B., van Os J., Yu X., Yue W., Yu X., Yue W., Yue W., Roussos P., Vassos E., Verhage M., Koopmans F., Sahasrabudhe D., Toonen R.F., Verhage M., Verhage M., Posthuma D., Yang J., Dai N., Wenwen Q., Wildenauer D.B., Dai N., Wenwen Q., Wildenauer D.B., Agiananda F., Amir N., Antoni R., Arsianti T., Asmarahadi A., Diatri H., Djatmiko P., Irmansyah I., Khalimah S., Kusumadewi I., Kusumaningrum P., Lukman P.R., Nasrun M.W., Safyuni N.S., Prasetyawan P., Semen G., Siste K., Tobing H., Widiasih N., Wiguna T., Wulandari D., Evalina N., Hananto A.J., Ismoyo J.H., Marini T.M., Henuhili S., Reza M., Yusnadewi S., Abyzov A., Akbarian S., van Bakel H., Breen M., Charney A., Dracheva S., Girdhar K., Hoffman G., Jiang Y., Pinto D., Purcell S., Roussos P., Wiseman J., Ashley-Koch A., Crawford G., Reddy T., Brown M., Grennan K., Bryois J., Carlyle B., Emani P., Galeev T., Gerstein M., Gu M., Guerra B., Gursoy G., Kitchen R., Lee D., Li M., Liu S., Navarro F., Pan X., Pochareddy S., Rozowsky J., Sestan N., Sethi A., Shi X., Szekely A., Wang D., Warrell J., Weissman S., Wu F., Xu X., Coetzee G., Farnham P., Lay F., Rhie S., Witt H., Wood S., Yao L., Gandal M., Polioudakis D., Swarup V., Won H., Giase G., Jiang S., Kefi A., Shieh A., Goes F., Zandi P., Kim Y., Knowles J.A., Mattei E., Purcaro M., Pratt H., Peters M.A., Sanders S., Weng Z., White K., Arranz M.J., Bramon E., Iyegbe C., Lewis C., Lin K., Murray R.M., Powell J., Walshe M., Arranz M.J., Bender S., Bender S., Weisbrod M., Bramon E., Crepo-Facorro B., Mata I., Hall J., Lawrie S., McIntosh A., Linszen D.H., Ophoff R.A., van Os J., van Os J., Rujescu D., Rujescu D., Achsel T., Bagni C., Andres-Alonso M., Kreutz M.R., Bayés À., Biederer T., Brose N., Chua J.J., Coba M.P., Cornelisse L.N., van Weering J.R., de Jong A.P., MacGillavry H.D., de Juan-Sanz J., Dieterich D.C., Pielot R., Smalla K.H., Dieterich D.C., Gundelfinger E.D., Pielot R., Smalla K.H., Feng G., Goldschmidt H.L., Huganir R.L., Hoogenraad C., Hyman S.E., Imig C., Jahn R., Jung H., Kim E., Kaeser P.S., Lipstein N., Malenka R., McPherson P.S., O’Connor V., Ryan T.A., Sala C., Verpelli C., Smit A.B., Südhof T.C, & Thomas P.D. (2022). Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature, 604(7906), 502-508.
Publication 2022
African American Diploidy East Asian People Europeans Genome Genome-Wide Association Study Genotype Latinos Parent Schizophrenia TRIO protein, human

Most recents protocols related to «Schizophrenia»

1
Comorbid Psychiatric Disorders in Patients
The proportion of patients with COD was not significantly different for male (45.4%) and female (52.0%) patients (p = 0.139). The prevalence rates for the types of co-occurring psychiatric diagnoses are shown in Table 2. Among patients with COD, anxiety (22.9%) and mood disorders (17.3%) were the two most common psychiatric disorders. About one in five had more than one COD (21.4%), with a higher prevalence rate of multiple CODs among females (30.3%) than males (18.0%). Having anxiety disorders were significantly more prevalent among females (30.3%) than males (19.8%).

Prevalence of co-occurring psychiatric disorders

Total(N = 611)Females(N = 175)Males(N = 434)Females versus malesref
N%N%N%ORp-value
Without COD32252.78448.023754.6
With COD28947.39152.019745.41.300.139
Psychiatric diagnoses1
- Anxiety disorders F40-4914022.95330.38619.81.760.005
- Mood disorders F30-3910617.33620.67016.11.350.191
- ADHD F90.0-F90.97912.92112.05813.40.880.650
- Personality disorders F60-697011.52715.4439.91.660.053
- Multiple CODs13121.453*30.37818.01.98< 0.001

1 Other psychiatric diagnoses (n = 17) included Schizophrenia, F20-F29 (n = 8); Behavioral syndromes associated with physiological disorders and physical factors (n = 16); Mental retardation, F70-F79 (n = 6); Pervasive and specific developmental disorders, F80-89 (n = 16); Behavioral disorders, F91-F98 (n = 8)

Andersson H.W., Mosti M.P, & Nordfjaern T. (2023). Inpatients in substance use treatment with co-occurring psychiatric disorders: a prospective cohort study of characteristics and relapse predictors. BMC Psychiatry, 23, 152.
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Publication 2023
Anxiety Disorders Behavior Disorders Cods Developmental Disabilities Diagnosis, Psychiatric Disorder, Attention Deficit-Hyperactivity Females Intellectual Disability Males Mental Disorders Mood Mood Disorders Patients Personality Disorders Physical Examination physiology Schizophrenia Syndrome Woman
2
Comparative Study of Schizophrenia Spectrum
The study was approved by the Medical Science Research Ethics Committee of the First Affiliated Hospital of China Medical University (approval reference number [2012]25–1). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. All participants provided written informed consent by themselves or by their parents/guardians if they were under 18 years old after a complete description of the study. SZ and GHR participants were recruited from the inpatient and outpatient services at Shenyang Mental Health Center and the Department of Psychiatry at First Affiliated Hospital of China Medical University. Healthy controls (HC) participants were recruited from the local community by advertisement.
All components of the study were conducted at a single site and included both longitudinal and cross-sectional study cohorts, aged 13–45 years. All participants were evaluated by 2 trained psychiatrists to determine the presence or absence of Axis I psychiatric diagnoses using the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders-IV-Text Revision (DSM-IV) Axis I Disorders (SCID) in those 18 years old and older and the Schedule for Affective Disorders and Schizophrenia for School-Age Children-present and Lifetime Version (K-SADS-PL) in those younger than 18 years. SZ participants met DSM-IV diagnostic criteria for SZ and not any other Axis I disorder. GHR participants were first-degree relatives of individuals with SZ and did not meet criteria for any DSM-IV Axis I disorder. HC participants did not have current or lifetime Axis I disorder or history of psychotic, mood, or other Axis I disorders in first-degree relatives as determined by detailed family history. Participants were excluded if any of the following were present: (1) the existence of substance/alcohol abuse or dependence or concomitant major medical disorder, (2) any magnetic resonance imaging (MRI) contraindications, and (3) history of head trauma with loss of consciousness for ≥ 5 min or any neurological disorder. Symptom severity was measured using the Brief Psychiatric Rating Scale (BPRS).
Duan J., Gong X., Womer F.Y., Sun K., Tang L., Liu J., Zheng J., Zhu Y., Tang Y., Zhang X, & Wang F. (2023). Neurodevelopmental trajectories, polygenic risk, and lipometabolism in vulnerability and resilience to schizophrenia. BMC Psychiatry, 23, 153.
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Publication 2023
Abuse, Alcohol Child concomitant disease Craniocerebral Trauma Diagnosis Diagnosis, Psychiatric Epistropheus Ethics Committees, Research Healthy Volunteers Homo sapiens Inpatient Legal Guardians Mental Disorders Mental Health Services Mood Mood Disorders Nervous System Disorder Outpatients Parent Psychiatrist Sadness Schizophrenia SCID Mice Youth
3
Holistic Support for Homeless with Complex Needs
Participants ranged in age from 25 to 58 (mean age 41). Their current living situation was reported as either currently homeless (38%), supported housing (50%), private rented accommodation (6%) and 6% were vulnerably housed in unsuitable accommodation.
Primary presenting substance misuse was reported as opiates (74%), alcohol (13%), and benzodiazepines (13%). Self-identified poor mental health was characterised as suffering from long term depression and anxiety, and 100% had trouble sleeping. 63% of participants reported suicidal ideation within the past 12 months. 25% reported that they had ever been admitted to a psychiatric facility. A minority had psychiatric diagnoses (6%) which were reported as schizophrenia and personality disorder.
Within the previous 12 months, 56% had accessed housing support services, 56% had used substance misuse services, 38% had accessed support for domestic abuse and 25% had accessed mental health support. Fifty percent had visited their GP at least once. Significant acute healthcare use was reported, with at least 18 individual admissions to A&E reported within the group in the previous 12 months.
McGrath J., Crossley S., Lhussier M, & Forster N. (2023). Social capital and women’s narratives of homelessness and multiple exclusion in northern England. International Journal for Equity in Health, 22, 41.
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Publication 2023
Anxiety Benzodiazepines Diagnosis, Psychiatric Drug Abuse Ethanol Mental Health Minority Groups Ocular Accommodation Opiate Alkaloids Personality Disorders Persons, Homeless Schizophrenia
4
First-Episode Major Depressive Disorder Patients
Participants were recruited at the psychiatric outpatient department of the First Hospital of Shanxi Medical University from 2015 to 2017. Inclusion criteria were as follows: (1) fulfilling DSM-IV criteria for MDD, diagnosed by two trained psychiatrists using the Structured Clinical Interview for DSM-IV Disorders (SCID); (2) 17-item Hamilton Depression Scale (HAMD) score of more than 23; (3) age 18-60 years old, Han nationality; (4) no prior medication, including antidepressant, antipsychotic drugs, thyroid hormone therapy, hypoglycemic agents, antihypertensive and lipid-lowering drugs; and (5) depression symptoms were first-episode and the disease duration of no more than 24 months. Exclusion criteria included: (1) pregnant or breastfeeding women; (2) concurrent DSM-IV axis I disorder including bipolar disorder, schizophrenia, and schizoaffective or severe medical conditions; (3) substance use disorder except for tobacco; and (4) unwillingness to provide informed consent.
All participants provided written informed consent. This study was approved by the Institutional Review Board (IRB) of the First Hospital of Shanxi Medical University (No. 2016-Y27).
Peng P., Wang Q., Lang X., Liu T, & Zhang X.Y. (2023). Clinical symptoms, thyroid dysfunction, and metabolic disturbances in first-episode drug-naïve major depressive disorder patients with suicide attempts: A network perspective. Frontiers in Endocrinology, 14, 1136806.
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Publication 2023
Antidepressive Agents Antihypertensive Agents Antipsychotic Agents Bipolar Disorder Depressive Symptoms Epistropheus Ethics Committees, Research Hypoglycemic Agents Hypolipidemic Agents Outpatients Pharmaceutical Preparations Psychiatrist Schizophrenia Therapeutics Thyroid Hormones Tobacco Use Disorder Woman
5
Adolescent Depression, Suicide Attempts, and Brain Function
A total of 71 first-episode drug-naïve adolescent depression patients were recruited from the Department of Psychiatry of Wuhan Mental Health Center. Patients were diagnosed with depression by two experienced psychiatrists based on DSM-IV criteria. To be eligible for study inclusion, patients had to be 7–17 years of age, right-handed, meet the diagnostic criteria for an acute episode of depression, have a history of SA within the past 14 days, be free of serious physical illnesses, be free of the alcohol and/or substance abuse or dependence, and be free of other Axis I disorders including schizophrenia, bipolar disorder, and substance-induced mood disorders. In addition, 54 age- and sex-matched healthy control individuals were recruited from the Wuhan Mental Health Center medical examination center. These controls were right-handed, had no history or family history of psychiatric disorders, and were free of any severe physical illness. All participants provided written informed consent for study participation. The Ethics Committee of Wuhan Mental Health Center approved this research, which was conducted in accordance with the guidelines of the Declaration of Helsinki.
SA was defined as any self-destructive behavior intended to terminate one’s own life that did not result in death (O’Carroll et al., 1996 (link); Li et al., 2021 (link)). The patients included in this study were confirmed to have a history of SA through interviews with experienced psychiatrists, who also collected relevant details including the numbers of SAs and the dates on which they had occurred. When ambiguous results were obtained, the psychiatrists also made inquiries with the parents or clinicians of that patient to confirm these results. The Suicidal Ideation Questionnaire Junior (SIQ-JR; Keane et al., 1996 (link)) scale was conducted on the same day as the rs-fMRI to evaluate the severity of suicidal ideation, while the child depression inventory (CDI; Akimana et al., 2019 (link)) was used to assess depression severity.
Zhou Y., Song Y., Chen C., Yan S., Chen M, & Liu T. (2023). Abnormal amplitude of low-frequency fluctuation values as a neuroimaging biomarker for major depressive disorder with suicidal attempts in adolescents: A resting-state fMRI and support vector machine analysis. Frontiers in Psychology, 14, 1146944.
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Publication 2023
Adolescent Bipolar Disorder Child Diagnosis Epistropheus Ethanol Ethics Committees fMRI Mental Disorders Mental Health Mood Disorders Parent Patients Pharmaceutical Preparations Physical Examination Psychiatrist Schizophrenia Sexual Health Substance Abuse

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More about "Schizophrenia"

Schizophrenia is a debilitating mental disorder characterized by disturbances in perception, thought, mood, and behavior.
Individuals with this chronic condition may experience hallucinations, delusions, disorganized speech, and impaired cognitive functioning, significantly impacting their daily lives.
The exact causes of schizophrenia are not fully understood, but it is believed to involve a complex interplay of genetic, neurobiological, and environmental factors.
Early diagnosis and effective treatment, often involving a combination of medication and psychosocial interventions, are crucial for managing the symptoms and improving the quality of life for those affected by this challenging mental illness.
Researchers continue to explore new avenues for understanding and treating schizophrenia, with the goal of developing more effective therapies and improving outcomes for individuals living with this disruptive condition.
Synonyms and related terms for schizophrenia include psychosis, schizoaffective disorder, delusional disorder, and thought disorder.
Abbreviations commonly used include SZ and SCZ.
Key subtopics include the different types of schizophrenia (e.g., paranoid, disorganized, catatonic), symptoms, risk factors, diagnostic criteria, and treatment approaches.
Statistcal software such as SAS 9.4, SPSS version 20, Stata 15, and MATLAB have been utilized in schizophrenia research to analyze data, model risk factors, and evaluate the effectiveness of interventions.
Additionally, genetic analysis tools like the HiSeq 2000 have contributed to the understanding of the genetic underpinnings of this complex disorder.