MRI diffusion tensor imaging (DTI), optimized for measuring the trace of the diffusion tensor, was used to investigate microstructural changes in the brains of 12 individuals with schizophrenia ...compared with 12 matched control subjects. To control for the effects of anatomic variation between subject groups, all participants' diffusion images were nonlinearly registered to standard anatomical space. Significant statistical differences in mean diffusivity (MD) measures between the two groups were determined on a pixel-by-pixel basis, using Gaussian random field theory. We found significantly elevated MD measures within temporal, parietal and prefrontal cortical regions in the schizophrenia group (
P > 0.001), especially within the medial frontal gyrus and anterior cingulate. The dorsal medial and anterior nucleus of the thalamus, including the caudate, also exhibited significantly increased MD in the schizophrenia group (
P > 0.001). This study has shown for the first time that MD measures offer an alternative strategy for investigating altered prefrontal–thalamic circuitry in schizophrenia.
Lymphoblastoid cell lines (LCLs) and fibroblasts provide conveniently derived non-neuronal samples in which to investigate the aetiology of schizophrenia (SZ) using gene expression profiling. This ...assumes that heritable mechanisms associated with risk of SZ have systemic effects and result in changes to gene expression in all tissues. The broad aim of this and other similar studies is that comparison of the transcriptomes of non-neuronal tissues from SZ patients and healthy controls may identify gene/pathway dysregulation underpinning the neurobiological defects associated with SZ. Using microarrays consisting of 18,664 probes we compared gene expression profiles of LCLs from SZ cases and healthy controls. To identify robust associations with SZ that were not patient or tissue specific, we also examined fibroblasts from an independent series of SZ cases and controls using the same microarrays. In both tissue types ANOVA analysis returned approximately the number of differentially expressed genes expected by chance. No genes were significantly differentially expressed in either tissue when corrected for multiple testing. Even using relaxed parameters (p < or = 0.05, without multiple testing correction) there were still no differentially expressed genes that also displayed > or = 2-fold change between the groups of SZ cases and controls common to both LCLs and fibroblasts. We conclude that despite encouraging data from previous microarray studies assessing non-neural tissues, the lack of a convergent set of differentially expressed genes associated with SZ using fibroblasts and LCLs indicates the utility of non-neuronal tissues for detection of gene expression differences and/or pathways associated with SZ remains to be demonstrated.
Although it is clear that errors in genotyping data can lead to severe errors in linkage analysis, there is as yet no consensus strategy for identification of genotyping errors. Strategies include ...comparison of duplicate samples, independent calling of alleles, and Mendelian-inheritance–error checking. This study aimed to develop a better understanding of error types associated with microsatellite genotyping, as a first step toward development of a rational error-detection strategy. Two microsatellite marker sets (a commercial genomewide set and a custom-designed fine-resolution mapping set) were used to generate 118,420 and 22,500 initial genotypes and 10,088 and 8,328 duplicates, respectively. Mendelian-inheritance errors were identified by PedManager software, and concordance was determined for the duplicate samples. Concordance checking identifies only human errors, whereas Mendelian-inheritance–error checking is capable of detection of additional errors, such as mutations and null alleles. Neither strategy is able to detect all errors. Inheritance checking of the commercial marker data identified that the results contained 0.13% human errors and 0.12% other errors (0.25% total error), whereas concordance checking found 0.16% human errors. Similarly, Mendelian-inheritance–error checking of the custom-set data identified 1.37% errors, compared with 2.38% human errors identified by concordance checking. A greater variety of error types were detected by Mendelian-inheritance–error checking than by duplication of samples or by independent reanalysis of gels. These data suggest that Mendelian-inheritance–error checking is a worthwhile strategy for both types of genotyping data, whereas fine-mapping studies benefit more from concordance checking than do studies using commercial marker data. Maximization of error identification increases the likelihood of linkage when complex diseases are analyzed.
The interplay between genotype and phenotype is governed by a multitude of genetic interactions (GIs), and the mapping of GI networks holds significant importance for two main reasons: (1) GIs offer ...a valuable means to uncover compensatory biological mechanisms by modelling biological robustness, thereby identifying functional relationships between genes. This aspect is particularly relevant for biological exploration and translational research, as biological systems have evolved to compensate for genetic (i.e. variations, mutations) and environmental (i.e. drug efficacy) perturbations by leveraging compensatory relationships between genes, pathways, and biological processes; (2) GI facilitates the identification of the direction (positive/alleviating or negative/aggravating interactions) and magnitude of epistatic interactions that influence the resulting phenotype. While comprehensive GI databases exist for organisms like yeast, generating GIs for human diseases through experimental biology methods such as systematic deletion analysis is infeasible. Furthermore, generating disease-specific GIs in humans has not been previously attempted.
We used the Indian schizophrenia case-control (case-816, controls-900) genetic dataset to implement and test GI workflow. Standard GWAS sample quality control procedure was followed to check for ancestry and relatedness outliers. We used the imputed genetic data to increase the SNP coverage to analyse epistatic interactions across the genome comprehensively. By using the odds ratio (OR) we identified the GIs that increase (OR >1) or decrease (OR < 1) the risk of a disease phenotype (i.e. schizophrenia). The SNP-based epistatic results were transformed into gene-based epistatic results.
We have developed a GI workflow for conducting gene-based statistical epistatic analysis and transforming these results to infer GIs. Spatial analysis of functional enrichment (SAFE) was used to detect the statistically overrepresented functional groups. There were ∼ 9.5 million GIs with a p-value ≤ 1 × 10-4. Approximately 4.8 million GIs showed an increased risk (Odds Ratio > 1.0), while ∼ 4.75 million GIs had decreased/no risk (Odds Ratio < 1.0) for schizophrenia. We identified many hub genes with numerous GIs, which increased and reduced the risk of Schizophrenia.
In contrast to model organisms, this approach is specifically viable in humans due to the availability of abundant disease-specific genome-wide genotype datasets. Despite limited power, meaningful GI data was generated with a small sample. SAFE and REVIGO analysis exclusively identified brain/nervous system-related processes, affirming the findings. This computational approach fills a critical gap by generating practically non-existent heritable disease-specific human GIs from human genetic data. These novel datasets can train innovative deep-learning models for post-GWAS functional characterisation, potentially surpassing the limitations of conventional GWAS.
Treatment of schizophrenia with olanzapine and other atypical antipsychotic agents is associated with insulin resistance and diabetes mellitus. The mechanism for this is not understood. Adiponectin ...is an insulin-sensitizing cytokine secreted by adipocytes. It is present in serum in multimers of varying size. Trimers and hexamers are referred to as low molecular weight (LMW) adiponectin. Larger multimers (12-, 18-, and 24-mers) have been designated high molecular weight (HMW) adiponectin and seem responsible for the insulin-sensitizing action of this adipokine. The aim of this study was to examine total adiponectin and LMW and HMW multimers in serum from patients with schizophrenia treated with either olanzapine (n = 9) or other typical antipsychotics (n = 9) and compare results with 16 healthy sex-, body mass index-, and age-matched controls. The effects of olanzapine on adiponectin protein expression and secretion in in vitro-differentiated primary human adipocytes were also examined. Patients receiving olanzapine had significantly lower total serum adiponectin as compared with those on conventional treatment and controls (5.23 +/- 1.53 ng/mL vs. 8.20 +/- 3.77 ng/mL and 8.78 +/- 3.8 ng/mL; P < 0.05 and P < 0.01, respectively). The HMW adiponectin was also reduced in patients on olanzapine as compared with the disease and healthy control groups (1.67 +/- 0.96 ng/mL vs. 3.87 +/- 2.69 ng/mL and 4.07 +/- 3.2 ng/mL; P < 0.05 for both). The LMW adiponectin was not different between patient groups (P = 0.15) but lower in patients on olanzapine as compared with controls (3.56 +/- 0.85 ng/mL vs. 4.70 +/- 1.4 ng/mL; P < 0.05). In vitro, short duration (up to 7 days) olanzapine exposure had no effect on total adiponectin expression or multimer composition of secreted protein. In summary, this study demonstrates a correlation between olanzapine treatment and reduced serum adiponectin, particularly HMW multimers. This may not be a direct effect of olanzapine on adipocyte expression or secretion of adiponectin. These observations provide insights into possible mechanisms for the association between olanzapine treatment and insulin resistance.
Humans reached present-day Island Southeast Asia (ISEA) in one of the first major human migrations out of Africa. Population movements in the millennia following this initial settlement are thought ...to have greatly influenced the genetic makeup of current inhabitants, yet the extent attributed to different events is not clear. Recent studies suggest that south-to-north gene flow largely influenced present-day patterns of genetic variation in Southeast Asian populations and that late Pleistocene and early Holocene migrations from Southeast Asia are responsible for a substantial proportion of ISEA ancestry. Archaeological and linguistic evidence suggests that the ancestors of present-day inhabitants came mainly from north-to-south migrations from Taiwan and throughout ISEA approximately 4,000 years ago. We report a large-scale genetic analysis of human variation in the Iban population from the Malaysian state of Sarawak in northwestern Borneo, located in the center of ISEA. Genome-wide single-nucleotide polymorphism (SNP) markers analyzed here suggest that the Iban exhibit greatest genetic similarity to Indonesian and mainland Southeast Asian populations. The most common non-recombining Y (NRY) and mitochondrial (mt) DNA haplogroups present in the Iban are associated with populations of Southeast Asia. We conclude that migrations from Southeast Asia made a large contribution to Iban ancestry, although evidence of potential gene flow from Taiwan is also seen in uniparentally inherited marker data.
Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which ...identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
The genetic architecture of the human cerebral cortex Ching, Christopher R K; Zsembik, Leo C P; Alhusaini, Saud ...
Science (American Association for the Advancement of Science),
03/2020, Letnik:
367, Številka:
6484
Journal Article
Recenzirano
Odprti dostop
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect ...cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
Rapid emotion processing is an ecologically essential ability for survival in social environments in which threatening or advantageous encounters dynamically and rapidly occur. Efficient emotion ...recognition is subserved by different processes, depending on one's expectations; however, the underlying functional and structural circuitry is still poorly understood. In this study, we delineate brain networks that subserve fast recognition of emotion in situations either congruent or incongruent with prior expectations. For this purpose, we used multimodal neuroimaging and investigated performance on a dynamic emotion perception task. We show that the extended amygdala structural and functional networks relate to speed of emotion processing under threatening conditions. Specifically, increased microstructure of the right stria terminalis, an amygdala white‐matter pathway, was related to faster detection of emotion during actual presentation of anger or after cueing anger. Moreover, functional connectivity of right amygdala with limbic regions was related to faster detection of anger congruent with cue, suggesting selective attention to threat. On the contrary, we found that faster detection of anger incongruent with cue engaged the ventral attention “reorienting” network. Faster detection of happiness, in either expectancy context, engaged a widespread frontotemporal‐subcortical functional network. These findings shed light on the functional and structural circuitries that facilitate speed of emotion recognition and, for the first time, elucidate a role for the stria terminalis in human emotion processing.
Objective:
The study of ethnically homogeneous populations may help to identify schizophrenia risk loci. The authors conducted a genomewide linkage scan for schizophrenia in an Indian population.
...Method:
Participants were 441 individuals (262 affected probands and siblings) who were recruited primarily from one ethnically homogeneous group, the Tamil Brahmin caste, although individuals from other geographically proximal castes also participated. Genotyping of 124 affected sibling pair pedigrees was performed with 402 short tandem repeat polymorphisms. Linkage analyses were conducted using nonparametric exponential LOD (logarithm of the odds ratio for linkage) scores and parametric heterogeneity LOD scores. Parametric heterogeneity scores were calculated using simple dominant and recessive models, correcting for multiple statistics. The data were examined for evidence of consanguinity. Genomewide significance levels were determined using 10,000 gene dropping simulations.
Results:
These findings revealed genomewide significant linkage to chromosome 1p31.1, through the use of both exponential and heterogeneity LOD scores, incorporating correction for multiple statistics and mild consanguinity. The estimated sibling recurrence risk associated with this putative locus was 1.95. Analysis for heterogeneity LOD scores also detected suggestive linkage to chromosomes 13q22.1 and 16q12.2. Using 117 tag single nucleotide polymorphisms (SNPs), family-based association analyses of phosphodiesterase 4B (
PDE4B
), the closest schizophrenia candidate gene, detected no convincing evidence of association, suggesting that the chromosome 1 peak represents a novel risk locus.
Conclusions:
This is the first study-to the authors' knowledge-to report significant linkage of schizophrenia to chromosome 1p31.1. Further investigation of this chromosome region in diverse populations is warranted to identify underlying sequence variants.
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