Background
Research shows that women have a higher risk of developing Alzheimer’s disease (AD) than men. This study seeks to identify sex‐specific risk profiles linked to the development of AD.
...Method
We analyzed multiple blood biomarkers for risk of development of AD as well as with cognitive decline in the community‐based longitudinal Framingham Heart Study Offspring Cohort. A total of 2962 participants (mean age 60 year, 55% women) without any type of dementia were followed up to a median of 12 years with cognitive testing, blood sampling and dementia assessments. This study analyzed participants 60 years and older. Proportional hazards models were performed to investigate associations between biomarkers and the time to incident AD. Linear models were used to quantify the associations between biomarkers and annualized, domain‐specific cognitive decline. Covariates included age, sex, education, and baseline cognitive measurement.
Result
During the follow‐up, 7.3% (119/1631) women and 4.7% (63/1331) men developed AD; 8.6% (141/1631) women and 7.1% (94/1331) men developed all‐cause dementia. We found that women were 41% more likely than men to be diagnosed with AD (P = 0.029) while found no gender differences in the time to develop all‐cause dementia (P = 0.16). We found that lower plasma amyloid‐beta42 level was significantly predictive for the future risk of AD in women (P = 0.0018) and not in men (P = 0.069), while the hazards ratio were not significantly different between men and women (Pdiff = 0.92). Further, lower plasma amyloid‐beta42 was significantly associated with annualized memory decline in women (P = 0.00023) but not in men (P = 0.55) (Pdiff = 0.026 between men and women for regression estimates). Several vascular risk factors, such as fasting glucose levels, were predictive of AD/dementia in both men and women.
Conclusion
Our study may offer new insights into how blood tests can be better personalized for predicting future AD risk in women versus men.
Epigenetic Signatures of Cigarette Smoking Joehanes, Roby; Just, Allan C; Marioni, Riccardo E ...
Circulation. Cardiovascular genetics,
2016-October, Letnik:
9, Številka:
5
Journal Article
Recenzirano
Odprti dostop
DNA methylation leaves a long-term signature of smoking exposure and is one potential mechanism by which tobacco exposure predisposes to adverse health outcomes, such as cancers, osteoporosis, lung, ...and cardiovascular disorders.
To comprehensively determine the association between cigarette smoking and DNA methylation, we conducted a meta-analysis of genome-wide DNA methylation assessed using the Illumina BeadChip 450K array on 15 907 blood-derived DNA samples from participants in 16 cohorts (including 2433 current, 6518 former, and 6956 never smokers). Comparing current versus never smokers, 2623 cytosine-phosphate-guanine sites (CpGs), annotated to 1405 genes, were statistically significantly differentially methylated at Bonferroni threshold of P<1×10
(18 760 CpGs at false discovery rate <0.05). Genes annotated to these CpGs were enriched for associations with several smoking-related traits in genome-wide studies including pulmonary function, cancers, inflammatory diseases, and heart disease. Comparing former versus never smokers, 185 of the CpGs that differed between current and never smokers were significant P<1×10
(2623 CpGs at false discovery rate <0.05), indicating a pattern of persistent altered methylation, with attenuation, after smoking cessation. Transcriptomic integration identified effects on gene expression at many differentially methylated CpGs.
Cigarette smoking has a broad impact on genome-wide methylation that, at many loci, persists many years after smoking cessation. Many of the differentially methylated genes were novel genes with respect to biological effects of smoking and might represent therapeutic targets for prevention or treatment of tobacco-related diseases. Methylation at these sites could also serve as sensitive and stable biomarkers of lifetime exposure to tobacco smoke.
Association studies have achieved significant progress in mapping hundreds of genetic variants to major psychiatric disorders. But the underlying molecular mechanisms regarding specific genes, ...pathways involved, and interactions among the genes remain largely unknown. Gene expression and its regulation systems are critical for unraveling the causal relationships. This symposium presents cutting edge studies of brain gene expression regulation and its relevance to disease associations.
Hermona Soreq from the Hebrew University of Jerusalem will present a study of microRNA (miR) and pseudogene expression and their roles in psychiatry. A selected group of non-coding pseudogenes (PSGs) carry micro RNA (miR) recognition elements (PSG+MRE) compete with brain-expressed genes for the available miR regulators. Furthermore, SNPs surrounding these coding genes tend to be more abundant in psychiatric patients compared to controls. They used transfection-mediated over-expression of PSG+MRE and GapmeR-directed suppression of selected cholinergic transcripts sharing MREs with them in cultured human cells, and demonstrated bi-directional modulation of the interaction of these transcripts with miRs. The study illustrated functional roles of PSGs+MRE in cholinergic functioning, with potential impact on mental disorders.
Seth Ament from the Institute for Systems Biology will present a study of transcription factor (TF) binding targets in the brain. They reconstructed a model for the genomic binding sites and functional target genes of 778 TFs in the human brain by integrating large-scale epigenomics and transcriptomics datasets. Using this model, they predicted master regulator transcription factors and functional non-coding variants associated with risk for bipolar disorder and schizophrenia. They experimentally validated the prediction that a master regulator transcription factor, POU3F2, interacts with a risk-associated SNP to modulate the VRK2 promoter.
Chunyu Liu from the University of Illinois at Chicago will present a study of co-expression networks involving noncoding RNAs. They retrieved lncRNAs mapped to the seven major CNV deletion regions known to increase risks of developing schizophrenia and carried out weighted gene co-expression network analysis (WGCNA) using data from Genotype-Tissue Expression (GTEx) and BrainSpan projects to look for co-expression modules that harbor CNV-lncRNAs. They identified coexpression modules that were associated with male reproduction in male individuals and associated with neuronal functions in both male and female individuals. The findings suggest that lncRNAs inside those rare CNVs might play significant temporal and spatial roles in regulating other protein-coding genes and subsequently contribute to schizophrenia risk.
Hae Kyung Im from the University of Chicago will present the PrediXcan method, which was developed by him, Nancy Cox, and colleagues. By using genotype to predict expression (or other molecular traits) and correlating them with the trait of interest. They have developed prediction models for gene expression in 40 human tissues using the GTEx and Depression Genes Network data. They also extended the method so that only summary statistics are needed to infer PrediXcan results so that they can perform large meta analysis. Using this new method called MetaXcan they have generated results for 117 phenotypes with publicly available GWAS meta-analysis results.
Progress In Psychiatric Genetics In China Burmeister, Margit; Liu, Chunyu; Schulze, Thomas G.
European neuropsychopharmacology,
2017, 2017-00-00, Letnik:
27
Journal Article
Recenzirano
The purpose of this symposium is to highlight recent progress in psychiatric genetics in Chinese samples, complementing findings largely from Caucasian samples. We will stress commonalities and ...differences between existing studies and Chinese studies.
Weihua Yue from Peking University reports on a multi-site GWAS of schizophrenia with >10,000 samples. 13 SNPs were selected for replication in another 10,000 samples. 4 SNPs in 3 regions out of 13 survived after confirmation in the replication sample, 9/13 SNPs were in the same direction, and 7/13 SNPs were both p<0.05 and in the same direction. One SNP in 2p16.1 is near a region on 2p16.3 implicated previously (2011) in schizophrenia in a different Han Chinese sample, while two hits, on 10q24.32 and 6p22.1 appear to be novel. Polygenic Risk scores from Caucasian schizophrenia GWAS only moderately predicted case-control status in Chinese (R2 of 1.5-5.7 %).
Yin Yao from NIMH integrated functional magnetic resonance imaging (fMRI) and brain-gene ResNet (BGR) data to identify functional pathways associated with SCZ phenotypes. Automated Anatomical Labeling based brain connectivity analysis on fMRI data and Gene Set and Subnetwork Enrichment Analyses identified 4 SCZ candidate brain regions (P<1e-5) using fMRI data alone, which were replicated in the BGR data. These 4 SCZ candidate brain regions were related to 26 SCZ candidate genes, which were enriched in 62 genetic SCZ candidate pathways (P-value<1e-4), including those related to brain functional development (P<<1e-5), and implicating 7 genes, SNAP25, APP, MAPT, APOE, NTRK2, GRM5, and BDNF as top candidates.
Gang Chen from Nanjing University of Chinese Medicine will report on a GWAS of alcohol dependence symptom count (ADSC) in sample of 3838 European and African Americans from the “Study of Addiction: Genetics and Environment”. Using a mixed linear approach, 20 SNPs showed significant (permutation testing) association with ADSC after accounting for ethnicity, co-morbidities, and including additive as well as dominance and epistasis in the model. Association with the previously known ADH1C gene was confirmed, as well as several other known and new genes. The detected SNPs explain ~20% of the variance, half of which is accounted for by dominance and epistatic interactions, suggesting such networks are important in the genetic architecture of alcoholism.
Margit Burmeister will report on implementing in China Srijan Sen’s “medical intern health study”. Medical graduates are recruited after matching in now 55 hospitals in the US. Baseline surveys include personality, stress level, other psychological tests and the PHQ9 depression score. Depression increases from ~4% of incoming Medical graduates to ~ 26% during internship. Perceived stress, work hour and medical errors are associated with increased PHQ9 scores. Most residents do not seek care for their depression symptoms, out of fear of reprisal. In China, a formal residency program has recently been introduced in several cities. Interviews with residents documented similar concerns as in the US. Our pilot data (N=75, ~75% participation) in 2015 in Peking Union Medical College demonstrate a similar increase of depression scores from ~4% to ~ 22%, suggesting that work-stress induced depression may be modeled similarly in China as in the US, where a GWAS of the first ~7500 interns will soon become available.
In order to investigate the effect of temperatures and operating modes on extracellular polymeric substances (EPS) contents, three sequencing batch reactors (SBRs) were operated at temperatures of ...15, 25, and 35 °C (R
, R
, and R
, respectively), with two SBRs operated under alternating anoxic/oxic conditions (R
and R
, respectively). Results showed that higher contents of tightly bound EPS (TB-EPS) and total EPS appeared in R
, while loosely bound EPS (LB-EPS) dominated in R
. In all three kinds of EPS (LB-EPS, TB-EPS and total EPS) assessed, protein was the main component in R
and R
, while polysaccharides dominated in R
. Moreover, compared with R
, R
was favorable for the production of the three kinds of EPS. Furthermore, three kinds of EPS and their components were augmented during the nitrification process, while they declined during the denitrification process under all conditions except for R
.
A novel organic polymorphic luminogen, (Z)-N-((benzoylimino) (4-(diphenylamino)phenyl)methyl)-N-(4-fluorophenyl)benzamide (DPA-PYZ-F), has been designed and synthesized successfully by a green ...photo-oxidation reaction. Two polymorphs (FB and FG) based on DPA-PYZ-F with different conformations display blue and green fluorescence, respectively. The emission of the newly obtained polymorphic molecule can be switched through the response to a mechanical force, thermal stimulus and protonic acid. The photophysical property tests and single crystal structural analysis disclosed that the mechanical force stimuli-responsive behavior of the FB and FG samples originate from the change of molecular arrangement. More significantly, FT-IR spectroscopy confirmed that the conformation transition from the FG to the FB could be achieved by thermal stimulus at 430 K. Additionally, protonation−deprotonation of the benzoylimino moieties in DPA-PYZ-F induced a remarkable fluorescence on-off characteristics upon protonic acid and thermal stimulus. The multi-stimuli response performance endows the new kind of molecule with the potential as a candidate for applications in mechanical force, thermal and protonic acid sensing.
Display omitted
•A new multi-stimuli-responsive molecule of benzoimido-benzamide derivatives.•The fluorescence emission are switched through the response to force, thermal and protonic acid.•The conformation conversion from the green-emissive phase to the blue one.
Humans use binocular disparity to extract depth information from two-dimensional retinal images in a process called stereopsis. Previous studies usually introduce the standard univariate analysis to ...describe the correlation between disparity level and brain activity within a given brain region based on functional magnetic resonance imaging (fMRI) data. Recently, multivariate pattern analysis has been developed to extract activity patterns across multiple voxels for deciphering categories of binocular disparity. However, the functional connectivity (FC) of patterns based on regions of interest or voxels and their mapping onto disparity category perception remain unknown. The present study extracted functional connectivity patterns for three disparity conditions (crossed disparity, uncrossed disparity, and zero disparity) at distinct spatial scales to decode the binocular disparity. Results of 27 subjects’ fMRI data demonstrate that FC features are more discriminatory than traditional voxel activity features in binocular disparity classification. The average binary classification of the whole brain and visual areas are respectively 87% and 79% at single subject level, and thus above the chance level (50%). Our research highlights the importance of exploring functional connectivity patterns to achieve a novel understanding of 3D image processing.
There are many types of cells in the brain. They form the structure and execute the function of the brain. Cell classification conventionally uses location, morphology, and electrophysiological ...characteristics, often combined with cell type-specific markers. The cell type-specific marker gene is important for identifying cells in the brain and understanding the cell-specific mechanism underlying psychiatric disorders. However, the definition of the cell type-specific marker is frequently inconsistent across sources and studies. The relationship between cell types and psychiatric disorders is not clear.
The transcriptome and proteomics data of brain cells from human and mouse, by RNA-Seq and microarray from acutely isolation cell and primary culture cell were collected. We followed the convention quality control and analytical processing on the raw data. We collected 543 “putative” marker genes for ten cell types that have been commonly used from literature, In Situ Hybridization (ISH) databases and antibody companies. We defined general marker gene as their expressions in claimed target cells is the highest across all cell types tested. The expression difference for the rigorous marker gene defined as dividing the second highest expression level across all the other cell types by the expression level in target cell type. We set the fold change threshold for rigorous marker gene as at least 2. Parietal cortex tissue specimens from the Stanley Medical Research Institute (SMRI) Neuropathology Consortium and Array collections included schizophrenia, bipolar disorder and control samples were used for Weighted Gene Co-Expression Network Analysis (WGCNA).
With the datasets collected and the criteria provided, we found that 44 general marker genes showed stable specificity across all data collected. That included 29 neuron markers, eight astrocyte markers, seven oligodendrocyte markers. The averaged correlation values of specific marker genes between human and mouse, transcriptome and proteome, RNA-Seq and microarray, acutely isolation and primary culture were 0.50, 0.58, 0.51 and 0.43, respectively. According to the criterion for rigorous marker genes, 23 of the 44 marker genes showed more than two-fold changes in at least seven data sets evaluated. The most specific marker gene (fold change=710.31) is RELN, a neuron marker gene. It is not clear whether the non-specificity of rest of marker genes is related to data quality or technical artifacts in the data we can use for the assessment. In the WGCNA analysis, we found general marker genes of astrocyte were significantly enriched (p<2.2e-16) in disease associated module. The enriched six astrocyte marker genes (ALDH1L1, ALDOC, CLU, GJA1, SLC1A3, SLC4A4) showed co-expression with significant GWAS loci of schizophrenia and bipolar disorder in previous studies.
Based on transcriptome and proteomics of data of isolated cells, we confirmed a small set of 44 genes to be cell-type-specific in the brain while many other commonly-used marker genes will require additional studies to verify their specificity. Studies using these marker genes to tag cell types should exercise caution. Moreover, astrocyte marker genes enriched in disease-associated module co-expressed with known GWAS loci for schizophrenia and bipolar disorder. Further study and more data is need for evaluation of the rest non-specific marker genes and the co-expression of brain cell marker genes with psychiatric disorders.
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