Mitochondrial localization and function of a subset of 22q11 deletion syndrome candidate genes

Six genes in the 1.5 MB region of chromosome 22 deleted in DiGeorge/22q11 Deletion Syndrome—Mrpl40, Prodh, Slc25a1, Txnrd2, T10, and Zdhhc8—encode mitochondrial proteins. All six genes are expressed in the brain, and maximal expression coincides with peak forebrain synaptogenesis shortly after birth. Furthermore, their protein products are associated with brain mitochondria, including those in synaptic terminals. Among the six, only Zddhc8 influences mitochondria-regulated apoptosis when overexpressed, and appears to interact biochemically with established mitochondrial proteins. Zdhhc8 has an apparent interaction with Uqcrc1, a component of mitochondrial complex III. The two proteins are coincidently expressed in presynaptic processes; however, Zdhhc8 is more frequently seen in glutamatergic terminals. 22q11 deletion may alter metabolic properties of cortical mitochondria during early post-natal life, since expression complex III components, including Uqcrc1, is significantly increased at birth in a mouse model of 22q11 deletion, and declines to normal values in adulthood. Our results suggest that altered dosage of one, or several 22q11 mitochondrial genes, particularly during early postnatal cortical development, may disrupt neuronal metabolism or synaptic signaling

Using Virtual Agents to Guide Attention in Multi-task Scenarios

Kulms P, Kopp S. Using Virtual Agents to Guide Attention in Multi-task Scenarios. In: Aylett R, Krenn B, Pelachaud C, Shimodaira H, eds. Intelligent Virtual Agents. Lecture Notes in Computer Science. Vol 8108. Berlin, Heidelberg: Springer Berlin Heidelberg; 2013: 295-302

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

ARIA 2016: Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

The Allergic Rhinitis and its Impact on Asthma (ARIA) initiative commenced during a World Health Organization workshop in 1999. The initial goals were (1) to propose a new allergic rhinitis classification, (2) to promote the concept of multi-morbidity in asthma a

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele