Heritability of Gene Expression Measured from Peripheral Blood in Older Adults.

The contributions of genetic variation and the environment to gene expression may change across the lifespan. However, few studies have investigated the heritability of blood gene expression in older adults. The current study therefore aimed to investigate this question in a community sample of older adults. A total of 246 adults (71 MZ and 52 DZ twins, 69.91% females; mean age-75.79 ± 5.44) were studied. Peripheral blood gene expression was assessed using Illumina microarrays. A heritability analysis was performed using structural equation modelling. There were 5269 probes (19.9%) from 4603 unique genes (23.9%) (total 26,537 probes from 19,256 genes) that were significantly heritable (mean h2 = 0.40). A pathway analysis of the top 10% of significant genes showed enrichment for the immune response and ageing-associated genes. In a comparison with two other gene expression twin heritability studies using adults from across the lifespan, there were 38 out of 9479 overlapping genes that were significantly heritable. In conclusion, our study found ~24% of the available genes for analysis were heritable in older adults, with only a small number common across studies that used samples from across adulthood, indicating the importance of examining gene expression in older age groups.

Multifactorial structure of cognitive assessment tests in the UK Biobank: A combined exploratory factor and structural equation modeling analyses.

Introduction: The UK Biobank cognitive assessment data has been a significant resource for researchers looking to investigate predictors and modifiers of cognitive abilities and associated health outcomes in the general population. Given the diverse nature of this data, researchers use different approaches - from the use of a single test to composing the general intelligence score, g, across the tests. We argue that both approaches are suboptimal - one being too specific and the other one too general - and suggest a novel multifactorial solution to represent cognitive abilities. Methods: Using a combined Exploratory Factor (EFA) and Exploratory Structural Equation Modeling Analyses (ESEM) we developed a three-factor model to characterize an underlying structure of nine cognitive tests selected from the UK Biobank using a Cattell-Horn-Carroll framework. We first estimated a series of probable factor solutions using the maximum likelihood method of extraction. The best solution for the EFA-defined factor structure was then tested using the ESEM approach with the aim of confirming or disconfirming the decisions made. Results: We determined that a three-factor model fits the UK Biobank cognitive assessment data best. Two of the three factors can be assigned to fluid reasoning (Gf) with a clear distinction between visuospatial reasoning and verbal-analytical reasoning. The third factor was identified as a processing speed (Gs) factor. Discussion: This study characterizes cognitive assessment data in the UK Biobank and delivers an alternative view on its underlying structure, suggesting that the three factor model provides a more granular solution than g that can further be applied to study different facets of cognitive functioning in relation to health outcomes and to further progress examination of its biological underpinnings.

General intelligence and executive functioning are overlapping but separable at genetic and molecular pathway levels: An analytical review of existing GWAS findings.

Understanding the genomic architecture and molecular mechanisms of cognitive functioning in healthy individuals is critical for developing tailored interventions to enhance cognitive functioning, as well as for identifying targets for treating impaired cognition. There has been substantial progress in uncovering the genetic composition of the general cognitive ability (g). However, there is an ongoing debate whether executive functioning (EF)-another key predictor of cognitive health and performance, is separable from general g. To provide an analytical review on existing findings on genetic influences on the relationship between g and EF, we re-analysed a subset of genome-wide association studies (GWAS) from the GWAS catalogue that used measures of g and EF as outcomes in non-clinical populations. We identified two sets of single nucleotide polymorphisms (SNPs) associated with g (1,372 SNPs across 12 studies), and EF (300 SNPs across 5 studies) at p<5x10-6. A comparative analysis of GWAS-identified g and EF SNPs in high linkage disequilibrium (LD), followed by pathway enrichment analyses suggest that g and EF are overlapping but separable at genetic variant and molecular pathway levels, however more evidence is required to characterize the genetic overlap/distinction between the two constructs. While not without limitations, these findings may have implications for navigating further research towards translatable genetic findings for cognitive remediation, enhancement, and augmentation.

Building a transdisciplinary expert consensus on the cognitive drivers of performance under pressure: An international multi-panel Delphi study.

Introduction: The ability to perform optimally under pressure is critical across many occupations, including the military, first responders, and competitive sport. Despite recognition that such performance depends on a range of cognitive factors, how common these factors are across performance domains remains unclear. The current study sought to integrate existing knowledge in the performance field in the form of a transdisciplinary expert consensus on the cognitive mechanisms that underlie performance under pressure. Methods: International experts were recruited from four performance domains [(i) Defense; (ii) Competitive Sport; (iii) Civilian High-stakes; and (iv) Performance Neuroscience]. Experts rated constructs from the Research Domain Criteria (RDoC) framework (and several expert-suggested constructs) across successive rounds, until all constructs reached consensus for inclusion or were eliminated. Finally, included constructs were ranked for their relative importance. Results: Sixty-eight experts completed the first Delphi round, with 94% of experts retained by the end of the Delphi process. The following 10 constructs reached consensus across all four panels (in order of overall ranking): (1) Attention; (2) Cognitive Control-Performance Monitoring; (3) Arousal and Regulatory Systems-Arousal; (4) Cognitive Control-Goal Selection, Updating, Representation, and Maintenance; (5) Cognitive Control-Response Selection and Inhibition/Suppression; (6) Working memory-Flexible Updating; (7) Working memory-Active Maintenance; (8) Perception and Understanding of Self-Self-knowledge; (9) Working memory-Interference Control, and (10) Expert-suggested-Shifting. Discussion: Our results identify a set of transdisciplinary neuroscience-informed constructs, validated through expert consensus. This expert consensus is critical to standardizing cognitive assessment and informing mechanism-targeted interventions in the broader field of human performance optimization.

Downregulated transferrin receptor in the blood predicts recurrent MDD in the elderly cohort: A fuzzy forests approach.

BACKGROUND: At present, no predictive markers for Major Depressive Disorder (MDD) exist. The search for such markers has been challenging due to clinical and molecular heterogeneity of MDD, the lack of statistical power in studies and suboptimal statistical tools applied to multidimensional data. Machine learning is a powerful approach to mitigate some of these limitations. METHODS: We aimed to identify the predictive markers of recurrent MDD in the elderly using peripheral whole blood from the Sydney Memory and Aging Study (SMAS) (N = 521, aged over 65) and adopting machine learning methodology on transcriptome data. Fuzzy Forests is a Random Forests-based classification algorithm that takes advantage of the co-expression network structure between genes; it allows to alleviate the problem of p >> n via reducing the dimensionality of transcriptomic feature space. RESULTS: By adopting Fuzzy Forests on transcriptome data, we found that the downregulated TFRC (transferrin receptor) can predict recurrent MDD with an accuracy of 63%. LIMITATIONS: Although we corrected our data for several important confounders, we were not able to account for the comorbidities and medication taken, which may be numerous in the elderly and might have affected the levels of gene transcription. CONCLUSIONS: We found that downregulated TFRC is predictive of recurrent MDD, which is consistent with the previous literature, indicating the role of the innate immune system in depression. This study is the first to successfully apply Fuzzy Forests methodology on psychiatric condition, opening, therefore, a methodological avenue that can lead to clinically useful predictive markers of complex traits.

Co-expression network analysis of peripheral blood transcriptome identifies dysregulated protein processing in endoplasmic reticulum and immune response in recurrent MDD in older adults.

The molecular factors involved in the pathophysiology of major depressive disorder (MDD) remain poorly understood. One approach to examine the molecular basis of MDD is co-expression network analysis, which facilitates the examination of complex interactions between expression levels of individual genes and how they influence biological pathways affected in MDD. Here, we applied an unsupervised gene-network based approach to a prospective experimental design using microarray genome-wide gene expression from the peripheral whole blood of older adults. We utilised the Sydney Memory and Ageing Study (sMAS, N = 521) and the Older Australian Twins Study (OATS, N = 186) as discovery and replication cohorts, respectively. We constructed networks using Weighted Gene Co-expression Network Analysis (WGCNA), and correlated identified modules with four subtypes of depression: single episode, current, recurrent, and lifetime MDD. Four modules of highly co-expressed genes were associated with recurrent MDD (N = 27) in our discovery cohort (FDR<0.2), with no significant findings for a single episode, current or lifetime MDD. Functional characterisation of these modules revealed a complex interplay between dysregulated protein processing in the endoplasmic reticulum (ER), and innate and adaptive immune response signalling, with possible involvement of pathogen-related pathways. We were underpowered to replicate findings at the network level in an independent cohort (OATS), however; we found a significant overlap for 9 individual genes with similar co-expression and dysregulation patterns associated with recurrent MDD in both cohorts. Overall, our findings support other reports on dysregulated immune response and protein processing in the ER in MDD and provide novel insights into the pathophysiology of depression.

The prevalence and burden of mental and substance use disorders in Australia: Findings from the Global Burden of Disease Study 2015.

OBJECTIVES: Timely and accurate assessments of disease burden are essential for developing effective national health policies. We used the Global Burden of Disease Study 2015 to examine burden due to mental and substance use disorders in Australia. METHODS: For each of the 20 mental and substance use disorders included in Global Burden of Disease Study 2015, systematic reviews of epidemiological data were conducted, and data modelled using a Bayesian meta-regression tool to produce prevalence estimates by age, sex, geography and year. Prevalence for each disorder was then combined with a disorder-specific disability weight to give years lived with disability, as a measure of non-fatal burden. Fatal burden was measured as years of life lost due to premature mortality which were calculated by combining the number of deaths due to a disorder with the life expectancy remaining at the time of death. Disability-adjusted life years were calculated by summing years lived with disability and years of life lost to give a measure of total burden. Uncertainty was calculated around all burden estimates. RESULTS: Mental and substance use disorders were the leading cause of non-fatal burden in Australia in 2015, explaining 24.3% of total years lived with disability, and were the second leading cause of total burden, accounting for 14.6% of total disability-adjusted life years. There was no significant change in the age-standardised disability-adjusted life year rates for mental and substance use disorders from 1990 to 2015. CONCLUSION: Global Burden of Disease Study 2015 found that mental and substance use disorders were leading contributors to disease burden in Australia. Despite several decades of national reform, the burden of mental and substance use disorders remained largely unchanged between 1990 and 2015. To reduce this burden, effective population-level preventions strategies are required in addition to effective interventions of sufficient duration and coverage.

Health Effects of Overweight and Obesity in 195 Countries over 25 Years.

BACKGROUND: Although the rising pandemic of obesity has received major attention in many countries, the effects of this attention on trends and the disease burden of obesity remain uncertain. METHODS: We analyzed data from 68.5 million persons to assess the trends in the prevalence of overweight and obesity among children and adults between 1980 and 2015. Using the Global Burden of Disease study data and methods, we also quantified the burden of disease related to high body-mass index (BMI), according to age, sex, cause, and BMI in 195 countries between 1990 and 2015. RESULTS: In 2015, a total of 107.7 million children and 603.7 million adults were obese. Since 1980, the prevalence of obesity has doubled in more than 70 countries and has continuously increased in most other countries. Although the prevalence of obesity among children has been lower than that among adults, the rate of increase in childhood obesity in many countries has been greater than the rate of increase in adult obesity. High BMI accounted for 4.0 million deaths globally, nearly 40% of which occurred in persons who were not obese. More than two thirds of deaths related to high BMI were due to cardiovascular disease. The disease burden related to high BMI has increased since 1990; however, the rate of this increase has been attenuated owing to decreases in underlying rates of death from cardiovascular disease. CONCLUSIONS: The rapid increase in the prevalence and disease burden of elevated BMI highlights the need for continued focus on surveillance of BMI and identification, implementation, and evaluation of evidence-based interventions to address this problem. (Funded by the Bill and Melinda Gates Foundation.).

Summaries of plenary and selected symposia sessions at the XXIV World Congress of Psychiatric Genetics; Jerusalem, Israel; 30 October 2016-3 November 2016.

The XXII World Congress of Psychiatric Genetics, sponsored by the International Society of Psychiatric Genetics, took place in Jerusalem, Israel, from 30 October 2016 to 3 November 2016. A total of 372 participants gathered to discuss the latest findings in the field. The following report was written by early career investigator travel awardees, and student and postdoctoral attendees. Each was assigned one or more sessions as a rapporteur. This manuscript represents topics covered in most, but not all of the presentations during the conference, and contains some of the major notable new findings reported.

A systematic review on the association between inflammatory genes and cognitive decline in non-demented elderly individuals.

Cognitive impairment, or decline, is not only a feature of Alzheimer׳s disease and other forms of dementia but also normal ageing. Abundant evidence from epidemiological studies points towards perturbed inflammatory mechanisms in aged individuals, though the cause-effect nature of this apparent relationship is difficult to establish. Genetic association studies focusing on polymorphism in and around inflammatory genes represent a viable approach to establish whether inflammatory mechanisms might play a causal role in cognitive decline, whilst also enabling the identification of specific genes potentially influencing specific cognitive facets. Thus, here we provide a review of published genetic association studies investigating inflammatory genes in the context of cognitive decline in elderly, non-demented, samples. Numerous candidate gene association studies have been performed to date, focusing almost exclusively on genes encoding major cytokines. Some of these studies report significant cognitive domain-specific associations implicating Interleukin 1ß (IL1ß) (rs16944), Tumour Necrosis Factor α (TNFα) (rs1800629) and C-reactive protein (CRP) in various domains of cognitive function. However, the majority of these studies are lacking in statistical power and have other methodological limitations, suggesting some of them may have yielded false positive results. Genome-wide association studies have implicated less direct and less obvious regulators of inflammatory processes (i.e., PDE7A, HS3ST4, SPOCK3), indicating that a shift away from the major cytokine-encoding genes in future studies will be important. Furthermore, better cohesion across studies with regards to the cognitive test batteries administered to participants along with the continued application of longitudinal designs will be vital.

Differential gene expression in brain and peripheral tissues in depression across the life span: A review of replicated findings.

There is a growing body of research investigating the gene expression signature of depression at the genome-wide level, with potential for the discovery of novel pathophysiological mechanisms of depression. However, heterogeneity of depression, dynamic nature of gene expression patterns and various sources of noise have resulted in inconsistent findings. We systematically review the current state of transcriptome profiling of depression in the brain and peripheral tissues with a particular focus on replicated findings at the single gene level. By examining 16 brain regions and 5 cell types from the periphery, we identified 57 replicated differentially expressed genes in the brain and 21 in peripheral tissues. Functional overlap between brain and periphery strongly implicates shared pathways in a comorbid phenotype of depression and cardiovascular disease. The findings highlight dermal fibroblasts as a promising experimental model for depression biomarker research, provide partial support for all major theories of depression and suggest a novel candidate gene, PXMP2, which plays a critical role in lipid and reactive oxygen species metabolism.