Searching for Imaging Biomarkers of Psychotic Dysconnectivity

Background: Progress in precision psychiatry is predicated on identifying reliable individual-level diagnostic biomarkers. For psychosis, measures of structural and functional connectivity could be promising biomarkers given consistent reports of dysconnectivity across psychotic disorders using magnetic resonance imaging. Methods: We leveraged data from four independent cohorts of patients with psychosis and control subjects with observations from approximately 800 individuals. We used group-level analyses and two supervised machine learning algorithms (support vector machines and ridge regression) to test within-, between-, and across-sample classification performance of white matter and resting-state connectivity metrics. Results: Although we replicated group-level differences in brain connectivity, individual-level classification was suboptimal. Classification performance within samples was variable across folds (highest area under the curve [AUC] range = 0.30) and across datasets (average support vector machine AUC range = 0.50; average ridge regression AUC range = 0.18). Classification performance between samples was similarly variable or resulted in AUC values of approximately 0.65, indicating a lack of model generalizability. Furthermore, collapsing across samples (resting-state functional magnetic resonance imaging, N = 888; diffusion tensor imaging, N = 860) did not improve model performance (maximal AUC = 0.67). Ridge regression models generally outperformed support vector machine models, although classification performance was still suboptimal in terms of clinical relevance. Adjusting for demographic covariates did not greatly affect results. Conclusions: Connectivity measures were not suitable as diagnostic biomarkers for psychosis as assessed in this study. Our results do not negate that other approaches may be more successful, although it is clear that a systematic approach to individual-level classification with large independent validation samples is necessary to properly vet neuroimaging features as diagnostic biomarkers

Associations of cannabis use disorder with cognition, brain structure, and brain function in African Americans

Although previous studies have highlighted associations of cannabis use with cognition and brain morphometry, critical questions remain with regard to the association between cannabis use and brain structural and functional connectivity. In a cross-sectional community sample of 205 African Americans (age 18–70) we tested for associations of cannabis use disorder (CUD, n = 57) with multi-domain cognitive measures and structural, diffusion, and resting state brain-imaging phenotypes. Post hoc model evidence was computed with Bayes factors (BF) and posterior probabilities of association (PPA) to account for multiple testing. General cognitive functioning, verbal intelligence, verbal memory, working memory, and motor speed were lower in the CUD group compared with nonusers (p \u3c .011; 1.9 \u3c BF \u3c 3,217). CUD was associated with altered functional connectivity in a network comprising the motor-hand region in the superior parietal gyri and the anterior insula (p \u3c .04). These differences were not explained by alcohol, other drug use, or education. No associations with CUD were observed in cortical thickness, cortical surface area, subcortical or cerebellar volumes (0.12 \u3c BF \u3c 1.5), or graph-theoretical metrics of resting state connectivity (PPA \u3c 0.01). In a large sample collected irrespective of cannabis used to minimize recruitment bias, we confirm the literature on poorer cognitive functioning in CUD, and an absence of volumetric brain differences between CUD and non-CUD. We did not find evidence for or against a disruption of structural connectivity, whereas we did find localized resting state functional dysconnectivity in CUD. There was sufficient proof, however, that organization of functional connectivity as determined via graph metrics does not differ between CUD and non-user group

Genetic influences on externalizing psychopathology overlap with cognitive functioning and show developmental variation

Background: Questions remain regarding whether genetic influences on early life psychopathology overlap with cognition and show developmental variation. Methods: Using data from 9,421 individuals aged 8-21 from the Philadelphia Neurodevelopmental Cohort, factors of psychopathology were generated using a bifactor model of item-level data from a psychiatric interview. Five orthogonal factors were generated: anxious-misery (mood and anxiety), externalizing (attention deficit hyperactivity and conduct disorder), fear (phobias), psychosis-spectrum, and a general factor. Genetic analyses were conducted on a subsample of 4,662 individuals of European American ancestry. A genetic relatedness matrix was used to estimate heritability of these factors, and genetic correlations with executive function, episodic memory, complex reasoning, social cognition, motor speed, and general cognitive ability. Gene × Age analyses determined whether genetic influences on these factors show developmental variation. Results: Externalizing was heritable (h2 = 0.46, p = 1 × 10-6), but not anxious-misery (h2 = 0.09, p = 0.183), fear (h2 = 0.04, p = 0.337), psychosis-spectrum (h2 = 0.00, p = 0.494), or general psychopathology (h2 = 0.21, p = 0.040). Externalizing showed genetic overlap with face memory (ρg = -0.412, p = 0.004), verbal reasoning (ρg = -0.485, p = 0.001), spatial reasoning (ρg = -0.426, p = 0.010), motor speed (ρg = 0.659, p = 1x10-4), verbal knowledge (ρg = -0.314, p = 0.002), and general cognitive ability (g)(ρg = -0.394, p = 0.002). Gene × Age analyses revealed decreasing genetic variance (γg = -0.146, p = 0.004) and increasing environmental variance (γe = 0.059, p = 0.009) on externalizing. Conclusions: Cognitive impairment may be a useful endophenotype of externalizing psychopathology and, therefore, help elucidate its pathophysiological underpinnings. Decreasing genetic variance suggests that gene discovery efforts may be more fruitful in children than adolescents or young adults

Family-based analyses reveal novel genetic overlap between cytokine interleukin-8 and risk for suicide attempt

Background: Suicide is major public health concern. It is imperative to find robust biomarkers so that at-risk individuals can be identified in a timely and reliable manner. Previous work suggests mechanistic links between increased cytokines and risk for suicide, but questions remain regarding the etiology of this association, as well as the roles of sex and BMI. Methods: Analyses were conducted using a randomly-ascertained extended-pedigree sample of 1882 Mexican-American individuals (60% female, mean age = 42.04, range = 18-97). Genetic correlations were calculated using a variance components approach between the cytokines TNF-α, IL-6 and IL-8, and Lifetime Suicide Attempt and Current Suicidal Ideation. The potentially confounding effects of sex and BMI were considered. Results: 159 individuals endorse a Lifetime Suicide Attempt. IL-8 and IL-6 shared significant genetic overlap with risk for suicide attempt (ρg = 0.49, pFDR = 7.67 × 10-03; ρg = 0.53, pFDR = 0.01), but for IL-6 this was attenuated when BMI was included as a covariate (ρg = 0.37, se = 0.23, pFDR = 0.12). Suicide attempts were significantly more common in females (pFDR = 0.01) and the genetic overlap between IL-8 and risk for suicide attempt was significant in females (ρg = 0.56, pFDR = 0.01), but not in males (ρg = 0.44, pFDR = 0.30). Discussion: These results demonstrate that: IL-8 shares genetic influences with risk for suicide attempt; females drove this effect; and BMI should be considered when assessing the association between IL-6 and suicide. This finding represents a significant advancement in knowledge by demonstrating that cytokine alterations are not simply a secondary manifestation of suicidal behavior, but rather, the pathophysiology of suicide attempts is, at least partly, underpinned by the same biological mechanisms responsible for regulating inflammatory response

Imaging local genetic influences on cortical folding

Recent progress in deciphering mechanisms of human brain cortical folding leave unexplained whether spatially patterned genetic influences contribute to this folding. High-resolution in vivo brain MRI can be used to estimate genetic correlations (covariability due to shared genetic factors) in interregional cortical thickness, and biomechanical studies predict an influence of cortical thickness on folding patterns. However, progress has been hampered because shared genetic influences related to folding patterns likely operate at a scale that is much more local (cm) than that addressed in prior imaging studies. Here, we develop methodological approaches to examine local genetic influences on cortical thickness and apply these methods to two large, independent samples. We find that such influences are markedly heterogeneous in strength, and in some cortical areas are notably stronger in specific orientations relative to gyri or sulci. The overall, phenotypic local correlation has a significant basis in shared genetic factors and is highly symmetric between left and right cortical hemispheres. Furthermore, the degree of local cortical folding relates systematically with the strength of local correlations, which tends to be higher in gyral crests and lower in sulcal fundi. The relationship between folding and local correlations is stronger in primary sensorimotor areas and weaker in association areas such as prefrontal cortex, consistent with reduced genetic constraints on the structural topology of association cortex. Collectively, our results suggest that patterned genetic influences on cortical thickness, measurable at the scale of in vivo MRI, may be a causal factor in the development of cortical folding

Cognitive impairment from early to middle adulthood in patients with affective and nonaffective psychotic disorders

Background.—Cognitive impairment is a core feature of psychotic disorders, but the profile of impairment across adulthood, particularly in African-American populations, remains unclear. Methods.—Using cross-sectional data from a case–control study of African-American adults with affective (n = 59) and nonaffective (n = 68) psychotic disorders, we examined cognitive functioning between early and middle adulthood (ages 20–60) on measures of general cognitive ability, language, abstract reasoning, processing speed, executive function, verbal memory, and working memory. Results.—Both affective and nonaffective psychosis patients showed substantial and widespread cognitive impairments. However, comparison of cognitive functioning between controls and psychosis groups throughout early (ages 20–40) and middle (ages 40–60) adulthood also revealed age-associated group differences. During early adulthood, the nonaffective psychosis group showed increasing impairments with age on measures of general cognitive ability and executive function, while the affective psychosis group showed increasing impairment on a measure of language ability. Impairments on other cognitive measures remained mostly stable, although decreasing impairments on measures of processing speed, memory and working memory were also observed. Conclusions.—These findings suggest similarities, but also differences in the profile of cognitive dysfunction in adults with affective and nonaffective psychotic disorders. Both affective and nonaffective patients showed substantial and relatively stable impairments across adulthood. The nonaffective group also showed increasing impairments with age in general and executiv

Neurocognitive impairment in type 2 diabetes: evidence for shared genetic aetiology

Aims/hypothesis: Type 2 diabetes is associated with cognitive impairments, but it is unclear whether common genetic factors influence both type 2 diabetes risk and cognition. Methods: Using data from 1892 Mexican-American individuals from extended pedigrees, including 402 with type 2 diabetes, we examined possible pleiotropy between type 2 diabetes and cognitive functioning, as measured by a comprehensive neuropsychological test battery. Results: Negative phenotypic correlations (ρp) were observed between type 2 diabetes and measures of attention (Continuous Performance Test [CPT d\u27]: ρp = -0.143, p = 0.001), verbal memory (California Verbal Learning Test [CVLT] recall: ρp = -0.111, p = 0.004) and face memory (Penn Face Memory Test [PFMT]: ρp = -0.127, p = 0.002; PFMT Delayed: ρp = -0.148, p = 2 × 10-4), replicating findings of cognitive impairment in type 2 diabetes. Negative genetic correlations (ρg) were also observed between type 2 diabetes and measures of attention (CPT d\u27: ρg = -0.401, p = 0.001), working memory (digit span backward test: ρg = -0.380, p = 0.005), and face memory (PFMT: ρg = -0.476, p = 2 × 10-4; PFMT Delayed: ρg = -0.376, p = 0.005), suggesting that the same genetic factors underlying risk for type 2 diabetes also influence poor cognitive performance in these domains. Performance in these domains was also associated with type 2 diabetes risk using an endophenotype ranking value approach. Specifically, on measures of attention (CPT d\u27: β = -0.219, p = 0.005), working memory (digit span backward: β = -0.326, p = 0.035), and face memory (PFMT: β = -0.171, p = 0.023; PFMT Delayed: β = -0.215, p = 0.005), individuals with type 2 diabetes showed the lowest performance, while unaffected/unrelated individuals showed the highest performance, and those related to an individual with type 2 diabetes performed at an intermediate level. Conclusions/interpretation: These findings suggest that cognitive impairment may be a useful endophenotype of type 2 diabetes and, therefore, help to elucidate the pathophysiological underpinnings of this chronic disease. Data availability: The data analysed in this study is available in dbGaP: www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001215.v2.p2

The Genetic contribution to solving the cocktail-party problem

Communicating in everyday situations requires solving the cocktail-party problem, or segregating the acoustic mixture into its constituent sounds and attending to those of most interest. Humans show dramatic variation in this ability, leading some to experience real-world problems irrespective of whether they meet criteria for clinical hearing loss. Here, we estimated the genetic contribution to cocktail-party listening by measuring speech-reception thresholds (SRTs) in 425 people from large families and ranging in age from 18 to 91 years. Roughly half the variance of SRTs was explained by genes (h 2 = 0.567). The genetic correlation between SRTs and hearing thresholds (HTs) was medium (ρ G = 0.392), suggesting that the genetic factors influencing cocktail-party listening were partially distinct from those influencing sound sensitivity. Aging and socioeconomic status also strongly influenced SRTs. These findings may represent a first step toward identifying genes for hidden hearing loss, or hearing problems in people with normal HTs

Reprogramming the Mycobacterium tuberculosis transcriptome during pathogenesis

Transcriptional profiling has revealed that Mycobacterium tuberculosis adapts both its metabolic and respiratory states during infection, utilising lipids as a carbon source and switching to alternative electron acceptors. These global gene expression datasets may be exploited to identify virulence determinants and to screen for new targets for rational drug design. Characterising the changing physiological predicament of distinct M. tb populations during infection will help expose the fundamental biology of M. tb highlighting mechanisms that influence tuberculosis pathogenicity

High-throughput sequencing of Astrammina rara: Sampling the giant genome of a giant foraminiferan protist

<p>Abstract</p> <p>Background</p> <p>Foraminiferan protists, which are significant players in most marine ecosystems, are also genetic innovators, harboring unique modifications to proteins that make up the basic eukaryotic cell machinery. Despite their ecological and evolutionary importance, foraminiferan genomes are poorly understood due to the extreme sequence divergence of many genes and the difficulty of obtaining pure samples: exogenous DNA from ingested food or ecto/endo symbionts often vastly exceed the amount of "native" DNA, and foraminiferans cannot be cultured axenically. Few foraminiferal genes have been sequenced from genomic material, although partial sequences of coding regions have been determined by EST studies and mass spectroscopy. The lack of genomic data has impeded evolutionary and cell-biology studies and has also hindered our ability to test ecological hypotheses using genetic tools.</p> <p>Results</p> <p>454 sequence analysis was performed on a library derived from whole genome amplification of microdissected nuclei of the Antarctic foraminiferan <it>Astrammina rara</it>. Xenogenomic sequence, which was shown not to be of eukaryotic origin, represented only 12% of the sample. The first foraminiferal examples of important classes of genes, such as tRNA genes, are reported, and we present evidence that sequences of mitochondrial origin have been translocated to the nucleus. The recovery of a 3' UTR and downstream sequence from an actin gene suggests that foraminiferal mRNA processing may have some unusual features. Finally, the presence of a co-purified bacterial genome in the library also permitted the first calculation of the size of a foraminiferal genome by molecular methods, and statistical analysis of sequence from different genomic sources indicates that low-complexity tracts of the genome may be endoreplicated in some stages of the foraminiferal life cycle.</p> <p>Conclusions</p> <p>These data provide the first window into genomic organization and genetic control in these organisms, and also complement and expands upon information about foraminiferal genes based on EST projects. The genomic data obtained are informative for environmental and cell-biological studies, and will also be useful for efforts to understand relationships between foraminiferans and other protists.</p