[Show abstract][Hide abstract] ABSTRACT: The apolipoprotein E (APOE) ɛ4 allele is the best established genetic risk factor for Alzheimer's disease (AD) and has been previously associated with alterations in structural gray matter and changes in functional brain activity in healthy middle-aged individuals and older non-demented subjects. In order to determine the neural mechanism by which APOE polymorphisms affect white matter (WM) structure, we investigated the diffusion characteristics of WM tracts in carriers and non-carriers of the APOE ɛ4 and ɛ2 alleles using an unbiased whole brain analysis technique (Tract Based Spatial Statistics) in a healthy young adolescent (14 years) cohort. A large sample of healthy young adolescents (n = 575) were selected from the European neuroimaging-genetics IMAGEN study with available APOE status and accompanying diffusion imaging data. MR Diffusion data was acquired on 3T systems using 32 diffusion-weighted (DW) directions and 4 non-DW volumes (b-value = 1,300 s/mm2 and isotropic resolution of 2.4×2.4×2.4 mm). No significant differences in WM structure were found in diffusion indices between carriers and non-carriers of the APOE ɛ4 and ɛ2 alleles, and dose-dependent effects of these variants were not established, suggesting that differences in WM structure are not modulated by the APOE polymorphism. In conclusion, our results suggest that microstructural properties of WM structure are not associated with the APOE ɛ4 and ɛ2 alleles in young adolescence, suggesting that the neural effects of these variants are not evident in 14-year-olds and may only develop later in life.
[Show abstract][Hide abstract] ABSTRACT: Cannabis use during adolescence is known to increase the risk for schizophrenia in men. Sex differences in the dynamics of brain maturation during adolescence may be of particular importance with regard to vulnerability of the male brain to cannabis exposure.
To evaluate whether the association between cannabis use and cortical maturation in adolescents is moderated by a polygenic risk score for schizophrenia.
Observation of 3 population-based samples included initial analysis in 1024 adolescents of both sexes from the Canadian Saguenay Youth Study (SYS) and follow-up in 426 adolescents of both sexes from the IMAGEN Study from 8 European cities and 504 male youth from the Avon Longitudinal Study of Parents and Children (ALSPAC) based in England. A total of 1577 participants (aged 12-21 years; 899 [57.0%] male) had (1) information about cannabis use; (2) imaging studies of the brain; and (3) a polygenic risk score for schizophrenia across 108 genetic loci identified by the Psychiatric Genomics Consortium. Data analysis was performed from March 1 through December 31, 2014.
Cortical thickness derived from T1-weighted magnetic resonance images. Linear regression tests were used to assess the relationships between cannabis use, cortical thickness, and risk score.
Across the 3 samples of 1574 participants, a negative association was observed between cannabis use in early adolescence and cortical thickness in male participants with a high polygenic risk score. This observation was not the case for low-risk male participants or for the low- or high-risk female participants. Thus, in SYS male participants, cannabis use interacted with risk score vis-à-vis cortical thickness (P = .009); higher scores were associated with lower thickness only in males who used cannabis. Similarly, in the IMAGEN male participants, cannabis use interacted with increased risk score vis-à-vis a change in decreasing cortical thickness from 14.5 to 18.5 years of age (t137 = -2.36; P = .02). Finally, in the ALSPAC high-risk group of male participants, those who used cannabis most frequently (≥61 occasions) had lower cortical thickness than those who never used cannabis (difference in cortical thickness, 0.07 [95% CI, 0.01-0.12]; P = .02) and those with light use (<5 occasions) (difference in cortical thickness, 0.11 [95% CI, 0.03-0.18]; P = .004).
Cannabis use in early adolescence moderates the association between the genetic risk for schizophrenia and cortical maturation among male individuals. This finding implicates processes underlying cortical maturation in mediating the link between cannabis use and liability to schizophrenia.
[Show abstract][Hide abstract] ABSTRACT: Alcohol abuse is highly prevalent, but little is understood about the molecular causes. Here, we report that Ras suppressor 1 (Rsu1) affects ethanol consumption in flies and humans. Drosophila lacking Rsu1 show reduced sensitivity to ethanol-induced sedation. We show that Rsu1 is required in the adult nervous system for normal sensitivity and that it acts downstream of the integrin cell adhesion molecule and upstream of the Ras-related C3 botulinum toxin substrate 1 (Rac1) GTPase to regulate the actin cytoskeleton. In an ethanol preference assay, global loss of Rsu1 causes high naive preference. In contrast, flies lacking Rsu1 only in the mushroom bodies of the brain show normal naive preference but then fail to acquire ethanol preference like normal flies. Rsu1 is, thus, required in distinct neurons to modulate naive and acquired ethanol preference. In humans, we find that polymorphisms in RSU1 are associated with brain activation in the ventral striatum during reward anticipation in adolescents and alcohol consumption in both adolescents and adults. Together, these data suggest a conserved role for integrin/Rsu1/Rac1/actin signaling in modulating reward-related phenotypes, including ethanol consumption, across phyla.
Proceedings of the National Academy of Sciences 07/2015; 112(30-30):E4085-93. DOI:10.1073/pnas.1417222112 · 9.67 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: The authors examined whether alterations in the brain's reward network operate as a mechanism across the spectrum of risk for depression. They then tested whether these alterations are specific to anhedonia as compared with low mood and whether they are predictive of depressive outcomes.
Functional MRI was used to collect blood-oxygen-level-dependent (BOLD) responses to anticipation of reward in the monetary incentive task in 1,576 adolescents in a community-based sample. Adolescents with current subthreshold depression and clinical depression were compared with matched healthy subjects. In addition, BOLD responses were compared across adolescents with anhedonia, low mood, or both symptoms, cross-sectionally and longitudinally.
Activity in the ventral striatum was reduced in participants with subthreshold and clinical depression relative to healthy comparison subjects. Low ventral striatum activation predicted transition to subthreshold or clinical depression in previously healthy adolescents at 2-year follow-up. Brain responses during reward anticipation decreased in a graded manner between healthy adolescents, adolescents with current or future subthreshold depression, and adolescents with current or future clinical depression. Low ventral striatum activity was associated with anhedonia but not low mood; however, the combined presence of both symptoms showed the strongest reductions in the ventral striatum in all analyses.
The findings suggest that reduced striatal activation operates as a mechanism across the risk spectrum for depression. It is associated with anhedonia in healthy adolescents and is a behavioral indicator of positive valence systems, consistent with predictions based on the Research Domain Criteria.
American Journal of Psychiatry 04/2015; DOI:10.1176/appi.ajp.2015.14101298 · 12.30 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Resilience is the capacity of individuals to resist mental disorders despite exposure to stress. Little is known about its neural underpinnings. The putative variation of white-matter microstructure with resilience in adolescence, a critical period for brain maturation and onset of high-prevalence mental disorders, has not been assessed by diffusion tensor imaging (DTI). Lower fractional anisotropy (FA) though, has been reported in the corpus callosum (CC), the brain's largest white-matter structure, in psychiatric and stress-related conditions. We hypothesized that higher FA in the CC would characterize stress-resilient adolescents.
Three groups of adolescents recruited from the community were compared: resilient with low risk of mental disorder despite high exposure to lifetime stress (n = 55), at-risk of mental disorder exposed to the same level of stress (n = 68), and controls (n = 123). Personality was assessed by the NEO-Five Factor Inventory (NEO-FFI). Voxelwise statistics of DTI values in CC were obtained using tract-based spatial statistics. Regional projections were identified by probabilistic tractography.
Higher FA values were detected in the anterior CC of resilient compared to both non-resilient and control adolescents. FA values varied according to resilience capacity. Seed regional changes in anterior CC projected onto anterior cingulate and frontal cortex. Neuroticism and three other NEO-FFI factor scores differentiated non-resilient participants from the other two groups.
High FA was detected in resilient adolescents in an anterior CC region projecting to frontal areas subserving cognitive resources. Psychiatric risk was associated with personality characteristics. Resilience in adolescence may be related to white-matter microstructure.
Psychological Medicine 03/2015; 45(11):1-10. DOI:10.1017/S0033291715000239 · 5.94 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Human brain anatomy is strikingly diverse and highly inheritable: genetic factors may explain up to 80% of its variability. Prior studies have tried to detect genetic variants with a large effect on neuroanatomical diversity, but those currently identified account for <5% of the variance. Here, based on our analyses of neuroimaging and whole-genome genotyping data from 1765 subjects, we show that up to 54% of this heritability is captured by large numbers of single-nucleotide polymorphisms of small-effect spread throughout the genome, especially within genes and close regulatory regions. The genetic bases of neuroanatomical diversity appear to be relatively independent of those of body size (height), but shared with those of verbal intelligence scores. The study of this genomic architecture should help us better understand brain evolution and disease.Molecular Psychiatry advance online publication, 16 September 2014; doi:10.1038/mp.2014.99.
[Show abstract][Hide abstract] ABSTRACT: A comprehensive account of the causes of alcohol misuse must accommodate individual differences in biology, psychology and environment, and must disentangle cause and effect. Animal models1 can demonstrate the effects of neurotoxic substances; however, they provide limited insight into the psycho-social and higher cognitive factors involved in the initiation of substance use and progression to misuse. One can search for pre-existing risk factors by testing for endophenotypic biomarkers2 in non-using relatives; however, these relatives may have personality or neural resilience factors that protect them from developing dependence3. A longitudinal study has potential to identify predictors of adolescent substance misuse, particularly if it can incorporate a wide range of potential causal factors, both proximal and distal, and their influence on numerous social, psychological and biological mechanisms4. Here we apply machine learning to a wide range of data from a large sample of adolescents (n = 692) to generate models of current and future adolescent alcohol misuse that incorporate brain structure and function, individual personality and cognitive differences, environmental factors (including gestational cigarette and alcohol exposure), life experiences, and candidate genes. These models were accurate and generalized to novel data, and point to life experiences, neurobiological differences and personality as important antecedents of binge drinking. By identifying the vulnerability factors underlying individual differences in alcohol misuse, these models shed light on the aetiology of alcohol misuse and suggest targets for prevention.
[Show abstract][Hide abstract] ABSTRACT: Brain imaging is a natural intermediate phenotype to understand the link between genetic information and behavior or brain pathologies risk factors. Massive efforts have been made in the last few years to acquire high-dimensional neuroimaging and genetic data on large cohorts of subjects. The statistical analysis of such data is carried out with increasingly sophisticated techniques and represents a great computational challenge. Fortunately, increasing computational power in distributed architectures can be harnessed, if new neuroinformatics infrastructures are designed and training to use these new tools is provided. Combining a MapReduce framework (TomusBLOB) with machine learning algorithms (Scikit-learn library), we design a scalable analysis tool that can deal with non-parametric statistics on high-dimensional data. End-users describe the statistical procedure to perform and can then test the model on their own computers before running the very same code in the cloud at a larger scale. We illustrate the potential of our approach on real data with an experiment showing how the functional signal in subcortical brain regions can be significantly fit with genome-wide genotypes. This experiment demonstrates the scalability and the reliability of our framework in the cloud with a 2 weeks deployment on hundreds of virtual machines.
Frontiers in Neuroinformatics 04/2014; 8:31. DOI:10.3389/fninf.2014.00031 · 3.26 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.
[Show abstract][Hide abstract] ABSTRACT: This article reviews work published by the ENIGMA Consortium and its Working Groups (http://enigma.ini.usc.edu). It was written collaboratively; P.T. wrote the first draft and all listed authors revised and edited the document for important intellectual content, using Google Docs for parallel editing, and approved it. Some ENIGMA investigators contributed to the design and implementation of ENIGMA or provided data but did not participate in the analysis or writing of this report. A complete listing of ENIGMA investigators is available at http://enigma.ini.usc.edu/publications/the-enigma-consortium-in-review/ For ADNI, some investigators contributed to the design and implementation of ADNI or provided data but did not participate in the analysis or writing of this report. A complete listing of ADNI investigators is available at http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ ADNI_Acknowledgement_List.pdf The work reviewed here was funded by a large number of federal and private agencies worldwide, listed in Stein et al. (2012); the funding for listed consortia is also itemized in Stein et al. (2012).
[Show abstract][Hide abstract] ABSTRACT: Alleles of the apolipoprotein E (ApoE) gene are known to modulate the genetic risk for developing late-onset Alzheimer's disease (AD) and have been associated with hippocampal volume differences in AD. However, the effect of these alleles on hippocampal volume in younger subjects has yet to be clearly established. Using a large cohort of more than 1,400 adolescents, this study found no hippocampal volume or hippocampal asymmetry differences between carriers and non-carriers of the ApoE ε4 or ε2 alleles, nor dose-dependent effects of either allele, suggesting that regionally specific effects of these alleles may only become apparent in later life.
[Show abstract][Hide abstract] ABSTRACT: Episodic memory (EM) declines with age and the rate of decline is variable across individuals. A single nucleotide polymorphism (rs17070145) in the WWC1 gene that encodes the KIBRA protein critical for long-term potentiation and memory consolidation has previously been associated with EM performance, as well as differences in hippocampal engagement during EM tasks using functional magnetic resonance imaging (fMRI). In the current study, we explore the effect of this polymorphism on EM-related activity and cognitive performance across the adult life span using fMRI.
Two hundred thirty-two healthy, Caucasian subjects (18-89 years) completed a battery of cognitive tests, as well as an EM task during an fMRI scan.
WWC1 T carriers had significantly better delayed recall performance than CC individuals (p = .006). The relationship between increasing age and recall scores (immediate and delayed) was also significantly different between WWC1 genotype groups (p = .01). In addition to the age-related decline in hippocampal formation (HF) activation (p < .05; false discovery ratesmall volume correction-HF-region of interest), we observed an age by WWC1 genotype interaction on HF activation during encoding and retrieval. The CC group showed a significant negative association between HF activity and increasing age, while no such association was observed in the T carrier group (left HF p = .04; r-z correlation difference during encoding and retrieval; right HF p = .0008; r-z correlation difference during retrieval).
Our results show a dynamic relationship between rs17070145 polymorphism and increasing age on neuronal activity in the hippocampal region.