[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: 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).
Brain Imaging and Behavior 01/2014; · 3.39 Impact Factor
[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.
[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.
Journal of Alzheimer's disease: JAD 12/2013; · 3.61 Impact Factor
[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.
[Show abstract][Hide abstract] ABSTRACT: Abnormalities in white-matter (WM) microstructure, as lower fractional anisotropy (FA), have been reported in adolescent-onset bipolar disorder and in youth at familial risk for bipolarity. We sought to determine whether healthy adolescents with subthreshold bipolar symptoms (SBP) would have early WM microstructural alterations and whether those alterations would be associated with differences in gray-matter (GM) volumes. Forty-two adolescents with three core manic symptoms and no psychiatric diagnosis, and 126 adolescents matched by age and sex, with no psychiatric diagnosis or symptoms, were identified after screening the IMAGEN database of 2223 young adolescents recruited from the general population. After image quality control, voxel-wise statistics were performed on the diffusion parameters using tract-based spatial statistics in 25 SBP adolescents and 77 controls, and on GM and WM images using voxel-based morphometry in 30 SBP adolescents and 106 controls. As compared with healthy controls, adolescents with SBP displayed lower FA values in a number of WM tracts, particularly in the corpus callosum, cingulum, bilateral superior and inferior longitudinal fasciculi, uncinate fasciculi and corticospinal tracts. Radial diffusivity was mainly higher in posterior parts of bilateral superior and inferior longitudinal fasciculi, inferior fronto-occipital fasciculi and right cingulum. As compared with controls, SBP adolescents had lower GM volume in the left anterior cingulate region. This is the first study to investigate WM microstructure and GM morphometric variations in adolescents with SBP. The widespread FA alterations in association and projection tracts, associated with GM changes in regions involved in mood disorders, suggest altered structural connectivity in those adolescents.Molecular Psychiatry advance online publication, 30 April 2013; doi:10.1038/mp.2013.44.
[Show abstract][Hide abstract] ABSTRACT: The BDNF Val(66)Met polymorphism, a possible risk variant for mental disorders, is a potent modulator of neural plasticity in humans and has been linked to deficits in gray matter structure, function, and cognition. The impact of the variant on brain white matter structure, however, is controversial and remains poorly understood. Here, we used diffusion tensor imaging to examine the effects of BDNF Val(66)Met genotype on white matter microstructure in a sample of 85 healthy Caucasian adults. We demonstrate decreases of fractional anisotropy and widespread increases in radial diffusivity in Val/Val homozygotes compared with Met-allele carriers, particularly in prefrontal and occipital pathways. These data provide an independent confirmation of prior imaging genetics work, are consistent with complex effects of the BDNF Val(66)Met polymorphism on human brain structure, and may serve to generate hypotheses about variation in white matter microstructure in mental disorders associated with this variant.Neuropsychopharmacology advance online publication, 7 November 2012; doi:10.1038/npp.2012.214.
Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology 11/2012; · 8.68 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: A functional decline of brain regions underlying memory processing represents a hallmark of cognitive aging. Although a rich literature documents age-related differences in several memory domains, the effect of aging on networks that underlie multiple memory processes has been relatively unexplored. Here we used functional magnetic resonance imaging during working memory and incidental episodic encoding memory to investigate patterns of age-related differences in activity and functional covariance patterns common across multiple memory domains. Relative to younger subjects, older subjects showed increased activation in left dorso-lateral prefrontal cortex along with decreased deactivation in the posterior cingulate. Older subjects showed greater functional covariance during both memory tasks in a set of regions that included a positive prefronto-parietal-occipital network as well as a negative network that spanned the default mode regions. These findings suggest that the memory process-invariant recruitment of brain regions within prefronto-parietal-occipital network increases with aging. Our results are in line with the dedifferentiation hypothesis of neurocognitive aging, thereby suggesting a decreased specialization of the brain networks supporting different memory networks.
European Journal of Neuroscience 08/2012; · 3.67 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Normal aging is accompanied by global as well as regional structural changes. While these age-related changes in gray matter volume have been extensively studied, less has been done using newer morphological indexes, such as cortical thickness and surface area. To this end, we analyzed structural images of 216 healthy volunteers, ranging from 18 to 87 years of age, using a surface-based automated parcellation approach. Linear regressions of age revealed a concomitant global age-related reduction in cortical thickness, surface area and volume. Cortical thickness and volume collectively confirmed the vulnerability of the prefrontal cortex, whereas in other cortical regions, such as in the parietal cortex, thickness was the only measure sensitive to the pronounced age-related atrophy. No cortical regions showed more surface area reduction than the global average. The distinction between these morphological measures may provide valuable information to dissect age-related structural changes of the brain, with each of these indexes probably reflecting specific histological changes occurring during aging.
Neurobiology of aging 03/2012; 33(3):617.e1-9. · 5.94 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Neuroimaging studies of patients with treatment-resistant depression (TRD) have reported abnormalities in the frontal and temporal regions. We sought to determine whether metabolism in these regions might be related to response to repetitive transcranial magnetic stimulation (TMS) in patients with TRD. Magnetic resonance images and baseline resting-state cerebral glucose uptake index (gluMI) obtained using (18)F-fluorodeoxyglucose positron emission tomography were analyzed in TRD patients who had participated in a double-blind, randomized, sham-controlled trial of prefrontal 10 Hz TMS. Among the patients randomized to active TMS, 17 responders, defined as having 50% depression score decrease, and 14 nonresponders were investigated for prestimulation glucose metabolism and compared with 39 healthy subjects using a voxel-based analysis. In nonresponders relative to responders, gluMI was lower in left lateral orbitofrontal cortex (OFC), and higher in left amygdala and uncinate fasciculus. OFC and amygdala gluMI negatively correlated in nonresponders, positively correlated in responders, and did not correlate in healthy subjects. Relative to healthy subjects, both responders and nonresponders displayed lower gluMI in right dorsolateral prefrontal (DLPFC), right anterior cingulate (ACC), and left ventrolateral prefrontal cortices. Additionally, nonresponders had lower gluMI in left DLPFC, ACC, left and right insula, and higher gluMI in left amygdala and uncus. Hypometabolisms were partly explained by gray matter reductions, whereas hypermetabolisms were unrelated to structural changes. The findings suggest that different patterns of frontal-temporal-limbic abnormalities may distinguish responders and nonresponders to prefrontal magnetic stimulation. Both preserved OFC volume and amygdala metabolism might precondition response to TMS.
Neuropsychopharmacology: official publication of the American College of Neuropsychopharmacology 08/2011; 36(13):2710-9. · 8.68 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: In a sample of 1186 healthy subjects aged 65 to 89 years who were scanned twice with MRI 3.6 years apart, we studied the effects of age and ApoE-epsilon4 allele load on the rate of atrophy of grey matter and hippocampus. Rates of grey matter and hippocampal volumes loss were computed from T1-weighted magnetic resonance images using voxel-based morphometry and region of interest analysis. Longitudinal analysis showed that an age-related annual rate of grey matter volume loss was only seen in epsilon4 homozygotes only (n=14) whereas no age effect was seen epsilon4 heterozygotes (n=239) and in noncarriers (n=933). ApoE-epsilon4 homozygotes also had a significantly larger rate of hippocampal volume loss than heterozygotes or noncarriers. During the same period, no effect or interaction of ApoE genotype and age was observed on cognitive decline, as assessed by the Mini Mental State Examination (MMSE). These data do not suggest an epsilon4 gene dose effect on the rate of hippocampal volume loss in healthy elderly subjects as most of the effect was limited to homozygotes. Hippocampal volume loss may not be a good imaging marker to understand the effect of the ApoE-epsilon4 allele on the risk of dementia in a population-based setting. It could be hypothesized that the impact of a single ApoE-epsilon4 allele on brain structures is largely delayed in time.
[Show abstract][Hide abstract] ABSTRACT: Previous neuromorphometric investigations of major depressive disorder (MDD) have reported abnormalities in gray matter in several regions, although the results have been inconsistent across studies. Some discrepancies in the results across studies may reflect design limitations such as small sample sizes, whereas others may reflect biological variability that potentially manifests as differences in clinical course. For example, it remains unclear whether the abnormalities found in persistently depressed MDD subjects extend to or persist in patients who experience prolonged remission. The aim of the present study was to investigate gray matter (GM) differences in unmedicated, currently-depressed participants (dMDD) and unmedicated, currently-remitted (rMDD) participants with MDD compared to healthy controls (HC). The GM density and volume were compared across groups using voxel-based morphometry, a quantitative neuroanatomical technique, and high-resolution MRI images from 107 HC, 58 dMDD and 27 rMDD subjects. Relative to the HC group the dMDD group had reduced GM in the dorsal anterolateral (DALPFC), the dorsomedial (DMPFC) and the ventrolateral prefrontal cortex (VLPFC). Relative to the rMDD group the dMDD group showed reduced GM in the DALPFC, the VLPFC, the anterior cingulate cortex (ACC), the precuneus and the inferior parietal lobule. No regions were identified in which the rMDD group showed significantly lower GM compared to the HC group after p-values were corrected for the number of comparisons performed. In unmedicated patients in the depressed phase of MDD, we found evidence of morphometric abnormalities in DALPFC and in medial prefrontal cortical regions belonging to the visceromotor network. These findings, along with the absence of GM abnormalities in the remitted sample imply a possible link between greater GM tissue and better clinical outcome. Consistent with other neuroimaging and post-mortem neuropathological studies of MDD, we also found evidence of decreased white matter in patients with dMDD and rMDD.