Jason L. Stein

YNIMG Journal 2023 Journal Article

Genetic variations within human gained enhancer elements affect human brain sulcal morphology

• Herve Lemaitre
• Yann Le Guen
• Amanda K. Tilot
• Jason L. Stein
• Cathy Philippe
• Jean-François Mangin
• Simon E. Fisher
• Vincent Frouin

The expansion of the cerebral cortex is one of the most distinctive changes in the evolution of the human brain. Cortical expansion and related increases in cortical folding may have contributed to emergence of our capacities for high-order cognitive abilities. Molecular analysis of humans, archaic hominins, and non-human primates has allowed identification of chromosomal regions showing evolutionary changes at different points of our phylogenetic history. In this study, we assessed the contributions of genomic annotations spanning 30 million years to human sulcal morphology measured via MRI in more than 18,000 participants from the UK Biobank. We found that variation within brain-expressed human gained enhancers, regulatory genetic elements that emerged since our last common ancestor with Old World monkeys, explained more trait heritability than expected for the left and right calloso-marginal posterior fissures and the right central sulcus. Intriguingly, these are sulci that have been previously linked to the evolution of locomotion in primates and later on bipedalism in our hominin ancestors.

YNIMG Journal 2017 Journal Article

ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide

• Paul M. Thompson
• Ole A. Andreassen
• Alejandro Arias-Vasquez
• Carrie E. Bearden
• Premika S. Boedhoe
• Rachel M. Brouwer
• Randy L. Buckner
• Jan K. Buitelaar

In this review, we discuss recent work by the ENIGMA Consortium (http: //enigma. ini. usc. edu) – a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date – of schizophrenia and major depression – ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others 1 1 Abbreviations: ADNI, Alzheimer's Disease Neuroimaging Initiative (http: //www. adni-info. org); CHARGE, the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (http: //www. chargeconsortium. com); IMAGEN, IMAging GENetics Consortium (http: //www. imagen-europe. com). , ENIGMA's genomic screens – now numbering over 30, 000 MRI scans – have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants – and genetic variants in general – may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures – from tens of thousands of people – that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

YNICL Journal 2012 Journal Article

Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment

• Priya Rajagopalan
• Neda Jahanshad
• Jason L. Stein
• Xue Hua
• Sarah K. Madsen
• Omid Kohannim
• Derrek P. Hibar
• Arthur W. Toga

A commonly carried C677T polymorphism in a folate-related gene, MTHFR, is associated with higher plasma homocysteine, a well-known mediator of neuronal damage and brain atrophy. As homocysteine promotes brain atrophy, we set out to discover whether people carrying the C677T MTHFR polymorphism which increases homocysteine, might also show systematic differences in brain structure. Using tensor-based morphometry, we tested this association in 359 elderly Caucasian subjects with mild cognitive impairment (MCI) (mean age: 75 ± 7.1 years) scanned with brain MRI and genotyped as part of Alzheimer's Disease Neuroimaging Initiative. We carried out a replication study in an independent, non-overlapping sample of 51 elderly Caucasian subjects with MCI (mean age: 76 ± 5.5 years), scanned with brain MRI and genotyped for MTHFR, as part of the Cardiovascular Health Study. At each voxel in the brain, we tested to see where regional volume differences were associated with carrying one or more MTHFR 'T' alleles. In ADNI subjects, carriers of the MTHFR risk allele had detectable brain volume deficits, in the white matter, of up to 2-8% per risk T allele locally at baseline and showed accelerated brain atrophy of 0.5-1.5% per T allele at 1 year follow-up, after adjusting for age and sex. We replicated these brain volume deficits of up to 5-12% per MTHFR T allele in the independent cohort of CHS subjects. As expected, the associations weakened after controlling for homocysteine levels, which the risk gene affects. The MTHFR risk variant may thus promote brain atrophy by elevating homocysteine levels. This study aims to investigate the spatially detailed effects of this MTHFR polymorphism on brain structure in 3D, pointing to a causal pathway that may promote homocysteine-mediated brain atrophy in elderly people with MCI.

YNIMG Journal 2012 Journal Article

Sparse reduced-rank regression detects genetic associations with voxel-wise longitudinal phenotypes in Alzheimer's disease

• Maria Vounou
• Eva Janousova
• Robin Wolz
• Jason L. Stein
• Paul M. Thompson
• Daniel Rueckert
• Giovanni Montana

Scanning the entire genome in search of variants related to imaging phenotypes holds great promise in elucidating the genetic etiology of neurodegenerative disorders. Here we discuss the application of a penalized multivariate model, sparse reduced-rank regression (sRRR), for the genome-wide detection of markers associated with voxel-wise longitudinal changes in the brain caused by Alzheimer's disease (AD). Using a sample from the Alzheimer's Disease Neuroimaging Initiative database, we performed three separate studies that each compared two groups of individuals to identify genes associated with disease development and progression. For each comparison we took a two-step approach: initially, using penalized linear discriminant analysis, we identified voxels that provide an imaging signature of the disease with high classification accuracy; then we used this multivariate biomarker as a phenotype in a genome-wide association study, carried out using sRRR. The genetic markers were ranked in order of importance of association to the phenotypes using a data re-sampling approach. Our findings confirmed the key role of the APOE and TOMM40 genes but also highlighted some novel potential associations with AD.

YNIMG Journal 2012 Journal Article

Structural and functional neuroimaging phenotypes in dysbindin mutant mice

• Evan Lutkenhoff
• Katherine H. Karlsgodt
• Boris Gutman
• Jason L. Stein
• Paul M. Thompson
• Tyrone D. Cannon
• J. David Jentsch

Schizophrenia is a highly heritable psychiatric disorder that is associated with a number of structural and functional neurophenotypes. DTNBP1, the gene encoding dysbindin-1, is a promising candidate gene for schizophrenia. Use of a mouse model carrying a large genomic deletion exclusively within the dysbindin gene permits a direct investigation of the gene in isolation. Here, we use manganese-enhanced magnetic resonance imaging (MEMRI) to explore the regional alterations in brain structure and function caused by loss of the gene encoding dysbindin-1. We report novel findings that uniquely inform our understanding of the relationship of dysbindin-1 to known schizophrenia phenotypes. First, in mutant mice, analysis of the rate of manganese uptake into the brain over a 24-hour period, putatively indexing basal cellular activity, revealed differences in dopamine rich brain regions, as well as in CA1 and dentate subregions of the hippocampus formation. Finally, novel tensor-based morphometry techniques were applied to the mouse MRI data, providing evidence for structural volume deficits in cortical regions, subiculum and dentate gyrus, and the striatum of dysbindin mutant mice. The affected cortical regions were primarily localized to the sensory cortices in particular the auditory cortex. This work represents the first application of manganese-enhanced small animal imaging to a mouse model of schizophrenia endophenotypes, and a novel combination of functional and structural measures. It revealed both hypothesized and novel structural and functional neural alterations related to dysbindin-1.

YNIMG Journal 2011 Journal Article

Voxelwise gene-wide association study (vGeneWAS): Multivariate gene-based association testing in 731 elderly subjects

• Derrek P. Hibar
• Jason L. Stein
• Omid Kohannim
• Neda Jahanshad
• Andrew J. Saykin
• Li Shen
• Sungeun Kim
• Nathan Pankratz

Imaging traits provide a powerful and biologically relevant substrate to examine the influence of genetics on the brain. Interest in genome-wide, brain-wide search for influential genetic variants is growing, but has mainly focused on univariate, SNP-based association tests. Moving to gene-based multivariate statistics, we can test the combined effect of multiple genetic variants in a single test statistic. Multivariate models can reduce the number of statistical tests in gene-wide or genome-wide scans and may discover gene effects undetectable with SNP-based methods. Here we present a gene-based method for associating the joint effect of single nucleotide polymorphisms (SNPs) in 18, 044 genes across 31, 662 voxels of the whole brain in 731 elderly subjects (mean age: 75. 56±6. 82SD years; 430 males) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. Using the voxel-level volume difference values as the phenotype, we selected the most significantly associated gene (out of 18, 044) at each voxel across the brain. No genes identified were significant after correction for multiple comparisons, but several known candidates were re-identified, as were other genes highly relevant to brain function. GAB2, which has been previously associated with late-onset AD, was identified as the top gene in this study, suggesting the validity of the approach. This multivariate, gene-based voxelwise association study offers a novel framework to detect genetic influences on the brain.

YNIMG Journal 2010 Journal Article

Genome-wide analysis reveals novel genes influencing temporal lobe structure with relevance to neurodegeneration in Alzheimer's disease

• Jason L. Stein
• Xue Hua
• Jonathan H. Morra
• Suh Lee
• Derrek P. Hibar
• April J. Ho
• Alex D. Leow
• Arthur W. Toga

In a genome-wide association study of structural brain degeneration, we mapped the 3D profile of temporal lobe volume differences in 742 brain MRI scans of Alzheimer's disease patients, mildly impaired, and healthy elderly subjects. After searching 546, 314 genomic markers, 2 single nucleotide polymorphisms (SNPs) were associated with bilateral temporal lobe volume (P <5×10−7). One SNP, rs10845840, is located in the GRIN2B gene which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit. This protein – involved in learning and memory, and excitotoxic cell death – has age-dependent prevalence in the synapse and is already a therapeutic target in Alzheimer's disease. Risk alleles for lower temporal lobe volume at this SNP were significantly over-represented in AD and MCI subjects vs. controls (odds ratio=1. 273; P =0. 039) and were associated with mini-mental state exam scores (MMSE; t =−2. 114; P =0. 035) demonstrating a negative effect on global cognitive function. Voxelwise maps of genetic association of this SNP with regional brain volumes, revealed intense temporal lobe effects (FDR correction at q =0. 05; critical P =0. 0257). This study uses large-scale brain mapping for gene discovery with implications for Alzheimer's disease.

YNIMG Journal 2010 Journal Article

Voxelwise genome-wide association study (vGWAS)

• Jason L. Stein
• Xue Hua
• Suh Lee
• April J. Ho
• Alex D. Leow
• Arthur W. Toga
• Andrew J. Saykin
• Li Shen

The structure of the human brain is highly heritable, and is thought to be influenced by many common genetic variants, many of which are currently unknown. Recent advances in neuroimaging and genetics have allowed collection of both highly detailed structural brain scans and genome-wide genotype information. This wealth of information presents a new opportunity to find the genes influencing brain structure. Here we explore the relation between 448, 293 single nucleotide polymorphisms in each of 31, 622 voxels of the entire brain across 740 elderly subjects (mean age±s. d. : 75. 52±6. 82 years; 438 male) including subjects with Alzheimer's disease, Mild Cognitive Impairment, and healthy elderly controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We used tensor-based morphometry to measure individual differences in brain structure at the voxel level relative to a study-specific template based on healthy elderly subjects. We then conducted a genome-wide association at each voxel to identify genetic variants of interest. By studying only the most associated variant at each voxel, we developed a novel method to address the multiple comparisons problem and computational burden associated with the unprecedented amount of data. No variant survived the strict significance criterion, but several genes worthy of further exploration were identified, including CSMD2 and CADPS2. These genes have high relevance to brain structure. This is the first voxelwise genome wide association study to our knowledge, and offers a novel method to discover genetic influences on brain structure.

YNIMG Journal 2009 Journal Article

Active fibers: Matching deformable tract templates to diffusion tensor images

• Ilya Eckstein
• David W. Shattuck
• Jason L. Stein
• Katie L. McMahon
• Greig de Zubicaray
• Margaret J. Wright
• Paul M. Thompson
• Arthur W. Toga

Reliable quantitative analysis of white matter connectivity in the brain is an open problem in neuroimaging, with common solutions requiring tools for fiber tracking, tractography segmentation and estimation of intersubject correspondence. This paper proposes a novel, template matching approach to the problem. In the proposed method, a deformable fiber-bundle model is aligned directly with the subject tensor field, skipping the fiber tracking step. Furthermore, the use of a common template eliminates the need for tractography segmentation and defines intersubject shape correspondence. The method is validated using phantom DTI data and applications are presented, including automatic fiber-bundle reconstruction and tract-based morphometry.

YNIMG Journal 2008 Journal Article

Corrigendum to “A validated network of effective amygdala connectivity” [NeuroImage 36 (2007) 736–745]

• Jason L. Stein
• Lisa M. Wiedholz
• Danielle S. Bassett
• Daniel R. Weinberger
• Caroline F. Zink
• Venkata S. Mattay
• Andreas Meyer-Lindenberg

YNIMG Journal 2007 Journal Article

A validated network of effective amygdala connectivity

• Jason L. Stein
• Lisa M. Wiedholz
• Danielle S. Bassett
• Daniel R. Weinberger
• Caroline F. Zink
• Venkata S. Mattay
• Andreas Meyer-Lindenberg

Regulatory interactions with the amygdala are thought to be critical for emotional processing in the extended limbic system. Structural equation modeling (path analysis) is a widely used method to quantify interactions among brain regions based on connectivity models, but is often limited by lack of precise anatomical and functional constraints. To address this issue, we developed an automated elaborative path analysis procedure guided by known anatomical connectivity in the macaque. We applied this technique to a large human fMRI data set acquired during perceptual processing of angry or fearful facial stimuli. The derived models were inferentially validated using a bootstrapping split-half approach in pairs of 500 independent groups. Significant paths across the groups were used to form a rigorously validated and consistent path model. We confirm and extend previous observations of amygdala regulation by an extended prefrontal network encompassing cingulate, orbitofrontal, insular, and dorsolateral prefrontal cortex, as well as strong interactions between amygdala and parahippocampal gyrus. This validated model can be used to study neurocognitive correlates as well as genotype or disease-related alterations of functional interactions in the limbic system.