Genome-wide association identifies genetic variants associated with lentiform nucleus volume in N = 1345 young and elderly subjects

Statistical shape analysis of the lentiform nucleus of children of different age groups: a retrospective study

The basal nuclei are important during infancy because of the significant development of motor skills. The main aim of this study was to evaluate the shape differences of the lentiform nucleus between different age and gender groups. A total of 126 children's axial magnetic resonance image series were included in the presented study. These images were grouped between 1 and 5 yr old. Right and left lentiform nuclei are marked with selected landmarks using TPSDIG v2.04. Statistical shape analyses were examined by a Generalized Procrustes Analysis. Our results showed that there was no statistically significant difference in lentiform nucleus shape between genders. However, there was a difference between the shapes of the right and left lentiform nuclei between the 1-yr and 5-yr age groups. These results demonstrated the shape changes in the lentiform nucleus during the first 5 yr of life. Further clinical studies based on our results may be used to gather more detailed information about movement disorders and neuronal development.

The Association Between Lentiform Nucleus Function and Cognitive Impairments in Schizophrenia

Introduction: Cognitive decline is the core schizophrenia symptom, which is now well accepted. Holding a role in various aspects of cognition, lentiform nucleus (putamen and globus pallidus) dysfunction contributes to the psychopathology of this disease. However, the effects of lentiform nucleus function on cognitive impairments in schizophrenia are yet to be investigated.

Objectives: We aim to detect the fractional amplitude of low-frequency fluctuation (fALFF) alterations in patients with schizophrenia, and examine how their behavior correlates in relation to the cognitive impairments of the patients.

Methods: All participants underwent magnetic resonance imaging (MRI) and cognitive assessment (digit span and digit symbol coding tests). Screening of brain regions with significant changes in fALFF values was based on analysis of the whole brain. The data were analyzed between Jun 2020 and Mar 2021. There were no interventions beyond the routine therapy determined by their clinicians on the basis of standard clinical practice.

Results: There were 136 patients (75 men and 61 women, 24.1 ± 7.4 years old) and 146 healthy controls (82 men and 64 women, 24.2 ± 5.2 years old) involved in the experiments seriatim. Patients with schizophrenia exhibited decreased raw scores in cognitive tests (p < 0.001) and increased fALFF in the bilateral lentiform nuclei (left: 67 voxels; x = −24, y = −6, z = 3; peak t-value = 6.90; right: 16 voxels; x = 18, y = 0, z = 3; peak t-value = 6.36). The fALFF values in the bilateral lentiform nuclei were positively correlated with digit span-backward test scores (left: r = 0.193, p = 0.027; right: r = 0.190, p = 0.030), and the right lentiform nucleus was positively correlated with digit symbol coding scores (r = 0.209, p = 0.016).

Conclusion: This study demonstrates that cognitive impairments in schizophrenia are associated with lentiform nucleus function as revealed by MRI, involving working memory and processing speed.

Flavin-containing monooxygenase 1 deficiency promotes neuroinflammation in dopaminergic neurons in mice

A growing body of evidence indicates an association between flavin-containing monooxygenase (FMO) and neurodegeneration, including Parkinson's disease (PD); however, the details of this association are unclear. We previously showed that the level of Fmo1 mRNA is decreased in an in vitro rotenone model of parkinsonism. To further explore the potential involvement of FMO1 deficiency in parkinsonism, we generated Fmo1 knockout (KO) mice and examined the survival of dopaminergic neurons and relative changes. Fmo1 KO mice exhibited loss of tyrosine hydroxylase-positive neurons, decreased levels of tyrosine hydroxylase and Parkin proteins, and increased levels of pro-inflammatory cytokines (IL1β and IL6) in the nigrostriatal region. Moreover, the protein levels of PTEN induced kinase 1 (PINK1) and p62, and the Microtubule associated protein 1 light chain 3 (LC3)-II/I ratio were not significantly altered in Fmo1 KO mice (P > 0.05). FMO1 deficiency promotes neuroinflammation in dopaminergic neurons in mice, thus may plays a potential pathological role in dopaminergic neuronal loss. These findings may provide new insight into the pathogenesis of PD.

Meta-analysis of SNP-environment interaction with heterogeneity for overlapping data

Meta-analysis is a popular method used in genome-wide association studies, by which the results of multiple studies are combined to identify associations. This process generates heterogeneity. Recently, we proposed a random effect model meta-regression method (MR) to study the effect of single nucleotide polymorphism (SNP)-environment interactions. This method takes heterogeneity into account and produces high power. We also proposed a fixed effect model overlapping MR in which the overlapping data is taken into account. In the present study, a random effect model overlapping MR that simultaneously considers heterogeneity and overlapping data is proposed. This method is based on the random effect model MR and the fixed effect model overlapping MR. A new way of solving the logarithm of the determinant of covariance matrices in likelihood functions is also provided. Tests for the likelihood ratio statistic of the SNP-environment interaction effect and the SNP and SNP-environment joint effects are given. In our simulations, null distributions and type I error rates were proposed to verify the suitability of our method, and powers were applied to evaluate the superiority of our method. Our findings indicate that this method is effective in cases of overlapping data with a high heterogeneity.

Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive and mental health traits

Volumetric variations of the human brain are heritable and are associated with many brain-related complex traits. Here we performed genome-wide association studies (GWAS) of 101 brain volumetric phenotypes using the UK Biobank sample including 19,629 participants. GWAS identified 365 independent genetic variants exceeding a significance threshold of 4.9 × 10-10, adjusted for testing multiple phenotypes. A gene-based association study found 157 associated genes (124 new), and functional gene mapping analysis linked 146 additional genes. Many of the discovered genetic variants and genes have previously been implicated in cognitive and mental health traits. Through genome-wide polygenic-risk-score prediction, more than 6% of the phenotypic variance (P = 3.13 × 10-24) in four other independent studies could be explained by the UK Biobank GWAS results. In conclusion, our study identifies many new genetic associations at the variant, locus and gene levels and advances our understanding of the pleiotropy and genetic co-architecture between brain volumes and other traits.

Strategies for integrated analysis in imaging genetics studies

Imaging Genetics (IG) integrates neuroimaging and genomic data from the same individual, deepening our knowledge of the biological mechanisms behind neurodevelopmental domains and neurological disorders. Although the literature on IG has exponentially grown over the past years, the majority of studies have mainly analyzed associations between candidate brain regions and individual genetic variants. However, this strategy is not designed to deal with the complexity of neurobiological mechanisms underlying behavioral and neurodevelopmental domains. Moreover, larger sample sizes and increased multidimensionality of this type of data represents a challenge for standardizing modeling procedures in IG research. This review provides a systematic update of the methods and strategies currently used in IG studies, and serves as an analytical framework for researchers working in this field. To complement the functionalities of the Neuroconductor framework, we also describe existing R packages that implement these methodologies. In addition, we present an overview of how these methodological approaches are applied in integrating neuroimaging and genetic data.

Increasing the power of meta-analysis of genome-wide association studies to detect heterogeneous effects

Motivation

Meta-analysis is essential to combine the results of genome-wide association studies (GWASs). Recent large-scale meta-analyses have combined studies of different ethnicities, environments and even studies of different related phenotypes. These differences between studies can manifest as effect size heterogeneity. We previously developed a modified random effects model (RE2) that can achieve higher power to detect heterogeneous effects than the commonly used fixed effects model (FE). However, RE2 cannot perform meta-analysis of correlated statistics, which are found in recent research designs, and the identified variants often overlap with those found by FE.

Results

Here, we propose RE2C, which increases the power of RE2 in two ways. First, we generalized the likelihood model to account for correlations of statistics to achieve optimal power, using an optimization technique based on spectral decomposition for efficient parameter estimation. Second, we designed a novel statistic to focus on the heterogeneous effects that FE cannot detect, thereby, increasing the power to identify new associations. We developed an efficient and accurate p-value approximation procedure using analytical decomposition of the statistic. In simulations, RE2C achieved a dramatic increase in power compared with the decoupling approach (71% vs. 21%) when the statistics were correlated. Even when the statistics are uncorrelated, RE2C achieves a modest increase in power. Applications to real genetic data supported the utility of RE2C. RE2C is highly efficient and can meta-analyze one hundred GWASs in one day.

Availability and implementation

The software is freely available at http://software.buhmhan.com/RE2C.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome-wide association study of paliperidone efficacy

Supplemental Digital Content is available in the text.

Objective

Clinical response to the atypical antipsychotic paliperidone is known to vary among schizophrenic patients. We carried out a genome-wide association study to identify common genetic variants predictive of paliperidone efficacy.

Methods

We leveraged a collection of 1390 samples from individuals of European ancestry enrolled in 12 clinical studies investigating the efficacy of the extended-release tablet paliperidone ER (n₁=490) and the once-monthly injection paliperidone palmitate (n₂=550 and n₃=350). We carried out a genome-wide association study using a general linear model (GLM) analysis on three separate cohorts, followed by meta-analysis and using a mixed linear model analysis on all samples. The variations in response explained by each single nucleotide polymorphism (h²_SNP) were estimated.

Results

No SNP passed genome-wide significance in the GLM-based analyses with suggestive signals from rs56240334 [P=7.97×10⁻⁸ for change in the Clinical Global Impression Scale-Severity (CGI-S); P=8.72×10⁻⁷ for change in the total Positive and Negative Syndrome Scale (PANSS)] in the intron of ADCK1. The mixed linear model-based association P-values for rs56240334 were consistent with the results from GLM-based analyses and the association with change in CGI-S (P=4.26×10⁻⁸) reached genome-wide significance (i.e. P<5×10⁻⁸). We also found suggestive evidence for a polygenic contribution toward paliperidone treatment response with estimates of heritability, h²_SNP, ranging from 0.31 to 0.43 for change in the total PANSS score, the PANSS positive Marder factor score, and CGI-S.

Conclusion

Genetic variations in the ADCK1 gene may differentially predict paliperidone efficacy in schizophrenic patients. However, this finding should be replicated in additional samples.

Flavin-containing monooxygenases in aging and disease: Emerging roles for ancient enzymes

Flavin-containing monooxygenases (FMOs) are primarily studied as xenobiotic metabolizing enzymes with a prominent role in drug metabolism. In contrast, endogenous functions and substrates of FMOs are less well understood. A growing body of recent evidence, however, implicates FMOs in aging, several diseases, and metabolic pathways. The evidence suggests an important role for these well-conserved proteins in multiple processes and raises questions about the endogenous substrate(s) and regulation of FMOs. Here, we present an overview of evidence for FMOs' involvement in aging and disease, discussing the biological context and arguing for increased investigation into the function of these enzymes.

Genome-Wide Association Study Meta-Analysis of Long-Term Average Blood Pressure in East Asians

BACKGROUND

Genome-wide single marker and gene-based meta-analyses of long-term average (LTA) blood pressure (BP) phenotypes may reveal novel findings for BP.

METHODS AND RESULTS

We conducted genome-wide analysis among 18 422 East Asian participants (stage 1) followed by replication study of ≤46 629 participants of European ancestry (stage 2). Significant single-nucleotide polymorphisms and genes were determined by a P<5.0×10-8 and 2.5×10-6, respectively, in joint analyses of stage-1 and stage-2 data. We identified 1 novel ARL3 variant, rs4919669 at 10q24.32, influencing LTA systolic BP (stage-1 P=5.03×10-8, stage-2 P=8.64×10-3, joint P=2.63×10-8) and mean arterial pressure (stage-1 P=3.59×10-9, stage-2 P=2.35×10-2, joint P=2.64×10-8). Three previously reported BP loci (WBP1L, NT5C2, and ATP2B1) were also identified for all BP phenotypes. Gene-based analysis provided the first robust evidence for association of KCNJ11 with LTA systolic BP (stage-1 P=8.55×10-6, stage-2 P=1.62×10-5, joint P=3.28×10-9) and mean arterial pressure (stage-1 P=9.19×10-7, stage-2 P=9.69×10-5, joint P=2.15×10-9) phenotypes. Fourteen genes (TMEM180, ACTR1A, SUFU, ARL3, SFXN2, WBP1L, CYP17A1, C10orf32, C10orf32-ASMT, AS3MT, CNNM2, and NT5C2 at 10q24.32; ATP2B1 at 12q21.33; and NCR3LG1 at 11p15.1) implicated by previous genome-wide association study meta-analyses were also identified. Among the loci identified by the previous genome-wide association study meta-analysis of LTA BP, we transethnically replicated associations of the KCNK3 marker rs1275988 at 2p23.3 with LTA systolic BP and mean arterial pressure phenotypes (P=1.27×10-4 and 3.30×10-4, respectively).

CONCLUSIONS

We identified 1 novel variant and 1 novel gene and present the first direct evidence of relevance of the KCNK3 locus for LTA BP among East Asians.

Toward an integrative science of the developing human mind and brain: Focus on the developing cortex

Based on the Huttenlocher lecture, this article describes the need for a more integrative scientific paradigm for addressing important questions raised by key observations made over 2 decades ago. Among these are the early descriptions by Huttenlocher of variability in synaptic density in cortex of postmortem brains of children of different ages and the almost simultaneous reports of cortical volume reductions on MR imaging in children and adolescents. In spite of much progress in developmental neurobiology, developmental cognitive neuroscience, and behavioral and imaging genetics, we still do not know how these early observations relate to each other. It is argued that large scale, collaborative research programs are needed to establish the associations between behavioral differences among children and imaging biomarkers, and to link the latter to cellular changes in the developing brain. Examples of progress and challenges remaining are illustrated with data from the Pediatric Imaging, Neurocognition, and Genetics Project (PING).

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

Altered regional brain volumes in elderly carriers of a risk variant for drug abuse in the dopamine D2 receptor gene (DRD2)

Dopamine D2 receptors mediate the rewarding effects of many drugs of abuse. In humans, several polymorphisms in DRD2, the gene encoding these receptors, increase our genetic risk for developing addictive disorders. Here, we examined one of the most frequently studied candidate variant for addiction in DRD2 for association with brain structure. We tested whether this variant showed associations with regional brain volumes across two independent elderly cohorts, totaling 1,032 subjects. We first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI1). We hypothesized that this addiction-related polymorphism would be associated with structural brain differences in regions previously implicated in familial vulnerability for drug dependence. Then, we assessed the generalizability of our findings by testing this polymorphism in a non-overlapping replication sample of 294 elderly subjects from a continuation of the first ADNI project (ADNI2) to minimize the risk of reporting false positive results. In both cohorts, the minor allele-previously linked with increased risk for addiction-was associated with larger volumes in various brain regions implicated in reward processing. These findings suggest that neuroanatomical phenotypes associated with familial vulnerability for drug dependence may be partially mediated by DRD2 genotype.

The effect of increased genetic risk for Alzheimer's disease on hippocampal and amygdala volume

Reduction in hippocampal and amygdala volume measured via structural magnetic resonance imaging is an early marker of Alzheimer's disease (AD). Whether genetic risk factors for AD exert an effect on these subcortical structures independent of clinical status has not been fully investigated. We examine whether increased genetic risk for AD influences hippocampal and amygdala volumes in case-control and population cohorts at different ages, in 1674 older (aged >53 years; 17% AD, 39% mild cognitive impairment [MCI]) and 467 young (16-30 years) adults. An AD polygenic risk score combining common risk variants excluding apolipoprotein E (APOE), and a single nucleotide polymorphism in TREM2, were both associated with reduced hippocampal volume in healthy older adults and those with MCI. APOE ε4 was associated with hippocampal and amygdala volume in those with AD and MCI but was not associated in healthy older adults. No associations were found in young adults. Genetic risk for AD affects the hippocampus before the clinical symptoms of AD, reflecting a neurodegenerative effect before clinical manifestations in older adults.

The senescent methylome and its relationship with cancer, ageing and germline genetic variation in humans

BACKGROUND

Cellular senescence is a stable arrest of proliferation and is considered a key component of processes associated with carcinogenesis and other ageing-related phenotypes. Here, we perform methylome analysis of actively dividing and deeply senescent normal human epithelial cells.

RESULTS

We identify senescence-associated differentially methylated positions (senDMPs) from multiple experiments using cells from one donor. We find that human senDMP epigenetic signatures are positively and significantly correlated with both cancer and ageing-associated methylation dynamics. We also identify germline genetic variants, including those associated with the p16INK4A locus, which are associated with the presence of in vivo senDMP signatures. Importantly, we also demonstrate that a single senDMP signature can be effectively reversed in a newly-developed protocol of transient senescence reversal.

CONCLUSIONS

The senDMP signature has significant potential for understanding some of the key (epi)genetic etiological factors that may lead to cancer and age-related diseases in humans.

Altered mesocorticolimbic functional connectivity in psychotic disorder: an analysis of proxy genetic and environmental effects

BACKGROUND

Altered dopaminergic neurotransmission in the mesocorticolimbic (MCL) system may mediate psychotic symptoms. In addition, pharmacological dopaminergic manipulation may coincide with altered functional connectivity (fc) 'in rest'. We set out to test whether MCL-fc is conditional on (familial risk for) psychotic disorder and/or interactions with environmental exposures.

METHOD

Resting-state functional magnetic resonance imaging data were obtained from 63 patients with psychotic disorder, 73 non-psychotic siblings of patients with psychotic disorder and 59 healthy controls. With the nucleus accumbens (NAcc) as seed region, fc within the MCL system was estimated. Regression analyses adjusting for a priori hypothesized confounders were used to assess group differences in MCL connectivity as well as gene (group) × environmental exposure interactions (G × E) (i.e., to cannabis, developmental trauma and urbanicity).

RESULTS

Compared with controls, patients and siblings had decreased fc between the right NAcc seed and the right orbitofrontal cortex (OFC) as well as the left middle cingulate cortex (MCC). Siblings showed decreased connectivity between the NAcc seed and lentiform nucleus compared with patients and controls. In addition, patients had decreased left NAcc connectivity compared with siblings in the left middle frontal gyrus. There was no evidence for a significant interaction between group and the three environmental exposures in the model of MCL-fc.

CONCLUSIONS

Reduced NAcc-OFC/MCC connectivity was seen in patients and siblings, suggesting that altered OFC connectivity and MCC connectivity are vulnerability markers for psychotic disorder. Differential exposure to environmental risk factors did not make an impact on the association between familial risk and MCL connectivity.

Differential Natural Selection of Human Zinc Transporter Genes between African and Non-African Populations

Zinc transporters play important roles in all eukaryotes by maintaining the rational zinc concentration in cells. However, the diversity of zinc transporter genes (ZTGs) remains poorly studied. Here, we investigated the genetic diversity of 24 human ZTGs based on the 1000 Genomes data. Some ZTGs show small population differences, such as SLC30A6 with a weighted-average FST (WA-FST = 0.015), while other ZTGs exhibit considerably large population differences, such as SLC30A9 (WA-FST = 0.284). Overall, ZTGs harbor many more highly population-differentiated variants compared with random genes. Intriguingly, we found that SLC30A9 was underlying natural selection in both East Asians (EAS) and Africans (AFR) but in different directions. Notably, a non-synonymous variant (rs1047626) in SLC30A9 is almost fixed with 96.4% A in EAS and 92% G in AFR, respectively. Consequently, there are two different functional haplotypes exhibiting dominant abundance in AFR and EAS, respectively. Furthermore, a strong correlation was observed between the haplotype frequencies of SLC30A9 and distributions of zinc contents in soils or crops. We speculate that the genetic differentiation of ZTGs could directly contribute to population heterogeneity in zinc transporting capabilities and local adaptations of human populations in regard to the local zinc state or diets, which have both evolutionary and medical implications.

The perfect neuroimaging-genetics-computation storm: collision of petabytes of data, millions of hardware devices and thousands of software tools

The volume, diversity and velocity of biomedical data are exponentially increasing providing petabytes of new neuroimaging and genetics data every year. At the same time, tens-of-thousands of computational algorithms are developed and reported in the literature along with thousands of software tools and services. Users demand intuitive, quick and platform-agnostic access to data, software tools, and infrastructure from millions of hardware devices. This explosion of information, scientific techniques, computational models, and technological advances leads to enormous challenges in data analysis, evidence-based biomedical inference and reproducibility of findings. The Pipeline workflow environment provides a crowd-based distributed solution for consistent management of these heterogeneous resources. The Pipeline allows multiple (local) clients and (remote) servers to connect, exchange protocols, control the execution, monitor the states of different tools or hardware, and share complete protocols as portable XML workflows. In this paper, we demonstrate several advanced computational neuroimaging and genetics case-studies, and end-to-end pipeline solutions. These are implemented as graphical workflow protocols in the context of analyzing imaging (sMRI, fMRI, DTI), phenotypic (demographic, clinical), and genetic (SNP) data.

The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers

The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI), formally established in 2009, aims to provide resources and facilitate research related to genetic predictors of multidimensional Alzheimer's disease (AD)-related phenotypes. Here, we provide a systematic review of genetic studies published between 2009 and 2012 where either ADNI APOE genotype or genome-wide association study (GWAS) data were used. We review and synthesize ADNI genetic associations with disease status or quantitative disease endophenotypes including structural and functional neuroimaging, fluid biomarker assays, and cognitive performance. We also discuss the diverse analytical strategies used in these studies, including univariate and multivariate analysis, meta-analysis, pathway analysis, and interaction and network analysis. Finally, we perform pathway and network enrichment analyses of these ADNI genetic associations to highlight key mechanisms that may drive disease onset and trajectory. Major ADNI findings included all the top 10 AD genes and several of these (e.g., APOE, BIN1, CLU, CR1, and PICALM) were corroborated by ADNI imaging, fluid and cognitive phenotypes. ADNI imaging genetics studies discovered novel findings (e.g., FRMD6) that were later replicated on different data sets. Several other genes (e.g., APOC1, FTO, GRIN2B, MAGI2, and TOMM40) were associated with multiple ADNI phenotypes, warranting further investigation on other data sets. The broad availability and wide scope of ADNI genetic and phenotypic data has advanced our understanding of the genetic basis of AD and has nominated novel targets for future studies employing next-generation sequencing and convergent multi-omics approaches, and for clinical drug and biomarker development.

A single nucleotide polymorphism associated with reduced alcohol intake in the RASGRF2 gene predicts larger cortical volumes but faster longitudinal ventricular expansion in the elderly

A recent genome-wide association meta-analysis showed a suggestive association between alcohol intake in humans and a common single nucleotide polymorphism in the ras-specific guanine nucleotide releasing factor 2 gene. Here, we tested whether this variant – associated with lower alcohol consumption – showed associations with brain structure and longitudinal ventricular expansion over time, across two independent elderly cohorts, totaling 1,032 subjects. We first examined a large sample of 738 elderly participants with neuroimaging and genetic data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI1). Then, we assessed the generalizability of the findings by testing this polymorphism in a replication sample of 294 elderly subjects from a continuation of the first ADNI project (ADNI2) to minimize the risk of reporting false positive results. The minor allele – previously linked with lower alcohol intake – was associated with larger volumes in various cortical regions, notably the medial prefrontal cortex and cingulate gyrus in both cohorts. Intriguingly, the same allele also predicted faster ventricular expansion rates in the ADNI1 cohort at 1- and 2-year follow up. Despite a lack of alcohol consumption data in this study cohort, these findings, combined with earlier functional imaging investigations of the same gene, suggest the existence of reciprocal interactions between genes, brain, and drinking behavior.

The Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.