Cannabis is the most widely used illicit drug throughout the developed world and there is consistent evidence of heritable influences on multiple stages of cannabis involvement including initiation of use and abuse/dependence. In this paper, we describe the methodology and preliminary results of a large-scale interview study of 3,824 young adult twins (born 1972–1979) and their siblings. Cannabis use was common with 75.2% of males and 64.7% of females reporting some lifetime use of cannabis while 24.5% of males and 11.8% of females reported meeting criteria for DSM-IV cannabis abuse or dependence. Rates of other drug use disorders and common psychiatric conditions were highly correlated with extent of cannabis involvement and there was consistent evidence of heritable influences across a range of cannabis phenotypes including early (≤15 years) opportunity to use (h2 = 72%), early (≤16 years) onset use (h2 = 80%), using cannabis 11+ times lifetime (h2 = 76%), and DSM abuse/dependence (h2 = 72%). Early age of onset of cannabis use was strongly associated with increased rates of subsequent use of other illicit drugs and with illicit drug abuse/dependence; further analyses indicating that some component of this association may have been mediated by increasing exposure to and opportunity to use other illicit drugs.
Cannabis; twin; Comorbidity; Illicit drugs
The development of late-onset Alzheimer’s disease (LOAD) is under strong genetic control and there is great interest in the genetic variants that confer increased risk. The Alzheimer’s disease risk gene, growth factor receptor bound protein 2-associated protein (GAB2), has been shown to provide a 1.27–1.51 increased odds of developing LOAD for rs7101429 major allele carriers, in case-control analysis. GAB2 is expressed across the brain throughout life, and its role in LOAD pathology is well understood. Recent studies have begun to examine the effect of genetic variation in the GAB2 gene on differences in the brain. However, the effect of GAB2 on the young-adult brain has yet to be considered. Here we found a significant association between the GAB2 gene and morphological brain differences in 755 young-adult twins (469 females) (M = 23.1, SD = 3.1 years), using a gene-based test with principal components regression (PCReg). Detectable differences in brain morphology are therefore associated with variation in the GAB2 gene, even in young adults, long before the typical age of onset of Alzheimer’s disease.
GAB2; imaging genetics; tensor-based morphometry; Alzheimer’s disease
Several common genetic variants have recently been discovered that appear to influence white matter microstructure, as measured by diffusion tensor imaging (DTI). Each genetic variant explains only a small proportion of the variance in brain microstructure, so we set out to explore their combined effect on the white matter integrity of the corpus callosum. We measured six common candidate single-nucleotide polymorphisms (SNPs) in the COMT, NTRK1, BDNF, ErbB4, CLU, and HFE genes, and investigated their individual and aggregate effects on white matter structure in 395 healthy adult twins and siblings (age: 20–30 years). All subjects were scanned with 4-tesla 94-direction high angular resolution diffusion imaging. When combined using mixed-effects linear regression, a joint model based on five of the candidate SNPs (COMT, NTRK1, ErbB4, CLU, and HFE) explained ∼6% of the variance in the average fractional anisotropy (FA) of the corpus callosum. This predictive model had detectable effects on FA at 82% of the corpus callosum voxels, including the genu, body, and splenium. Predicting the brain's fiber microstructure from genotypes may ultimately help in early risk assessment, and eventually, in personalized treatment for neuropsychiatric disorders in which brain integrity and connectivity are affected.
neuroimaging; brain structure; DTI; genetics; genetic profiles; prediction; imaging; clinical or preclinical; neuroanatomy; neurogenetics; pharmacogenetics / pharmacogenomics; neuroimaging; brain structure; DTI; genetics; genetic profiles
The patient population of borderline personality disorder (BPD) is heterogeneous; many different combinations of BPD symptoms can lead to a BPD diagnosis. We investigated to what extent the covariance among four main components of BPD is explained by shared genetic and environmental factors. Using an extended twin design, multivariate genetic models were applied to the scales of the PAI-BOR, a self-report questionnaire tapping four main features of BPD (affective instability, identity problems, negative relationships, and self-harm). Data on the four BPD scales were available for 5,533 twins and 1,202 siblings from the Netherlands, Belgium, and Australia. The correlations among the scales ranged from 0.23 to 0.50 and were best explained by a genetic common pathway model. This model specifies that genes and environment influence the covariance between four main features of BPD in qualitatively similar ways, through a single latent factor representing the BPD construct. The heritability of the latent BPD factor was 51% and the remainder of its variance was explained by unique environmental influences. For each BPD scale, except self-harm, around 50% of its variance was explained by the latent BPD factor. The remaining variance for each of the four scales was explained by genetic (4% for affective instability to 20% for self-harm) and environmental (38% for negative relationships to 67% for self-harm) factors that were specific to each scale.
The endocannabinoid system has been implicated in stress adaptation and the regulation of mood in rodent studies, but few human association studies have examined these links and replications are limited.
To examine whether a synonymous polymorphism, rs1049353, in exon 4 of the gene encoding the human endocannabinoid receptor (CNR1) moderates the effect of self-reported childhood physical abuse on lifetime anhedonia and depression and further, to replicate this interaction in an independent sample.
Genetic association study in 1041 young adult U.S. women with replication in an independent Australian sample of 1428 heroin dependent cases and 506 neighborhood controls.
Main outcome measure
Self-reported anhedonia and depression (with anhedonia).
In both samples, those who experienced childhood physical abuse were considerably more likely to report lifetime anhedonia. However, in those with one or more copies of the minor allele of rs1049353, this pathogenic effect of childhood physical abuse was attenuated. Thus, in those reporting childhood physical abuse, while 57% of those homozygous for the major allele reported anhedonia, only 29% of those who were carriers of the minor allele reported it (p < 0.02). rs1049353 also buffered the effects of childhood physical abuse on major depressive disorder, however this influence was largely attributable to anhedonic depression. These effects were also noted in an independent sample, where minor allele carriers were at decreased risk for anhedonia even when exposed to physical abuse.
Consistent with preclinical findings, a synonymous CNR1 polymorphism, rs1049353, is linked to the effects of stress attributable to childhood physical abuse on anhedonia and anhedonic depression. This polymorphism reportedly resides in the neighborhood of an exon splice enhancer and hence, future studies should carefully examine its impact on expression and conformational variation in CNR1, particularly in relation to stress adaptation.
CNR1; endocannabinoid; physical abuse; rs1049353; GxE; anhedonia; major depression
This study demonstrates a novel approach to test associations between highly heterogeneous genetic loci and complex phenotypes. Previous investigations of the relationship between Cytochrome P450 2A6 (CYP2A6) genotype and smoking phenotypes made comparisons by dividing subjects into broad categories based on assumptions that simplify the range of function of different CYP2A6 alleles, their numerous possible diplotype combinations and non-additive allele effects. A predictive model that translates CYP2A6 diplotype into a single continuous variable was previously derived from an in vivo metabolism experiment in 189 European Americans. Here, we apply this model to assess associations between genotype, inferred nicotine metabolism and smoking behaviors in larger samples without direct nicotine metabolism measurements. CYP2A6 genotype is not associated with nicotine dependence, as defined by the Fagerström Test of Nicotine Dependence, demonstrating that cigarettes smoked per day (CPD) and nicotine dependence have distinct genetic correlates. The predicted metric is significantly associated with CPD among African Americans and European American dependent smokers. Individual slow metabolizing genotypes are associated with lower CPD, but the predicted metric is the best predictor of CPD. Furthermore, optimizing the predictive model by including additional CYP2A6 alleles improves the fit of the model in an independent data set and provides a novel method of predicting the functional impact of alleles without direct metabolism measurements. Lastly, comprehensive genotyping and in vivo metabolism data are used to demonstrate that genome-wide significant associations between CPD and single nucleotide polymorphisms are the result of synthetic associations.
Twin pairs and their siblings rated the intensity of the odorants amyl acetate,
androstenone, eugenol, Galaxolide, mercaptans, and rose (N =
1573). Heritability was established for ratings of androstenone (h
2 = 0.30) and Galaxolide (h2 = 0.34) but not for the other odorants. Genome-wide association analysis
using 2.3 million single nucleotide polymorphisms indicated that the most significant
association was between androstenone and a region without known olfactory receptor genes
(rs10966900, P = 1.2 ×
10−7). A previously reported association between the olfactory receptor
OR7D4 and the androstenone was not detected until we specifically typed
this gene (P = 1.1 × 10−4). We also tested
these 2 associations in a second independent sample of subjects and replicated the results
either fully (OR7D4, P = 0.00002) or partially
(rs10966900, P = 0.010; N
= 266). These findings suggest that 1) the perceived intensity of some but not all
odorants is a heritable trait, 2) use of a current genome-wide marker panel did not detect
a known olfactory genotype–phenotype association, and 3) person-to-person
differences in androstenone perception are influenced by OR7D4 genotype
and perhaps by variants of other genes.
androstenone; Galaxolide; genetic twin modeling; genome-wide association study; heritability; twins
The CHRNA5-CHRNA3-CHRNB4 gene cluster on chromosome 15q25.1 encoding the cholinergic nicotinic receptor subunits is robustly associated with smoking behavior and nicotine dependence. Only a few studies to date have examined the locus with alcohol related traits and found evidence of association with alcohol abuse and dependence. Our main goal was to examine the role of three intensively studied single nucleotide polymorphisms, rs16969968, rs578776 and rs588765, tagging three distinct loci, in alcohol use. Our sample was drawn from two independent Finnish population-based surveys, the National FINRISK Study and the Health 2000 (Health Examination) Survey. The combined sample included a total of 32,592 adult Finns (54% women) of whom 8,356 were assessed for cigarettes per day (CPD). Data on alcohol use were available for 31,812 individuals. We detected a novel association between rs588765 and alcohol use defined as abstainers and low-frequency drinkers versus drinkers (OR=1.15, p=0.00007). Additionally, we provide precise estimates of strength of the association between the three loci and smoking quantity in a very large population based sample. As a conclusion, our results provide further evidence for the nicotine-specific role of rs16969968 (locus 1). Further, our data suggest that the effect of rs588765 (locus 3) may be specific to alcohol use as the effect is seen also in never smokers.
Nicotinic acetylcholine receptors; 15q25.1; alcohol use; smoking behavior; public health; population-based sample; genetic association
Cutaneous malignant melanoma (CMM) is a major health issue in Queensland, Australia which has the world’s highest incidence. Recent molecular and epidemiologic studies suggest that CMM arises through multiple etiological pathways involving gene-environment interactions. Understanding the potential mechanisms leading to CMM requires larger studies than those previously conducted. This article describes the design and baseline characteristics of Q-MEGA, the Queensland study of Melanoma: Environmental and Genetic Associations, which followed-up four population-based samples of CMM patients in Queensland, including children, adolescents, men aged over 50, and a large sample of adult cases and their families, including twins. Q-MEGA aims to investigate the roles of genetic and environmental factors, and their interaction, in the etiology of melanoma. 3,471 participants took part in the follow-up study and were administered a computer-assisted telephone interview in 2002–2005. Updated data on environmental and phenotypic risk factors, and 2,777 blood samples were collected from interviewed participants as well as a subset of relatives. This study provides a large and well-described population-based sample of CMM cases with follow-up data. Characteristics of the cases and repeatability of sun exposure and phenotype measures between the baseline and the follow-up surveys, from six to 17 years later, are also described.
We have previously described the role of red hair (Melanocortin 1 Receptor, MC1R) and blue eye (Oculocutaneous Albinism Type 2, OCA2) gene polymorphisms in modulating risk of cutaneous malignant melanoma (CMM) in a highly sun-exposed population of European descent. A number of recent studies, including genome-wide association studies (GWAS), have identified numerous polymorphisms controlling human hair, eye and skin colour. In this paper, we test a selected set of polymorphisms in pigmentation loci (ASIP, TYR, TYRP1, MC1R, OCA2, IRF4, SLC24A4, SLC45A2) for association with CMM risk in a large Australian population-based case control study. Variants in IRF4 and SLC24A4, despite being strongly associated with pigmentation in our sample, did not modify CMM risk, but the other six did. Three SNPs (rs28777, rs35391, rs16891982) in the MATP gene (SLC45A2) exhibited the strongest crude association with risk, but this was attenuated to approximately the same effect size as that of a MC1R red hair color allele by controlling for ancestry of cases and controls. We also detected significant epistatic interactions between SLC45A2 and OCA2 alleles, and MC1R and ASIP alleles. Overall, these measured variants account for 12% of the familial risk of CMM in our population.
The prevalence of cutaneous malignant melanoma (CMM) has increased significantly in most Caucasian populations in recent decades. Both genetic and environment are significant risk factors involved in the development of CMM. A germline mutation in the Syntaxin 17 (STX17) gene was recently identified in horses causing premature hair gray and associated with susceptibility to melanoma. We hypothesized that common germline variants in the STX17 gene might be associated with predisposition to human CMM or might interact with other melanoma risk genes. We conducted a case-control study by genotyping 26 tagging single nucleotide polymorphisms (SNPs) across the STX17 gene region in an Australian sample and performed logistic regression analysis for predicting the possible SNP interactions in a combined dataset. Our results do not support an association between CMM and any of the STX17 SNPs and provide no evidence for interactions between the melanoma risk SNP rs910873 on chromosome 20 and any of the STX17 SNPs. We conclude that common variants in the STX17 gene region do not play a key role in the pathogenesis of human melanoma.
Syntaxin 17; melanoma; polymorphisms
The cardiometabolic syndrome comprised of multiple correlated traits, but its origin is incompletely understood. Chromogranin A (CHGA) is required for formation of the catecholamine secretory pathway in sympathochromaffin cells. In twin pair studies, we found that CHGA traits aggregated with body mass index (BMI), as well as its biochemical determinant leptin.
Here we used the twin method to probe the role of heredity in generating such risk traits, and then investigated the role of risk-trait-associated CHGA promoter genetic variation in transfected chromaffin cells. Trait heritability (h2) and shared genetic determination among traits (pleiotropy, genetic covariance, ρG) were estimated by variance components in twin pairs.
CHGA, BMI, and leptin each displayed substantial h2, and the traits also aggregated with several features of the metabolic syndrome (e.g., insulin resistance, blood pressure (BP), hypertension, catecholamines, and C-reactive protein (CRP)). Twin studies demonstrated genetic covariance (pleiotropy, ρG) for CHGA, BMI, and leptin with other metabolic traits (insulin resistance, BP, and CRP). We therefore investigated the CHGA locus for mechanisms of codetermination with such metabolic traits. A common functional variant in the human CHGA promoter (G-462A, rs9658634, minor allele frequency ~21%) was associated with leptin and CRP secretion, as well as BMI, especially in women; marker-on-trait effects on BMI were replicated across twin populations on two continents. In CHGA promoter/luciferase reporter plasmids transfected into chromaffin cells, G-462A alleles differed markedly in reporter expression. The G-462A variant disrupted predicted transcriptional control by a PPARγ/RXRα motif and costimulation by PPARγ/RXRα and their cognate ligands, differentially activated the two alleles. During chromatin immunoprecipitation, endogenous PPARγ bound the motif.
Multiple features of the metabolic syndrome are thus under joint (pleiotropic) genetic determination, with CHGA as one such contributory locus: a common polymorphism in the promoter (G-462A) of CHGA predicts such heritable metabolic traits as BMI and leptin. CHGA promoter variant G-462A was not only associated with such metabolic traits but also disrupted a PPARγ/RXRα motif and responded differentially to characteristic trans-activators of that motif. The results suggest novel links between the catecholaminergic system and risk for the metabolic syndrome as well as systemic hypertension.
adrenal; blood pressure; BMI; C-reactive protein; catecholamine; chromaffin; chromogranin; hypertension; leptin; metabolic syndrome; twin study
While there is solid evidence that cannabis use is heritable, attempts to identify genetic influences at the molecular level have yielded mixed results. Here, a large twin family sample (N=7452) was used to test for association between ten previously reported candidate genes and lifetime frequency of cannabis use using a gene-based association test. None of the candidate genes reached even nominal significance (p<.05). The lack of replication may point to our limited understanding of the neurobiology of cannabis involvement and also to potential publication bias and false-positive findings in previous studies.
genes; cannabis; genetics; association
Traits that are attractive to the opposite sex are often positively correlated when scaled such that scores increase with attractiveness, and this correlation typically has a genetic component. Such traits can be genetically correlated due to genes that affect both traits (“pleiotropy”) and/or because assortative mating causes statistical correlations to develop between selected alleles across the traits (“gametic phase disequilibrium”). In this study, we modeled the covariation between monozygotic and dizygotic twins, their siblings, and their parents (total N = 7,905) to elucidate the nature of the correlation between two potentially sexually selected traits in humans: height and IQ. Unlike previous designs used to investigate the nature of the height–IQ correlation, the present design accounts for the effects of assortative mating and provides much less biased estimates of additive genetic, non-additive genetic, and shared environmental influences. Both traits were highly heritable, although there was greater evidence for non-additive genetic effects in males. After accounting for assortative mating, the correlation between height and IQ was found to be almost entirely genetic in nature. Model fits indicate that both pleiotropy and assortative mating contribute significantly and about equally to this genetic correlation.
Traits that are attractive to the opposite sex are often positively correlated when scaled such that scores increase with attractiveness, and this correlation typically has a genetic component. Such traits can be genetically correlated due to genes that affect both traits and/or because assortative mating (people choosing mates who are similar to themselves) causes statistical correlations to develop between selected alleles across the traits. In this study, we used a large (total N = 7,905), genetically informative dataset to understand why two potentially sexually selected traits in humans—height and IQ—are correlated. We found that both shared genes and assortative mating were about equally important in causing the relationship between these two traits. To our knowledge, this is the first study that has been able to disambiguate the two principal reasons—shared genes versus assortative mating—for why traits can be genetically correlated.
Irregularity in the corneal curvature (CC) is highly associated with various eye disorders such as keratoconus and myopia. The sample had limited power to find genomewide significant (5 × 10−8) hits but good power for replication. Thus, an attempt was made to test whether alleles in the FRAP1 and PDGFRA genes, recently found to be associated with CC in Asian populations, also influence CC in Australians of North European ancestry. Results of initial genomewide association studies (GWAS) for CC in Australians were also reported.
Two population-based cohorts of 1788 Australian twins and their families, as well as 1013 individuals from a birth cohort from Western Australia, were genotyped using genomewide arrays. Following separate individual analysis and quality control, the results from each cohort underwent meta-analysis.
Meta-analysis revealed significant replication of association between rs2114039 and corneal curvature (P = 0.0045). The SNP rs2114039 near PDGFRA has been previously implicated in Asians. No SNP at the FRAP1 locus was found to be associated in our Australian samples. No SNP surpassed the genomewide significance threshold of 5 × 10−8. The SNP with strongest association was rs2444240 (P = 3.658 × 10−7), which is 31 kb upstream to the TRIM29 gene.
A significant role of the PDGFRA gene in determining corneal curvature in the Australian population was confirmed in this study, also highlighting the putative association of the TRIM29 locus with CC.
Corneal curvature (CC) is a risk factor for various vision disorders including keratoconus and myopia. This study reports association of the PDGFRA gene with CC in the Australian population, which was previously found to be associated in an Asian population. It also reports initial GWAS findings on CC in Australians.
We present an approximate conditional and joint association analysis that can use summary-level statistics from a meta-analysis of genome-wide association studies (GWAS) and estimated linkage disequilibrium (LD) from a reference sample with individual-level genotype data. Using this method, we analyzed meta-analysis summary data from the GIANT Consortium for height and body mass index (BMI), with the LD structure estimated from genotype data in two independent cohorts. We identified 36 loci with multiple associated variants for height (38 leading and 49 additional SNPs, 87 in total) via a genome-wide SNP selection procedure. The 49 new SNPs explain approximately 1.3% of variance, nearly doubling the heritability explained at the 36 loci. We did not find any locus showing multiple associated SNPs for BMI. The method we present is computationally fast and is also applicable to case-control data, which we demonstrate in an example from meta-analysis of type 2 diabetes by the DIAGRAM Consortium.
Women now represent nearly half of all individuals in treatment for pathological gambling (PG), but relatively little is known about the causes of PG among women or potential sex differences in the causes of PG.
To (1) investigate the role of genetic and environmental risk factors in the development of disordered gambling (DG) among women and (2) determine the extent to which the genetic and environmental risk of DG among women differs quantitatively or qualitatively from the risk of DG among men. (Disordered gambling refers to the full continuum of gambling-related problems that includes PG disorder.)
The national community-based Australian Twin Registry.
Four thousand seven hundred sixty-four individuals from 2889 twin pairs; twins were aged 32 to 43 years and 57% were women.
Main Outcome Measure
Disordered gambling was defined based on lifetime DSM-IV PG symptom counts.
The estimate of the proportion of variation in liability forDGdue to genetic influences was 49.2% (95% confidence interval, 26.7–60.9). There was no evidence for shared environmental influences contributing to variation in DG liability. There was no evidence for quantitative or qualitative sex differences in the causes of variation in DG liability.
This study establishes for the first time that genes are as important in the etiology of DG in women as they are in men and that the susceptibility genes contributing to variation in liability for DG are likely to overlap considerably in men and women.
Gays, lesbians, and bisexuals (i.e. nonheterosexuals) have been found to be at much greater risk for many psychiatric symptoms and disorders, including depression. This may be due in part to prejudice and discrimination experienced by nonheterosexuals, but studies controlling for minority stress, or performed in very socially liberal countries, suggest that other mechanisms must also play a role. Here we test the viability of common cause (shared genetic or environmental etiology) explanations of elevated depression rates in nonheterosexuals.
A community-based sample of adult twins (N=9884 individuals) completed surveys investigating the genetics of psychiatric disorder, and were also asked about their sexual orientation. Large subsets of the sample were asked about adverse childhood experiences such as sexual abuse, physical abuse, and risky family environment, and also about number of older brothers, paternal and maternal age, and number of close friends. Data were analysed using the classical twin design.
Nonheterosexual males and females had higher rates of lifetime depression than their heterosexual counterparts. Genetic factors accounted for 31% and 44% of variation in sexual orientation and depression, respectively. Bivariate analysis revealed that genetic factors accounted for a majority (60%) of the correlation between sexual orientation and depression. In addition, childhood sexual abuse and risky family environment were significant predictors of both sexual orientation and depression, further contributing to their correlation.
Nonheterosexual men and women had elevated rates of lifetime depression, partly due to shared etiological factors, although causality cannot be definitively resolved.
sexual orientation; childhood abuse; depression; twins; genetics
Understanding the relative contributions of genetic and environmental factors to trauma exposure, post-traumatic stress disorder (PTSD), and major depressive disorder (MDD) is critical to developing etiologic models of these conditions and their co-occurrence.
To quantify heritable influences on low-risk trauma, high-risk trauma, PTSD, and MDD and to estimate the degree of overlap between genetic and environmental sources of variance in these 4 phenotypes.
Adult twins and their siblings were ascertained from a large population-based sample of female and male twin pairs on the basis of screening items for childhood sexual abuse and physical abuse obtained in a previous assessment of this cohort.
Structured psychiatric telephone interviews.
Total sample size of 2591: 996 female and 536 male twins; 625 female and 434 male nontwin siblings.
Main Outcome Measure
Lifetime low- and high-risk trauma exposure, PTSD, and MDD.
In the best-fitting genetic model, 47% of the variance in low-risk trauma exposure and 60% of the variance in high-risk trauma exposure was attributable to additive genetic factors. Heritable influences accounted for 46% of the variance in PTSD and 27% of the variance in MDD. An extremely high degree of genetic overlap was observed between high-risk trauma exposure and both PTSD (r =0.89; 95% CI, 0.78-0.99) and MDD (r =0.89; 95% CI, 0.77-0.98). Complete correlation of genetic factors contributing to PTSD and to MDD (r=1.00) was observed.
The evidence suggests that almost all the heritable influences on high-risk trauma exposure, PTSD, and MDD, can be traced to the same sources; that is, genetic risk is not disorder specific. Individuals with a positive family history of either PTSD or MDD are at elevated risk for both disorders and should be closely monitored after a traumatic experience for symptoms of PTSD and MDD.
Modern non-invasive brain imaging technologies, such as diffusion weighted magnetic resonance imaging (DWI), enable the mapping of neural fiber tracts in the white matter, providing a basis to reconstruct a detailed map of brain structural connectivity networks. Brain connectivity networks differ from random networks in their topology, which can be measured using small worldness, modularity, and high-degree nodes (hubs). Still, little is known about how individual differences in structural brain network properties relate to age, sex, or genetic differences. Recently, some groups have reported brain network biomarkers that enable differentiation among individuals, pairs of individuals, and groups of individuals. In addition to studying new topological features, here we provide a unifying general method to investigate topological brain networks and connectivity differences between individuals, pairs of individuals, and groups of individuals at several levels of the data hierarchy, while appropriately controlling false discovery rate (FDR) errors. We apply our new method to a large dataset of high quality brain connectivity networks obtained from High Angular Resolution Diffusion Imaging (HARDI) tractography in 303 young adult twins, siblings, and unrelated people. Our proposed approach can accurately classify brain connectivity networks based on sex (93% accuracy) and kinship (88.5% accuracy). We find statistically significant differences associated with sex and kinship both in the brain connectivity networks and in derived topological metrics, such as the clustering coefficient and the communicability matrix.
Anatomical brain connectivity; Complex networks; Diffusion weighted MRI; Topological analysis; Hierarchical analysis; False discovery rate; Sex and kinship brain network differences
Large multi-site image-analysis studies have successfully discovered genetic variants that affect brain structure in tens of thousands of subjects scanned worldwide. Candidate genes have also associated with brain integrity, measured using fractional anisotropy in diffusion tensor images (DTI). To evaluate the heritability and robustness of DTI measures as a target for genetic analysis, we compared 417 twins and siblings scanned on the same day on the same high field scanner (4-Tesla) with two protocols: (1) 94-directions; 2mm-thick slices, (2) 27-directions; 5mm-thickness. Using mean FA in white matter ROIs and FA ‘skeletons’ derived using FSL, we (1) examined differences in voxelwise means, variances, and correlations among the measures; and (2) assessed heritability with structural equation models, using the classical twin design. FA measures from the genu of the corpus callosum were highly heritable, regardless of protocol. Genome-wide analysis of the genu mean FA revealed differences across protocols in the top associations.
imaging genetics; DTI protocol stability; corpus callosum; genome-wide association study; multi-site analysis
Graph theory can be applied to matrices that represent the brain’s anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and “small-world” topology. Network analysis is popular in adult studies of connectivity, but only one study – in just 30 subjects – has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.
graph theory; high angular resolution diffusion imaging (HARDI); tractography; network analyses; development; structural connectivity
Human brain connectivity is disrupted in a wide range of disorders – from Alzheimer’s disease to autism – but little is known about which specific genes affect it. Here we conducted a genome-wide association for connectivity matrices that capture information on the density of fiber connections between 70 brain regions. We scanned a large twin cohort (N=366) with 4-Tesla high angular resolution diffusion imaging (105-gradient HARDI). Using whole brain HARDI tractography, we extracted a relatively sparse 70×70 matrix representing fiber density between all pairs of cortical regions automatically labeled in co-registered anatomical scans. Additive genetic factors accounted for 1–58% of the variance in connectivity between 90 (of 122) tested nodes. We discovered genome-wide significant associations between variants and connectivity. GWAS permutations at various levels of heritability, and split-sample replication, validated our genetic findings. The resulting genes may offer new leads for mechanisms influencing aberrant connectivity and neurodegeneration.
genetics; high angular resolution diffusion imaging (HARDI); cortical surfaces; twin modeling; human connectome