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Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury 1-4 . These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries 5 . Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in sample size and genetic diversity improved locus identification and fine-mapping resolution, and that a large majority of the 3,823 associated variants (from 2,143 loci) showed consistent effect sizes across ancestry dimensions. However, polygenic risk scores developed in one ancestry performed poorly in others, highlighting the continued need to increase sample sizes of diverse ancestries to realize any potential benefit of polygenic prediction., (© 2022. The Author(s).)

Structural brain changes along the lineage leading to modern Homo sapiens contributed to our distinctive cognitive and social abilities. However, the evolutionarily relevant molecular variants impacting key aspects of neuroanatomy are largely unknown. Here, we integrate evolutionary annotations of the genome at diverse timescales with common variant associations from large-scale neuroimaging genetic screens. We find that alleles with evidence of recent positive polygenic selection over the past 2000-3000 years are associated with increased surface area (SA) of the entire cortex, as well as specific regions, including those involved in spoken language and visual processing. Therefore, polygenic selective pressures impact the structure of specific cortical areas even over relatively recent timescales. Moreover, common sequence variation within human gained enhancers active in the prenatal cortex is associated with postnatal global SA. We show that such variation modulates the function of a regulatory element of the developmentally relevant transcription factor HEY2 in human neural progenitor cells and is associated with structural changes in the inferior frontal cortex. These results indicate that non-coding genomic regions active during prenatal cortical development are involved in the evolution of human brain structure and identify novel regulatory elements and genes impacting modern human brain structure., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10 -8 ) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (r G  = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.

This letter reflects on my collaborations with Nick Martin over the past 18 years. Working together we have applied twin-family and statistical genetics methods to examine the genetic architecture and identify genetic variants influencing a range of physical, psychological and social traits. The common thread across much of this work has been the empirical questions: Why are we the way we are and how can this knowledge help us when things go wrong?

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Background: There have been considerable recent advances in understanding the genetic architecture of anxiety disorders and posttraumatic stress disorder (PTSD), as well as the underlying neurocircuitry of these disorders. However, there is little work on the concordance of genetic variations that increase risk for these conditions, and that influence subcortical brain structures. We undertook a genome-wide investigation of the overlap between the genetic influences from single nucleotide polymorphisms (SNPs) on volumes of subcortical brain structures and genetic risk for anxiety disorders and PTSD., Method: We obtained summary statistics of genome-wide association studies (GWAS) of anxiety disorders (N cases   = 7016, N controls   = 14,745), PTSD (European sample; N cases   = 2424, N controls   = 7113) and of subcortical brain structures (N = 13,171). SNP Effect Concordance Analysis (SECA) and Linkage Disequilibrium (LD) Score Regression were used to examine genetic pleiotropy, concordance, and genome-wide correlations respectively. SECAs conditional false discovery was used to identify specific risk variants associated with anxiety disorders or PTSD when conditioning on brain related traits., Results: For anxiety disorders, we found evidence of significant concordance between increased anxiety risk variants and variants associated with smaller amygdala volume. Further, by conditioning on brain volume GWAS, we identified novel variants that associate with smaller brain volumes and increase risk for disorders: rs56242606 was found to increase risk for anxiety disorders, while two variants (rs6470292 and rs683250) increase risk for PTSD, when conditioning on the GWAS of putamen volume., Limitations: Despite using the largest available GWAS summary statistics, the analyses were limited by sample size., Conclusions: These preliminary data indicate that there is genome wide concordance between genetic risk factors for anxiety disorders and those for smaller amygdala volume, which is consistent with research that supports the involvement of the amygdala in anxiety disorders. It is notable that a genetic variant that contributes to both reduced putamen volume and PTSD plays a key role in the glutamatergic system. Further work with GWAS summary statistics from larger samples, and a more extensive look at the genetics underlying brain circuits, is needed to fully delineate the genetic architecture of these disorders and their underlying neurocircuitry., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Background: Many studies have identified changes in the brain associated with obsessive-compulsive disorder (OCD), but few have examined the relationship between genetic determinants of OCD and brain variation.AimsWe present the first genome-wide investigation of overlapping genetic risk for OCD and genetic influences on subcortical brain structures., Method: Using single nucleotide polymorphism effect concordance analysis, we measured genetic overlap between the first genome-wide association study (GWAS) of OCD (1465 participants with OCD, 5557 controls) and recent GWASs of eight subcortical brain volumes (13 171 participants)., Results: We found evidence of significant positive concordance between OCD risk variants and variants associated with greater nucleus accumbens and putamen volumes. When conditioning OCD risk variants on brain volume, variants influencing putamen, amygdala and thalamus volumes were associated with risk for OCD., Conclusions: These results are consistent with current OCD neurocircuitry models. Further evidence will clarify the relationship between putamen volume and OCD risk, and the roles of the detected variants in this disorder.Declaration of interestThe authors have declared that no competing interests exist.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Background: Both genetic and environmental factors are known to affect body mass index (BMI), but detailed understanding of how their effects differ during childhood and adolescence is lacking., Objectives: We analyzed the genetic and environmental contributions to BMI variation from infancy to early adulthood and the ways they differ by sex and geographic regions representing high (North America and Australia), moderate (Europe), and low levels (East Asia) of obesogenic environments., Design: Data were available for 87,782 complete twin pairs from 0.5 to 19.5 y of age from 45 cohorts. Analyses were based on 383,092 BMI measurements. Variation in BMI was decomposed into genetic and environmental components through genetic structural equation modeling., Results: The variance of BMI increased from 5 y of age along with increasing mean BMI. The proportion of BMI variation explained by additive genetic factors was lowest at 4 y of age in boys (a(2) = 0.42) and girls (a(2) = 0.41) and then generally increased to 0.75 in both sexes at 19 y of age. This was because of a stronger influence of environmental factors shared by co-twins in midchildhood. After 15 y of age, the effect of shared environment was not observed. The sex-specific expression of genetic factors was seen in infancy but was most prominent at 13 y of age and older. The variance of BMI was highest in North America and Australia and lowest in East Asia, but the relative proportion of genetic variation to total variation remained roughly similar across different regions., Conclusions: Environmental factors shared by co-twins affect BMI in childhood, but little evidence for their contribution was found in late adolescence. Our results suggest that genetic factors play a major role in the variation of BMI in adolescence among populations of different ethnicities exposed to different environmental factors related to obesity., (© 2016 American Society for Nutrition.)

The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10(-33); 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.

A wealth of empirical evidence is accumulating on the genetic mediation of brain structure phenotypes. This comes from twin studies that assess heritability and genetic covariance between traits, candidate gene associations, and genome-wide association studies (GWAS) that can identify specific genetic variants. Here we review the major findings from each of these approaches and consider how they inform on the genetic architecture of brain structure. The findings from twin studies show there is a strong genetic influence (heritability) on brain structure, and overlap of genetic effects (pleiotropy) between structures, and between structure and cognition. However, there is also evidence for genetic specificity, with distinct genetic effects across some brain regions. Candidate gene associations show little convergence; most have been under powered to detect effect sizes of the magnitude now expected. GWAS have identified 19 genetic variants for brain structure, though no replicated associations account for more than 1% of the variance. Together these studies are revealing new insights into the genetic architecture of brain morphology. As the scope of inquiry broadens, including measures that capture the complexity of the brain, along with larger samples and new analyses, such as genome-wide common trait analysis (GCTA) and polygenic scores, which combine variant effects for a phenotype, as well as whole-genome sequencing, more genetic variants for brain structure will be identified. Increasingly, large-scale multi-site studies will facilitate this next wave of studies, and promise to enhance our understanding of the etiology of variation in brain morphology, as well as brain disorders.

Aberrant connectivity is implicated in many neurological and psychiatric disorders, including Alzheimer's disease and schizophrenia. However, other than a few disease-associated candidate genes, we know little about the degree to which genetics play a role in the brain networks; we know even less about specific genes that influence brain connections. Twin and family-based studies can generate estimates of overall genetic influences on a trait, but genome-wide association scans (GWASs) can screen the genome for specific variants influencing the brain or risk for disease. To identify the heritability of various brain connections, we scanned healthy young adult twins with high-field, high-angular resolution diffusion MRI. We adapted GWASs to screen the brain's connectivity pattern, allowing us to discover genetic variants that affect the human brain's wiring. The association of connectivity with the SPON1 variant at rs2618516 on chromosome 11 (11p15.2) reached connectome-wide, genome-wide significance after stringent statistical corrections were enforced, and it was replicated in an independent subsample. rs2618516 was shown to affect brain structure in an elderly population with varying degrees of dementia. Older people who carried the connectivity variant had significantly milder clinical dementia scores and lower risk of Alzheimer's disease. As a posthoc analysis, we conducted GWASs on several organizational and topological network measures derived from the matrices to discover variants in and around genes associated with autism (MACROD2), development (NEDD4), and mental retardation (UBE2A) significantly associated with connectivity. Connectome-wide, genome-wide screening offers substantial promise to discover genes affecting brain connectivity and risk for brain diseases.

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000.

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.

Genes in the TGF9 signaling pathway play important roles in the regulation of ovarian follicle growth and ovulation rate. Mutations in three genes in this pathway, growth differentiation factor 9 (GDF9), bone morphogenetic protein 15 (BMP15) and the bone morphogenetic protein receptor B 1 (BMPRB1), influence dizygotic (DZ) twinning rates in sheep. To date, only variants in GDF9 and BMP15, but not their receptors transforming growth factor ß receptor 1 (TGFBR1), bone morphogenetic protein receptor 2 (BMPR2) and BMPR1B, have been investigated with respect to their roles in human DZ twinning. We screened for rare and novel variants in TGFBR1, BMPR2 and BMPR1B in mothers of dizygotic twins (MODZT) from twin-dense families, and assessed association between genotyped and imputed variants and DZ twinning in another large sample of MODZT. Three novel variants were found: a deep intronic variant in BMPR2, and one intronic and one non-synonymous exonic variant in BMPRB1 which would result in the replacement of glutamine by glutamic acid at amino acid position 294 (p.Gln294Glu). None of these variants were predicted to have major impacts on gene function. However, the p.Gln294Glu variant changes the same amino acid as a sheep BMPR1B functional variant and may have functional consequences. Six BMPR1B variants were marginally associated with DZ twinning in the larger case-control sample, but these were no longer significant once multiple testing was taken into account. Our results suggest that variation in the TGF9 signaling pathway type II receptors has limited effects on DZ twinning rates in humans.

We conducted a genome-wide association study (GWAS) and a follow-up study of bipolar disorder (BD), a common neuropsychiatric disorder. In the GWAS, we investigated 499,494 autosomal and 12,484 X-chromosomal SNPs in 682 patients with BD and in 1300 controls. In the first follow-up step, we tested the most significant 48 SNPs in 1729 patients with BD and in 2313 controls. Eight SNPs showed nominally significant association with BD and were introduced to a meta-analysis of the GWAS and the first follow-up samples. Genetic variation in the neurocan gene (NCAN) showed genome-wide significant association with BD in 2411 patients and 3613 controls (rs1064395, p = 3.02 × 10(-8); odds ratio = 1.31). In a second follow-up step, we replicated this finding in independent samples of BD, totaling 6030 patients and 31,749 controls (p = 2.74 × 10(-4); odds ratio = 1.12). The combined analysis of all study samples yielded a p value of 2.14 × 10(-9) (odds ratio = 1.17). Our results provide evidence that rs1064395 is a common risk factor for BD. NCAN encodes neurocan, an extracellular matrix glycoprotein, which is thought to be involved in cell adhesion and migration. We found that expression in mice is localized within cortical and hippocampal areas. These areas are involved in cognition and emotion regulation and have previously been implicated in BD by neuropsychological, neuroimaging, and postmortem studies., (Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.)

The region containing ROBO1 (Chromosome 3p12.3) has been implicated as a susceptibility gene for reading disorder and language deficit by translocation and linkage data. No association studies have yet been reported supporting any candidate gene. Here we report the first association of this gene with language deficits, specifically with phonological buffer deficits (a phenotype implicated in language acquisition, Specific Language Impairment and Speech Sound Disorder) and dyslexia (reading and spelling ability traits) in an unselected sample of adolescent twins and their siblings. Family-based analyses were performed on 144 tag SNPs in ROBO1, typed in 538 families with up to five offspring and tested for association with a developmental marker of language impairment (phonological buffer capacity, assessed using non word repetition). A reading and spelling ability measure--based on validated measures of lexical processing (irregular word) and grapheme-phoneme decoding (pseudo word)--and measures of short-term and working memory were also analysed. Significant association for phonological buffer capacity was observed for 21 of 144 SNPs tested, peaking at 8.70 × 10(-05) and 9.30 × 10(-05) for SNPs rs6803202 and rs4535189 respectively for nonword repetition, values that survive correction for multiple testing. Twenty-two SNPs showed significant associations for verbal storage (forward digit span)--a trait linked to phonological span. By contrast, just 5 SNPs reached nominal significance for working-memory, not surviving correction, and, importantly, only one SNP in the 144 tested reached nominal significance (0.04) for association with reading and spelling ability. These results provide strong support for ROBO1 as a gene involved in a core trait underpinning language acquisition, with a specific function in supporting a short-term buffer for arbitrary phonological strings. These effects of ROBO1 appear to be unrelated to brain mechanisms underpinning reading ability, at least by adolescence. While replication will be critical, the present results strongly support ROBO1 as the first gene discovered to be associated with language deficits affecting normal variation in language ability. Its functional role in neuronal migration underlying bilateral symmetry and lateralization of neuronal function further suggests a role in the evolution of human language ability.

The perceived taste intensities of quinine HCl, caffeine, sucrose octaacetate (SOA) and propylthiouracil (PROP) solutions were examined in 1457 twins and their siblings. Previous heritability modeling of these bitter stimuli indicated a common genetic factor for quinine, caffeine and SOA (22-28%), as well as separate specific genetic factors for PROP (72%) and quinine (15%). To identify the genes involved, we performed a genome-wide association study with the same sample as the modeling analysis, genotyped for approximately 610,000 single-nucleotide polymorphisms (SNPs). For caffeine and SOA, no SNP association reached a genome-wide statistical criterion. For PROP, the peak association was within TAS2R38 (rs713598, A49P, P = 1.6 × 10(-104)), which accounted for 45.9% of the trait variance. For quinine, the peak association was centered in a region that contains bitter receptor as well as salivary protein genes and explained 5.8% of the trait variance (TAS2R19, rs10772420, R299C, P = 1.8 × 10(-15)). We confirmed this association in a replication sample of twins of similar ancestry (P = 0.00001). The specific genetic factor for the perceived intensity of PROP was identified as the gene previously implicated in this trait (TAS2R38). For quinine, one or more bitter receptor or salivary proline-rich protein genes on chromosome 12 have alleles which affect its perception but tight linkage among very similar genes precludes the identification of a single causal genetic variant.

Hair morphology is highly differentiated between populations and among people of European ancestry. Whereas hair morphology in East Asian populations has been studied extensively, relatively little is known about the genetics of this trait in Europeans. We performed a genome-wide association scan for hair morphology (straight, wavy, curly) in three Australian samples of European descent. All three samples showed evidence of association implicating the Trichohyalin gene (TCHH), which is expressed in the developing inner root sheath of the hair follicle, and explaining approximately 6% of variance (p=1.5x10(-31)). These variants are at their highest frequency in Northern Europeans, paralleling the distribution of the straight-hair EDAR variant in Asian populations.

Biochemical traits such as plasma alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma glutamyltransferase (GGT) and uric acid are associated with obesity, and with risk of cardiovascular disease, metabolic syndrome and diabetes. Each is subject to genetic influences, but little is known about changes in genetic and environmental influences on these traits over time. We investigated the contribution of genetic and environmental influences to variation in these biochemical traits in adolescent twins and their nontwin siblings from 965 twin families. Twins were studied at ages 12, 14 and 16 years. Multivariate genetic models that included effects of age and sex were fitted to determine whether the same or different genetic or environmental factors influence each trait at different ages. Results showed that the genetic factors influencing AST, ALT, GGT and uric acid change over time during adolescence, and that the magnitude of these effects differs between males and females. The nonshared environment effects were generally time specific. There are developmental changes in genes affecting these traits during adolescence.