Nonhuman primates (NHP) provide crucial biomedical model systems intermediate between rodents and humans. The vervet monkey (also called the African green monkey) is a widely used NHP model that has unique value for genetic and genomic investigations of traits relevant to human diseases. This article describes the phylogeny and population history of the vervet monkey and summarizes the use of both captive and wild vervet monkeys in biomedical research. It also discusses the effort of an international collaboration to develop the vervet monkey as the most comprehensively phenotypically and genomically characterized NHP, a process that will enable the scientific community to employ this model for systems biology investigations.
African green monkey; genetics; genomics; phenomics; simian immunodeficiency virus [SIV]; systems biology; transcriptomics; vervet
Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here, we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain providing biological plausibility for the findings. Many findings have the potential to provide entirely novel insights into aetiology, but associations at DRD2 and multiple genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that play important roles in immunity, providing support for the hypothesized link between the immune system and schizophrenia.
Although asthma is highly prevalent among certain Hispanic subgroups, genetic determinants of asthma and asthma‐related traits have not been conclusively identified in Hispanic populations. A study was undertaken to identify genomic regions containing susceptibility loci for pulmonary function and bronchodilator responsiveness (BDR) in Costa Ricans.
Eight extended pedigrees were ascertained through schoolchildren with asthma in the Central Valley of Costa Rica. Short tandem repeat (STR) markers were genotyped throughout the genome at an average spacing of 8.2 cM. Multipoint variance component linkage analyses of forced expiratory volume in 1 second (FEV1) and FEV1/ forced vital capacity (FVC; both pre‐bronchodilator and post‐bronchodilator) and BDR were performed in these eight families (pre‐bronchodilator spirometry, n = 640; post‐bronchodilator spirometry and BDR, n = 624). Nine additional STR markers were genotyped on chromosome 7. Secondary analyses were repeated after stratification by cigarette smoking.
Among all subjects, the highest logarithm of the odds of linkage (LOD) score for FEV1 (post‐bronchodilator) was found on chromosome 7q34–35 (LOD = 2.45, including the additional markers). The highest LOD scores for FEV1/FVC (pre‐bronchodilator) and BDR were found on chromosomes 2q (LOD = 1.53) and 9p (LOD = 1.53), respectively. Among former and current smokers there was near‐significant evidence of linkage to FEV1/FVC (post‐bronchodilator) on chromosome 5p (LOD = 3.27) and suggestive evidence of linkage to FEV1 on chromosomes 3q (pre‐bronchodilator, LOD = 2.74) and 4q (post‐bronchodilator, LOD = 2.66).
In eight families of children with asthma in Costa Rica, there is suggestive evidence of linkage to FEV1 on chromosome 7q34–35. In these families, FEV1/FVC may be influenced by an interaction between cigarette smoking and a locus (loci) on chromosome 5p.
We reported previously a significant linkage signal between psychotic bipolar disorder (BP) and microsatellite markers on chromosome 5q31–34 in the National Institute of Mental Health Bipolar Genetics Initiative (NIMH-BPGI) data set, Wave 1. In an attempt to fine-map this linkage signal we genotyped 1,134 single nucleotide polymorphisms (SNPs) under the linkage peak in 23 informative families (131 individuals) with evidence of linkage. We tested family based association in the presence of linkage with the computer software package FBAT. The most significant association in these families was with a SNP in the second intron of GRIA1 (α-amino-3-hydroxy-5-methyl-4-isoxazole proprionic acid (AMPA) subunit 1 receptor gene) (rs490922, Z-score = 3.3, P= 0.001). The analysis of 37 additional families with psychotic BP from NIMH-BPGI data sets, Waves 2, 3, and 4 revealed a signal at a SNP in intron 5 of the GRIA1 gene (rs4385264, Z-score = 3.2, P-value = 0.002). A combined analysis of all 60 families continued to support evidence for association of GRIA1 with psychotic BP; however, individual SNPs could not be replicated across datasets. The AMPA1 receptor has been shown to influence cognitive function, such as working memory and reward learning. Our findings suggest that variations in this receptor may contribute to the pathophysiology of BP with psychotic features in some families.
genetic; linkage; association; mood disorder; glutamate receptor
Elucidating the molecular mechanisms underlying quantitative neurocognitive phenotypes will further our understanding of the brain’s structural and functional architecture and advance the diagnosis and treatment of the psychiatric disorders that these traits underlie. Although many neurocognitive traits are highly heritable, little progress has been made in identifying genetic variants unequivocally associated with these phenotypes. A major obstacle to such progress is the difficulty in identifying heritable neurocognitive measures which are precisely defined, systematically assessed and represent unambiguous mental constructs, yet are amenable to the high-throughput phenotyping necessary to obtain adequate power for genetic association studies. In this perspective we compare the current status of genetic investigations of neurocognitive phenotypes to that of other categories of biomedically relevant traits and suggest strategies for genetically dissecting traits that may underlie disorders of brain and behavior.
Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5–5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p<5×10−8) including splice variants in LPA that lowered plasma lipoprotein(a) levels (P = 1.5×10−117). Through accessing the national medical records of these participants, we evaluate the LPA finding via Mendelian randomization and confirm that these splice variants confer protection from cardiovascular disease (OR = 0.84, P = 3×10−4), demonstrating for the first time the correlation between very low levels of LPA in humans with potential therapeutic implications for cardiovascular diseases. More generally, this study articulates substantial advantages for studying the role of rare variation in complex phenotypes in founder populations like the Finns and by combining a unique population genetic history with data from large population cohorts and centralized research access to National Health Registers.
We explored the coding regions of 3,000 Finnish individuals with 3,000 non-Finnish Europeans (NFEs) using whole-exome sequence data, in order to understand how an individual from a bottlenecked population might differ from an individual from an out-bred population. We provide empirical evidence that there are more rare and low-frequency deleterious alleles in Finns compared to NFEs, such that an average Finn has almost twice as many low-frequency complete knockouts of a gene. As such, we hypothesized that some of these low-frequency loss-of-function variants might have important medical consequences in humans and genotyped 83 of these variants in 36,000 Finns. In doing so, we discovered that completely knocking out the TSFM gene might result in inviability or a very severe phenotype in humans and that knocking out the LPA gene might confer protection against coronary heart diseases, suggesting that LPA is likely to be a good potential therapeutic target.
Low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides, and total cholesterol are heritable, modifiable, risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,578 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5×10−8, including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian, and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipids are often associated with cardiovascular and metabolic traits including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio, and body mass index. Our results illustrate the value of genetic data from individuals of diverse ancestries and provide insights into biological mechanisms regulating blood lipids to guide future genetic, biological, and therapeutic research.
Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiologic studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P<5×10−8 for each) to examine the role of triglycerides on risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglycerides, and show that the direction and magnitude of both are factors in determining CAD risk. Second, we consider loci with only a strong magnitude of association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol, a polymorphism's strength of effect on triglycerides is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.
Implicating particular genes in the generation of complex brain and behavior phenotypes requires multiple lines of evidence. The rarity of most high impact genetic variants typically precludes the possibility of accruing statistical evidence that they are associated with a given trait. We show here that the enrichment of a rare Chromosome 22q11.22 deletion in a recently expanded Northern Finnish sub-isolate enables the detection of association between TOP3β and both schizophrenia and cognitive impairment. Biochemical analysis of TOP3β revealed that this topoisomerase is a component of cytosolic messenger ribonucleoproteins (mRNPs) and is catalytically active on RNA. The recruitment of TOP3β to mRNPs was independent of RNA cis-elements and was coupled to the co-recruitment of FMRP, the disease gene product in fragile X mental retardation syndrome (FXS). Thus, we uncover a novel role for TOP3β in mRNA metabolism and provide several lines of evidence implicating it in neurodevelopmental disorders.
The aim of this study was to examine the prevalence and clinical correlates of explosive outbursts in two large samples of individuals with TS, including one collected primarily from non-clinical sources. Participants included 218 TS-affected individuals who were part of a genetic study (N=104 from Costa Rica (CR) and N=114 from the US). The relationship between explosive outbursts and comorbid attention deficit hyperactivity disorder (ADHD), obsessive compulsive disorder (OCD), tic severity, and prenatal and perinatal complications were examined using regression analyses. Twenty percent of participants had explosive outbursts, with no significant differences in prevalence between the CR (non-clinical) and the US (primarily clinical) samples. In the overall sample, ADHD, greater tic severity, and lower age of tic onset were strongly associated with explosive outbursts. ADHD, prenatal exposure to tobacco, and male gender were significantly associated with explosive outbursts in the US sample. Lower age of onset and greater severity of tics were significantly associated with explosive outbursts in the CR sample. This study confirms previous studies that suggest that clinically significant explosive outbursts are common in TS and associated with ADHD and tic severity. An additional potential risk factor, prenatal exposure to tobacco, was also identified.
impulse control; tic disorders; prenatal maternal smoking; rage; co-morbidity
Genome-wide association studies (GWAS) have identified >500 common variants associated with quantitative metabolic traits, but in aggregate such variants explain at most 20–30% of the heritable component of population variation in these traits. To further investigate the impact of genotypic variation on metabolic traits, we conducted re-sequencing studies in >6,000 members of a Finnish population cohort (The Northern Finland Birth Cohort of 1966 [NFBC]) and a type 2 diabetes case-control sample (The Finland-United States Investigation of NIDDM Genetics [FUSION] study). By sequencing the coding sequence and 5′ and 3′ untranslated regions of 78 genes at 17 GWAS loci associated with one or more of six metabolic traits (serum levels of fasting HDL-C, LDL-C, total cholesterol, triglycerides, plasma glucose, and insulin), and conducting both single-variant and gene-level association tests, we obtained a more complete understanding of phenotype-genotype associations at eight of these loci. At all eight of these loci, the identification of new associations provides significant evidence for multiple genetic signals to one or more phenotypes, and at two loci, in the genes ABCA1 and CETP, we found significant gene-level evidence of association to non-synonymous variants with MAF<1%. Additionally, two potentially deleterious variants that demonstrated significant associations (rs138726309, a missense variant in G6PC2, and rs28933094, a missense variant in LIPC) were considerably more common in these Finnish samples than in European reference populations, supporting our prior hypothesis that deleterious variants could attain high frequencies in this isolated population, likely due to the effects of population bottlenecks. Our results highlight the value of large, well-phenotyped samples for rare-variant association analysis, and the challenge of evaluating the phenotypic impact of such variants.
Abnormal serum levels of various metabolites, including measures relevant to cholesterol, other fats, and sugars, are known to be risk factors for cardiovascular disease and type 2 diabetes. Identification of the genes that play a role in generating such abnormalities could advance the development of new treatment and prevention strategies for these disorders. Investigations of common genetic variants carried out in large sets of research subjects have successfully pinpointed such genes within many regions of the human genome. However, these studies often have not led to the identification of the specific genetic variations affecting metabolic traits. To attempt to detect such causal variations, we sequenced genes in 17 genomic regions implicated in metabolic traits in >6,000 people from Finland. By conducting statistical analyses relating specific variations (individually and grouped by gene) to the measures for these metabolic traits observed in the study subjects, we added to our understanding of how genotypes affect these traits. Our findings support a long-held hypothesis that the unique history of the Finnish population provides important advantages for analyzing the relationship between genetic variations and biomedically important traits.
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.
Genetics; MRI; GWAS; Consortium; Meta-analysis; Multi-site
The direct estimation of heritability from genome-wide common variant data as implemented in the program Genome-wide Complex Trait Analysis (GCTA) has provided a means to quantify heritability attributable to all interrogated variants. We have quantified the variance in liability to disease explained by all SNPs for two phenotypically-related neurobehavioral disorders, obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS), using GCTA. Our analysis yielded a heritability point estimate of 0.58 (se = 0.09, p = 5.64e-12) for TS, and 0.37 (se = 0.07, p = 1.5e-07) for OCD. In addition, we conducted multiple genomic partitioning analyses to identify genomic elements that concentrate this heritability. We examined genomic architectures of TS and OCD by chromosome, MAF bin, and functional annotations. In addition, we assessed heritability for early onset and adult onset OCD. Among other notable results, we found that SNPs with a minor allele frequency of less than 5% accounted for 21% of the TS heritability and 0% of the OCD heritability. Additionally, we identified a significant contribution to TS and OCD heritability by variants significantly associated with gene expression in two regions of the brain (parietal cortex and cerebellum) for which we had available expression quantitative trait loci (eQTLs). Finally we analyzed the genetic correlation between TS and OCD, revealing a genetic correlation of 0.41 (se = 0.15, p = 0.002). These results are very close to previous heritability estimates for TS and OCD based on twin and family studies, suggesting that very little, if any, heritability is truly missing (i.e., unassayed) from TS and OCD GWAS studies of common variation. The results also indicate that there is some genetic overlap between these two phenotypically-related neuropsychiatric disorders, but suggest that the two disorders have distinct genetic architectures.
Family and twin studies have shown that genetic risk factors are important in the development of Tourette Syndrome (TS) and obsessive compulsive disorder (OCD). However, efforts to identify the individual genetic risk factors involved in these two neuropsychiatric disorders have been largely unsuccessful. One possible explanation for this is that many genetic variations scattered throughout the genome each contribute a small amount to the overall risk. For TS and OCD, the genetic architecture (characterized by the number, frequency, and distribution of genetic risk factors) is presently unknown. This study examined the genetic architecture of TS and OCD in a variety of ways. We found that rare genetic changes account for more genetic risk in TS than in OCD; certain chromosomes contribute to OCD risk more than others; and variants that influence the level of genes expressed in two regions of the brain can account for a significant amount of risk for both TS and OCD. Results from this study might help in determining where, and what kind of variants are individual risk factors for TS and OCD and where they might be located in the human genome.
Non-human primates provide genetic model systems biologically intermediate between humans and other mammalian model organisms. Populations of Caribbean vervet monkeys (Chlorocebus aethiops sabaeus) are genetically homogeneous and large enough to permit well-powered genetic mapping studies of quantitative traits relevant to human health, including expression quantitative trait loci (eQTL). Previous transcriptome-wide investigation in an extended vervet pedigree identified 29 heritable transcripts for which levels of expression in peripheral blood correlate strongly with expression levels in the brain. Quantitative trait linkage analysis using 261 microsatellite markers identified significant (n = 8) and suggestive (n = 4) linkages for 12 of these transcripts, including both cis- and trans-eQTL. Seven transcripts, located on different chromosomes, showed maximum linkage to markers in a single region of vervet chromosome 9; this observation suggests the possibility of a master trans-regulator locus in this region. For one cis-eQTL (at B3GALTL, beta-1,3-glucosyltransferase), we conducted follow-up single nucleotide polymorphism genotyping and fine-scale association analysis in a sample of unrelated Caribbean vervets, localizing this eQTL to a region of <200 kb. These results suggest the value of pedigree and population samples of the Caribbean vervet for linkage and association mapping studies of quantitative traits. The imminent whole genome sequencing of many of these vervet samples will enhance the power of such investigations by providing a comprehensive catalog of genetic variation.
Identifying genetic variants influencing human brain structures may reveal new biological mechanisms underlying cognition and neuropsychiatric illness. The volume of the hippocampus is a biomarker of incipient Alzheimer’s disease1,2 and is reduced in schizophrenia3, major depression4 and mesial temporal lobe epilepsy5. Whereas many brain imaging phenotypes are highly heritable6,7, identifying and replicating genetic influences has been difficult, as small effects and the high costs of magnetic resonance imaging (MRI) have led to underpowered studies. Here we report genome-wide association meta-analyses and replication for mean bilateral hippocampal, total brain and intracranial volumes from a large multinational consortium. The intergenic variant rs7294919 was associated with hippocampal volume (12q24.22; N = 21,151; P = 6.70 × 10−16) and the expression levels of the positional candidate gene TESC in brain tissue. Additionally, rs10784502, located within HMGA2, was associated with intracranial volume (12q14.3; N = 15,782; P = 1.12 × 10−12). We also identified a suggestive association with total brain volume at rs10494373 within DDR2 (1q23.3; N = 6,500; P = 5.81 × 10−7).
The peopling of the Americas has been the subject of extensive genetic, archaeological and linguistic research; however, central questions remain unresolved1–5. One contentious issue is whether the settlement occurred via a single6–8 or multiple streams of migration from Siberia9–15. The pattern of dispersals within the Americas is also poorly understood. To address these questions at higher resolution than was previously possible, we assembled data from 52 Native American and 17 Siberian groups genotyped at 364,470 single nucleotide polymorphisms. We show that Native Americans descend from at least three streams of Asian gene flow. Most descend entirely from a single ancestral population that we call “First American”. However, speakers of Eskimo-Aleut languages from the Arctic inherit almost half their ancestry from a second stream of Asian gene flow, and the Na-Dene-speaking Chipewyan from Canada inherit roughly one-tenth of their ancestry from a third stream. We show that the initial peopling followed a southward expansion facilitated by the coast, with sequential population splits and little gene flow after divergence, especially in South America. A major exception is in Chibchan-speakers on both sides of the Panama Isthmus, who have ancestry from both North and South America.
Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.
Tourette syndrome (TS) is a neuropsychiatric disorder with a strong genetic component. However, the genetic architecture of TS remains uncertain. Copy number variation (CNV) has been shown to contribute to the genetic make-up of several neurodevelopmental conditions, including schizophrenia and autism. Here we describe CNV calls using SNP chip genotype data from an initial sample of 210 TS cases and 285 controls ascertained in two Latin American populations. After extensive quality control, we found that cases (N = 179) have a significant excess (P = 0.006) of large CNV (>500 kb) calls compared to controls (N = 234). Amongst 24 large CNVs seen only in the cases, we observed four duplications of the COL8A1 gene region. We also found two cases with ∼400kb deletions involving NRXN1, a gene previously implicated in neurodevelopmental disorders, including TS. Follow-up using multiplex ligation-dependent probe amplification (and including 53 more TS cases) validated the CNV calls and identified additional patients with rearrangements in COL8A1 and NRXN1, but none in controls. Examination of available parents indicates that two out of three NRXN1 deletions detected in the TS cases are de-novo mutations. Our results are consistent with the proposal that rare CNVs play a role in TS aetiology and suggest a possible role for rearrangements in the COL8A1 and NRXN1 gene regions.
Investigation of the environmental influences on human behavioral phenotypes is important for our understanding of the causation of psychiatric disorders. However, there are complexities associated with the assessment of environmental influences on behavior.
We conducted a series of analyses using a prospective, longitudinal study of a nationally representative birth cohort from Finland (the Northern Finland 1966 Birth Cohort). Participants included a total of 3,761 male and female cohort members who were living in Finland at the age of 16 years and who had complete temperament scores. Our initial analyses (Wessman et al., in press) provide evidence in support of four stable and robust temperament clusters. Using these temperament clusters, as well as independent temperament dimensions for comparison, we conducted a data-driven analysis to assess the influence of a broad set of life course measures, assessed pre-natally, in infancy, and during adolescence, on adult temperament.
Measures of early environment, neurobehavioral development, and adolescent behavior significantly predict adult temperament, classified by both cluster membership and temperament dimensions. Specifically, our results suggest that a relatively consistent set of life course measures are associated with adult temperament profiles, including maternal education, characteristics of the family’s location and residence, adolescent academic performance, and adolescent smoking.
Our finding that a consistent set of life course measures predict temperament clusters indicate that these clusters represent distinct developmental temperament trajectories and that information about a subset of life course measures has implications for adult health outcomes.
Phenotype mining is a novel approach for elucidating the genetic basis of complex phenotypic variation. It involves a search of rich phenotype databases for measures correlated with genetic variation, as identified in genome-wide genotyping or sequencing studies. An initial implementation of phenotype mining in a prospective unselected population cohort, the Northern Finland 1966 Birth Cohort (NFBC1966), identifies neurodevelopment-related traits—intellectual deficits, poor school performance and hearing abnormalities—which are more frequent among individuals with large (>500 kb) deletions than among other cohort members. Observation of extensive shared single nucleotide polymorphism haplotypes around deletions suggests an opportunity to expand phenotype mining from cohort samples to the populations from which they derive.
Vervet monkeys are a frequently studied animal model in neuroscience research. Although equally distantly related to humans, the ancestors of vervets diverged from those of macaques and baboons more than eleven million years ago, antedating the divergence of the ancestors of humans, chimpanzees and gorillas. To facilitate anatomic localization in the vervet brain, two linked on-line electronic atlases are described, one based on registered MRI scans from hundreds of vervets (http://www.loni.ucla.edu/Research/Atlases/Data/vervet/vervetmratlas/vervetmratlas.html) and the other based on a high-resolution cryomacrotome study of a single vervet (http://www.loni.ucla.edu/Research/Atlases/Data/vervet/vervetatlas/vervetatlas.html). The averaged MRI atlas is also available as a volume in Neuroimaging Informatics Technology Initiative format. In the cryomacrotome atlas, various sulcal and subcortical structures have been anatomically labeled and surface rendered views are provided along the primary planes of section. Both atlases simultaneously provide views in all three primary planes of section, rapid navigation by clicking on the displayed images, and stereotaxic coordinates in the averaged MRI atlas space. Despite the extended time period since their divergence, the major sulcal and subcortical landmarks in vervets are highly conserved relative to those described in macaques.
brain atlas; vervet; Old World monkey; Chlorocebus aethiops; magnetic resonance imaging; cryomacrotome
Asymmetry is a prominent feature of human brains with important functional consequences. Many asymmetric traits show population bias, but little is known about the genetic and environmental sources contributing to inter-individual variance. Anatomic asymmetry has been observed in Old World monkeys, but the evidence for the direction and extent of asymmetry is equivocal and only one study has estimated the genetic contributions to inter-individual variance. In this study we characterize a range of qualitative and quantitative asymmetry measures in structural brain MRIs acquired from an extended pedigree of Old World vervet monkeys (n = 357), and implement variance component methods to estimate the proportion of trait variance attributable to genetic and environmental sources. Four of six asymmetry measures show pedigree-level bias and one of the traits has a significant heritability estimate of about 30%. We also found that environmental variables more significantly influence the width of the right compared to the left prefrontal lobe.
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene–environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10−9. There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
Circulating serum lipids contribute greatly to the global health by affecting the risk for cardiovascular diseases. Serum lipid levels are partly inherited, and already 95 loci affecting high- and low-density lipoprotein cholesterol, total cholesterol, and triglycerides have been found. Serum lipids are also known to be affected by multiple epidemiological risk factors like body composition, lifestyle, and sex. It has been hypothesized that there are loci modifying the effects between risk factors and serum lipids, but to date only candidate gene studies for interactions have been reported. We conducted a genome-wide screen with meta-analysis approach to identify loci having interactions with epidemiological risk factors on serum lipids with over 30,000 population-based samples. When combining results from our initial datasets and 8 additional replication cohorts (maximum N = 17,102), we found a genome-wide significant locus in chromosome 4p15 with a joint P-value of 4.79×10−9 modifying the effect of waist-to-hip ratio on total cholesterol. In the area surrounding this genetic variant, there were two genes having association between the genotypes and the gene expression in adipose tissue, and we also found enrichment of association in genes belonging to lipid metabolism related functions.
We carried out a genome-wide association study of hemoglobin levels in 16,001 individuals of European and Indian Asian ancestry. The most closely associated SNP (rs855791) results in nonsynonymous (V736A) change in the serine protease domain of TMPRSS6 and a blood hemoglobin concentration 0.13 (95% CI 0.09–0.17) g/dl lower per copy of allele A (P = 1.6 × 10−13). Our findings suggest that TMPRSS6, a regulator of hepcidin synthesis and iron handling, is crucial in hemoglobin level maintenance.
Two independent lines of evidence support the localization of a schizophrenia susceptibility locus to the proximal long arm of chromosome 5. A partial trisomy of chromosome 5 (5q11.2–q13.3) cosegregates with the disorder in a Canadian family of Chinese descent, and DNA markers from proximal 5q cosegregate with schizophrenia (plus related disorders) in families of British and Icelandic descent. We constructed a human:hamster hybrid cell line (HHW 1064) whose only human complement is a chromosome 5 that is missing the trisomic region associated with schizophrenia. In combination with a “matched” cell hybrid (HHW 105) containing an intact chromosome 5, we physically mapped DNA markers relative to the trisomy. “Schizophrenia-linked” DNA markers p105–153Ra (D5S39) and p105-599Ha (D5S76) map within the trisomy and proximal to the 5q11.2 breakpoint, respectively. The hybrid cell lines HHW 105 and HHW 1064 together provide a means to identify and generate syntenic DNA markers to further investigate the location of a schizophrenia locus.
PMID: 2591972 CAMSID: cams1865