Brain charts for the human lifespan.

Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data ( http://www.brainchart.io/ ). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Obesity and obesogenic growth are both highly heritable and modified by diet in a nonhuman primate model, the African green monkey (Chlorocebus aethiops sabaeus).

OBJECTIVE: In humans, the ontogeny of obesity throughout the life course and the genetics underlying it has been historically difficult to study. We compared, in a non-human primate model, the lifelong growth trajectories of obese and non-obese adults to assess the heritability of and map potential genomic regions implicated in growth and obesity. STUDY POPULATION: A total of 905 African green monkeys, or vervets (Chlorocebus aethiops sabaeus) (472 females, 433 males) from a pedigreed captive colony. METHODS: We measured fasted body weight (BW), crown-to-rump length (CRL), body-mass index (BMI) and waist circumference (WC) from 2000 to 2015. We used a longitudinal clustering algorithm to detect obesogenic growth, and logistic growth curves implemented in nonlinear mixed effects models to estimate three growth parameters. We used maximum likelihood variance decomposition methods to estimate the genetic contributions to obesity-related traits and growth parameters, including a test for the effects of a calorie-restricted dietary intervention. We used multipoint linkage analysis to map implicated genomic regions. RESULTS: All measurements were significantly influenced by sex, and with the exception of WC, also influenced by maternal and post-natal diet. Chronic obesity outcomes were significantly associated with a pattern of extended growth duration with slow growth rates for BW. After accounting for environmental influences, all measurements were found to have a significant genetic component to variability. Linkage analysis revealed several regions suggested to be linked to obesity-related traits that are also implicated in human obesity and metabolic disorders. CONCLUSIONS: As in humans, growth patterns in vervets have a significant impact on adult obesity and are largely under genetic control with some evidence for maternal and dietary programming. These results largely mirror findings from human research, but reflect shorter developmental periods, suggesting that the vervet offers a strong genetic model for elucidating the ontogeny of human obesity.

The lipidome in major depressive disorder: Shared genetic influence for ether-phosphatidylcholines, a plasma-based phenotype related to inflammation, and disease risk.

BACKGROUND: The lipidome is rapidly garnering interest in the field of psychiatry. Recent studies have implicated lipidomic changes across numerous psychiatric disorders. In particular, there is growing evidence that the concentrations of several classes of lipids are altered in those diagnosed with MDD. However, for lipidomic abnormalities to be considered potential treatment targets for MDD (rather than secondary manifestations of the disease), a shared etiology between lipid concentrations and MDD should be demonstrated. METHODS: In a sample of 567 individuals from 37 extended pedigrees (average size 13.57 people, range=3-80), we used mass spectrometry lipidomic measures to evaluate the genetic overlap between twenty-three biologically distinct lipid classes and a dimensional scale of MDD. RESULTS: We found that the lipid class with the largest endophenotype ranking value (ERV, a standardized parametric measure of pleiotropy) were ether-phosphodatidylcholines (alkylphosphatidylcholine, PC(O) and alkenylphosphatidylcholine, PC(P) subclasses). Furthermore, we examined the cluster structure of the twenty-five species within the top-ranked lipid class, and the relationship of those clusters with MDD. This analysis revealed that species containing arachidonic acid generally exhibited the greatest degree of genetic overlap with MDD. CONCLUSIONS: This study is the first to demonstrate a shared genetic etiology between MDD and ether-phosphatidylcholine species containing arachidonic acid, an omega-6 fatty acid that is a precursor to inflammatory mediators, such as prostaglandins. The study highlights the potential utility of the well-characterized linoleic/arachidonic acid inflammation pathway as a diagnostic marker and/or treatment target for MDD.

Molecular Profiling of Human Induced Pluripotent Stem Cell-Derived Hypothalamic Neurones Provides Developmental Insights into Genetic Loci for Body Weight Regulation.

Recent data suggest that common genetic risks for metabolic disorders such as obesity may be human-specific and exert effects via the central nervous system. To overcome the limitation of human tissue access for study, we have generated induced human pluripotent stem cell (hiPSC)-derived neuronal cultures that recapture many features of hypothalamic neurones within the arcuate nucleus. In the present study, we have comprehensively characterised this model across development, benchmarked these neurones to in vivo events, and demonstrate a link between obesity risk variants and hypothalamic development. The dynamic transcriptome across neuronal maturation was examined using microarray and RNA sequencing methods at nine time points. K-means clustering of the longitudinal data was conducted to identify co-regulation and microRNA control of biological processes. The transcriptomes were compared with those of 103 samples from 13 brain regions reported in the Genotype-Tissue Expression database (GTEx) using principal components analysis. Genes with proximity to body mass index (BMI)-associated genetic variants were mapped to the developmentally expressed genesets, and enrichment significance was assessed with Fisher's exact test. The human neuronal cultures have a transcriptional and physiological profile of neuropeptide Y/agouti-related peptide arcuate nucleus neurones. The neuronal transcriptomes were highly correlated with adult hypothalamus compared to any other brain region from the GTEx. Also, approximately 25% of the transcripts showed substantial changes in expression across neuronal development and potential co-regulation of biological processes that mirror neuronal development in vivo. These developmentally expressed genes were significantly enriched for genes in proximity to BMI-associated variants. We confirmed the utility of this in vitro human model for studying the development of key hypothalamic neurones involved in energy balance and show that genes at loci associated with body weight regulation may share a pattern of developmental regulation. These data support the need to investigate early development to elucidate the human-specific central nervous system pathophysiology underlying obesity susceptibility.

Genome-wide significant loci for addiction and anxiety.

BACKGROUND: Psychiatric comorbidity is common among individuals with addictive disorders, with patients frequently suffering from anxiety disorders. While the genetic architecture of comorbid addictive and anxiety disorders remains unclear, elucidating the genes involved could provide important insights into the underlying etiology. METHODS: Here we examine a sample of 1284 Mexican-Americans from randomly selected extended pedigrees. Variance decomposition methods were used to examine the role of genetics in addiction phenotypes (lifetime history of alcohol dependence, drug dependence or chronic smoking) and various forms of clinically relevant anxiety. Genome-wide univariate and bivariate linkage scans were conducted to localize the chromosomal regions influencing these traits. RESULTS: Addiction phenotypes and anxiety were shown to be heritable and univariate genome-wide linkage scans revealed significant quantitative trait loci for drug dependence (14q13.2-q21.2, LOD=3.322) and a broad anxiety phenotype (12q24.32-q24.33, LOD=2.918). Significant positive genetic correlations were observed between anxiety and each of the addiction subtypes (ρg=0.550-0.655) and further investigation with bivariate linkage analyses identified significant pleiotropic signals for alcohol dependence-anxiety (9q33.1-q33.2, LOD=3.054) and drug dependence-anxiety (18p11.23-p11.22, LOD=3.425). CONCLUSIONS: This study confirms the shared genetic underpinnings of addiction and anxiety and identifies genomic loci involved in the etiology of these comorbid disorders. The linkage signal for anxiety on 12q24 spans the location of TMEM132D, an emerging gene of interest from previous GWAS of anxiety traits, whilst the bivariate linkage signal identified for anxiety-alcohol on 9q33 peak coincides with a region where rare CNVs have been associated with psychiatric disorders. Other signals identified implicate novel regions of the genome in addiction genetics.

Genome-wide association studies suggest sex-specific loci associated with abdominal and visceral fat.

BACKGROUND: To identify loci associated with abdominal fat and replicate prior findings, we performed genome-wide association (GWA) studies of abdominal fat traits: subcutaneous adipose tissue (SAT); visceral adipose tissue (VAT); total adipose tissue (TAT) and visceral to subcutaneous adipose tissue ratio (VSR). SUBJECTS AND METHODS: Sex-combined and sex-stratified analyses were performed on each trait with (TRAIT-BMI) or without (TRAIT) adjustment for body mass index (BMI), and cohort-specific results were combined via a fixed effects meta-analysis. A total of 2513 subjects of European descent were available for the discovery phase. For replication, 2171 European Americans and 772 African Americans were available. RESULTS: A total of 52 single-nucleotide polymorphisms (SNPs) encompassing 7 loci showed suggestive evidence of association (P<1.0 × 10(-6)) with abdominal fat in the sex-combined analyses. The strongest evidence was found on chromosome 7p14.3 between a SNP near BBS9 gene and VAT (rs12374818; P=1.10 × 10(-7)), an association that was replicated (P=0.02). For the BMI-adjusted trait, the strongest evidence of association was found between a SNP near CYCSP30 and VAT-BMI (rs10506943; P=2.42 × 10(-7)). Our sex-specific analyses identified one genome-wide significant (P<5.0 × 10(-8)) locus for SAT in women with 11 SNPs encompassing the MLLT10, DNAJC1 and EBLN1 genes on chromosome 10p12.31 (P=3.97 × 10(-8) to 1.13 × 10(-8)). The THNSL2 gene previously associated with VAT in women was also replicated (P=0.006). The six gene/loci showing the strongest evidence of association with VAT or VAT-BMI were interrogated for their functional links with obesity and inflammation using the Biograph knowledge-mining software. Genes showing the closest functional links with obesity and inflammation were ADCY8 and KCNK9, respectively. CONCLUSIONS: Our results provide evidence for new loci influencing abdominal visceral (BBS9, ADCY8, KCNK9) and subcutaneous (MLLT10/DNAJC1/EBLN1) fat, and confirmed a locus (THNSL2) previously reported to be associated with abdominal fat in women.

Serum bilirubin concentration is modified by UGT1A1 haplotypes and influences risk of type-2 diabetes in the Norfolk Island genetic isolate.

BACKGROUND: Located in the Pacific Ocean between Australia and New Zealand, the unique population isolate of Norfolk Island has been shown to exhibit increased prevalence of metabolic disorders (type-2 diabetes, cardiovascular disease) compared to mainland Australia. We investigated this well-established genetic isolate, utilising its unique genomic structure to increase the ability to detect related genetic markers. A pedigree-based genome-wide association study of 16 routinely collected blood-based clinical traits in 382 Norfolk Island individuals was performed. RESULTS: A striking association peak was located at chromosome 2q37.1 for both total bilirubin and direct bilirubin, with 29 SNPs reaching statistical significance (P < 1.84 × 10(-7)). Strong linkage disequilibrium was observed across a 200 kb region spanning the UDP-glucuronosyltransferase family, including UGT1A1, an enzyme known to metabolise bilirubin. Given the epidemiological literature suggesting negative association between CVD-risk and serum bilirubin we further explored potential associations using stepwise multivariate regression, revealing significant association between direct bilirubin concentration and type-2 diabetes risk. In the Norfolk Island cohort increased direct bilirubin was associated with a 28% reduction in type-2 diabetes risk (OR: 0.72, 95% CI: 0.57-0.91, P = 0.005). When adjusted for genotypic effects the overall model was validated, with the adjusted model predicting a 30% reduction in type-2 diabetes risk with increasing direct bilirubin concentrations (OR: 0.70, 95% CI: 0.53-0.89, P = 0.0001). CONCLUSIONS: In summary, a pedigree-based GWAS of blood-based clinical traits in the Norfolk Island population has identified variants within the UDPGT family directly associated with serum bilirubin levels, which is in turn implicated with reduced risk of developing type-2 diabetes within this population.

Axial quantitative ultrasound assessment of pediatric bone quality in eastern Nepal.

UNLABELLED: This study presents quantitative ultrasonography (QUS) bone quality data for an underrepresented, south Asian pediatric population from Nepal. Data were collected as part of a longitudinal study of growth and development. This study offers normative data and documents the effect of stunting, wasting, and underweight on the bone properties measured by QUS. INTRODUCTION: The purpose of this study was to (1) examine the bone quality of a rural, non-Western pediatric population using QUS, (2) explore variation in the trajectory of bone quality development between males and females, and (3) examine the impact of growth disruption(s) on bone quality. METHODS: A cross-sectional study of 860 children and adolescents aged 5-18 years from the Jirel ethnic group in eastern Nepal was performed. The Sunlight Omnisense 7000P was used to assess bone quality of the distal 1/3 radius and midshaft tibia. WHO reference standards were used to assess growth disruptions of height, weight, and BMI. RESULTS: QUS bone quality data for an underrepresented, non-Western pediatric population are presented for the radius and tibia. A sizable portion of the study participants were classified as stunted, wasted, and/or underweight. Despite this prevalence of growth disruption in the study sample, bone quality data conform to other documented populations with less growth disruption. Thus, this study offers normative data and documents the minimal effect of stunting, wasting, and underweight on the bone properties measured by QUS. CONCLUSIONS: Non-Western pediatric populations are significantly underserved with regard to simple, non-invasive screening tools that may help identify developmental disorders and assess bone health. The children and adolescents examined here represent normal growth and development for an underrepresented south Asian population. While this work demonstrates that stunting, wasting, or underweight status at time of QUS assessment is not associated with poor bone quality, we do suggest that further study is needed to examine possible cumulative effects of persistent disruptions that may lead to compromised bone quality in later adolescence.

Metabolites as novel biomarkers for childhood obesity-related traits in Mexican-American children.

BACKGROUND/OBJECTIVES: Although newer approaches have identified several metabolites associated with obesity, there is paucity of such information in paediatric populations, especially among Mexican-Americans (MAs) who are at high risk of obesity. Therefore, we performed a global serum metabolite screening in MA children to identify biomarkers of childhood obesity. METHODS: We selected 15 normal-weight, 13 overweight and 14 obese MA children (6-17 years) and performed global serum metabolite screening using ultra-performance liquid chromatography/quadruple orthogonal acceleration time of flight tandem micro mass spectrometer. Metabolite values were analysed to assess mean differences among groups using one-way analysis of variance, to test for linear trend across groups and to examine Pearson's correlations between them and seven cardiometabolic traits (CMTs): body mass index, waist circumference, systolic blood pressure, diastolic blood pressure, homeostasis model of assessment-insulin resistance, triglycerides and high-density lipoprotein cholesterol. RESULTS: We identified 14 metabolites exhibiting differences between groups as well as linear trend across groups with nominal statistical significance. After adjustment for multiple testing, mean differences and linear trends across groups remained significant (P < 5.9 × 10(-5) ) for L-thyronine, bradykinin and naringenin. Of the examined metabolite-CMT trait pairs, all metabolites except for 2-methylbutyroylcarnitine were nominally associated with two or more CMTs, some exhibiting significance even after accounting for multiple testing (P < 3.6 × 10(-3) ). CONCLUSIONS: To our knowledge, this study - albeit pilot in nature - is the first study to identify these metabolites as novel biomarkers of childhood obesity and its correlates. These findings signify the need for future systematic investigations of metabolic pathways underlying childhood obesity.

Genotype by energy expenditure interaction and body composition traits: The Portuguese Healthy Family Study.

BACKGROUND AND AIMS: Energy expenditure has been negatively correlated with fat accumulation. However, this association is highly variable. In the present study we applied a genotype by environment interaction method to examine the presence of Genotype x by Total Daily Energy Expenditure and Genotype x by Daily Energy Expenditure interactions in the expression of different body composition traits. METHODS AND RESULTS: A total of 958 subjects from 294 families of The Portuguese Healthy Family Study were included in the analysis. TDEE and DEE were assessed using a physical activity recall. Body fat percentages were measured with a bioelectrical impedance scale. GxTDEE and GxDEE examinations were performed using SOLAR 4.0 software. All BC traits were significantly heritable, with heritabilities ranging from 21% to 34%. The GxTDEE and GxDEE interaction models fitted the data better than the polygenic model for all traits. For all traits, a significant GxTDEE and GxDEE interaction was due to variance heterogeneity among distinct levels of TDEE and DEE. For WC, GxTDEE was also significant due to the genetic correlation function. CONCLUSIONS: TDEE and DEE are environmental constraints associated with the expression of individuals' BC genotypes, leading to variability in the phenotypic expression of BC traits.

Waist circumference is genetically correlated with incident Type 2 diabetes in Mexican-American families.

AIMS: We aimed to determine the genetic and environmental correlation between various anthropometric indexes and incident Type 2 diabetes with a focus on waist circumference. METHODS: We used the data on extended Mexican-American families (808 subjects, 7617.92 person-years follow-up) from the San Antonio Family Heart Study and estimated the genetic and environmental correlations of 16 anthropometric indexes with the genetic liability of incident Type 2 diabetes. We performed bivariate trait analyses using the solar software package. RESULTS: All 16 anthropometric indexes were significantly heritable (range of heritabilities 0.24-0.99). Thirteen indexes were found to have significant environmental correlation with the liability of incident Type 2 diabetes. In contrast, only anthropometric indexes consisting of waist circumference (waist circumference, waist-hip ratio and waist-height ratio) were significantly genetically correlated (genetic correlation coefficients: 0.45, 0.55 and 0.44, respectively) with the liability of incident Type 2 diabetes. We did not observe such a correlation for BMI. CONCLUSIONS: Waist circumference as a predictor of future Type 2 diabetes is supported by the finding that they share common genetic influences.

Localization of a major susceptibility locus influencing preterm birth.

Preterm birth (PTB) is a complex trait, but little is known regarding its major genetic determinants. The objective of this study is to localize genes that influence susceptibility to PTB in Mexican Americans (MAs), a minority population in the USA, using predominantly microfilmed birth certificate-based data obtained from the San Antonio Family Birth Weight Study. Only 1302 singleton births from 288 families with information on PTB and significant covariates were considered for genetic analysis. PTB is defined as a childbirth that occurs at <37 completed weeks of gestation, and the prevalence of PTB in this sample was 6.4%. An ∼10 cM genetic map was used to conduct a genome-wide linkage analysis using the program SOLAR. The heritability of PTB was high (h(2) ± SE: 0.75 ± 0.20) and significant (P = 4.5 × 10(-5)), after adjusting for the significant effects of birthweight and birth order. We found significant evidence for linkage of PTB (LOD = 3.6; nominal P = 2.3 × 10(-5); empirical P = 1.0 × 10(-5)) on chromosome 18q between markers D18S1364 and D18S541. Several other chromosomal regions (2q, 9p, 16q and 20q) were also potentially linked with PTB. A strong positional candidate gene in the 18q linked region is SERPINB2 or PAI-2, a member of the plasminogen activator system that is associated with various reproductive processes. In conclusion, to our knowledge, perhaps for the first time in MAs or US populations, we have localized a major susceptibility locus for PTB on chromosome 18q21.33-q23.

Transcriptomics of cortical gray matter thickness decline during normal aging.

INTRODUCTION: We performed a whole-transcriptome correlation analysis, followed by the pathway enrichment and testing of innate immune response pathway analyses to evaluate the hypothesis that transcriptional activity can predict cortical gray matter thickness (GMT) variability during normal cerebral aging. METHODS: Transcriptome and GMT data were available for 379 individuals (age range=28-85) community-dwelling members of large extended Mexican American families. Collection of transcriptome data preceded that of neuroimaging data by 17 years. Genome-wide gene transcriptome data consisted of 20,413 heritable lymphocytes-based transcripts. GMT measurements were performed from high-resolution (isotropic 800 µm) T1-weighted MRI. Transcriptome-wide and pathway enrichment analysis was used to classify genes correlated with GMT. Transcripts for sixty genes from seven innate immune pathways were tested as specific predictors of GMT variability. RESULTS: Transcripts for eight genes (IGFBP3, LRRN3, CRIP2, SCD, IDS, TCF4, GATA3, and HN1) passed the transcriptome-wide significance threshold. Four orthogonal factors extracted from this set predicted 31.9% of the variability in the whole-brain and between 23.4 and 35% of regional GMT measurements. Pathway enrichment analysis identified six functional categories including cellular proliferation, aggregation, differentiation, viral infection, and metabolism. The integrin signaling pathway was significantly (p<10(-6)) enriched with GMT. Finally, three innate immune pathways (complement signaling, toll-receptors and scavenger and immunoglobulins) were significantly associated with GMT. CONCLUSION: Expression activity for the genes that regulate cellular proliferation, adhesion, differentiation and inflammation can explain a significant proportion of individual variability in cortical GMT. Our findings suggest that normal cerebral aging is the product of a progressive decline in regenerative capacity and increased neuroinflammation.

QTL-based association analyses reveal novel genes influencing pleiotropy of metabolic syndrome (MetS).

OBJECTIVE: Metabolic Syndrome (MetS) is a phenotype cluster predisposing to type 2 diabetes and cardiovascular disease. We conducted a study to elucidate the genetic basis underlying linkage signals for multiple representative traits of MetS that we had previously identified at two significant QTLs on chromosomes 3q27 and 17p12. DESIGN AND METHODS: We performed QTL-specific genomic and transcriptomic analyses in 1,137 individuals from 85 extended families that contributed to the original linkage. We tested in SOLAR association of MetS phenotypes with QTL-specific haplotype-tagging SNPs as well as transcriptional profiles of peripheral blood mononuclear cells (PBMCs). RESULTS: SNPs significantly associated with MetS phenotypes under the prior hypothesis of linkage mapped to seven genes at 3q27 and seven at 17p12. Prioritization based on biologic relevance, SNP association, and expression analyses identified two genes: insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) at 3q27 and tumor necrosis factor receptor 13B (TNFRSF13B) at 17p12. Prioritized genes could influence cell-cell adhesion and adipocyte differentiation, insulin/glucose responsiveness, cytokine effectiveness, plasma lipid levels, and lipoprotein densities. CONCLUSIONS: Using an approach combining genomic, transcriptomic, and bioinformatic data we identified novel candidate genes for MetS.

P-selectin Expression Tracks Cerebral Atrophy in Mexican-Americans.

BACKGROUND AND PURPOSE: We hypothesized that the P-selectin (SELP) gene, localized to a region on chromosome 1q24, pleiotropically contributes to increased blood pressure and cerebral atrophy. We tested this hypothesis by performing genetic correlation analyses for 13 mRNA gene expression measures from P-selectin and 11 other genes located in 1q24 region and three magnetic resonance imaging derived indices of cerebral integrity. METHODS: The subject pool consisted of 369 (219F; aged 28-85, average = 47.1 ± 12.7 years) normally aging, community-dwelling members of large extended Mexican-American families. Genetic correlation analysis decomposed phenotypic correlation coefficients into genetic and environmental components among 13 leukocyte-based mRNA gene expressions and three whole-brain and regional measurements of cerebral integrity: cortical gray matter thickness, fractional anisotropy of cerebral white matter, and the volume of hyperintensive WM lesions. RESULTS: From the 13 gene expressions, significant phenotypic correlations were only found for the P- and L-selectin expression levels. Increases in P-selectin expression levels tracked with decline in cerebral integrity while the opposite trend was observed for L-selectin expression. The correlations for the P-selectin expression were driven by shared genetic factors, while the correlations with L-selectin expression were due to shared environmental effects. CONCLUSION: This study demonstrated that P-selectin expression shared a significant variance with measurements of cerebral integrity and posits elevated P-selectin expression levels as a potential risk factor of hypertension-related cerebral atrophy.

Genome-wide linkage scan for quantitative trait loci underlying normal variation in heel bone ultrasound measures.

Quantitative ultrasound (QUS) traits are correlated with bone mineral density (BMD), but predict risk for future fracture independent of BMD. Only a few studies, however, have sought to identify specific genes influencing calcaneal QUS measures. The aim of this study was to conduct a genome-wide linkage scan to identify quantitative trait loci (QTL) influencing normal variation in QUS traits. QUS measures were collected from a total of 719 individuals (336 males and 383 females) from the Fels Longitudinal Study who have been genotyped and have at least one set of QUS measurements. Participants ranged in age from 18.0 to 96.6 years and were distributed across 110 nuclear and extended families. Using the Sahara ® bone sonometer, broadband ultrasound attenuation (BUA), speed of sound (SOS) and stiffness index (QUI) were collected from the right heel. Variance components based linkage analysis was performed on the three traits using 400 polymorphic short tandem repeat (STR) markers spaced approximately 10 cM apart across the autosomes to identify QTL influencing the QUS traits. Age, sex, and other significant covariates were simultaneously adjusted. Heritability estimates (h²) for the QUS traits ranged from 0.42 to 0.57. Significant evidence for a QTL influencing BUA was found on chromosome 11p15 near marker D11S902 (LOD = 3.11). Our results provide additional evidence for a QTL on chromosome 11p that harbors a potential candidate gene(s) related to BUA and bone metabolism.

Fractional anisotropy of water diffusion in cerebral white matter across the lifespan.

Determining the time of peak of cerebral maturation is vital for our understanding of when cerebral maturation ceases and the cerebral degeneration in healthy aging begins. We carefully mapped changes in fractional anisotropy (FA) of water diffusion for eleven major cerebral white matter tracts in a large group (831) of healthy human subjects aged 11-90. FA is a neuroimaging index of micro-structural white matter integrity, sensitive to age-related changes in cerebral myelin levels, measured using diffusion tensor imaging. The average FA values of cerebral white matter (WM) reached peak at the age 32 ± 6 years. FA measurements for all but one major cortical white matter tract (cortico-spinal) reached peaks between 23 and 39 years of age. The maturation rates, prior to age-of-peak were significantly correlated (r=0.74; p=0.01) with the rates of decline, past age-of-peak. Regional analysis of corpus callosum (CC) showed that thinly-myelinated, densely packed fibers in the genu, that connect pre-frontal areas, maturated later and showed higher decline in aging than the more thickly myelinated motor and sensory areas in the body and splenium of CC. Our findings can be summarized as: associative, cerebral WM tracts that reach their peak FA values later in life also show progressively higher age-related decline than earlier maturing motor and sensory tracts. These findings carry multiple and diverse implications for both theoretical studies of the neurobiology of maturation and aging and for the clinical studies of neuropsychiatric disorders.

Genetic variation in SH3-domain GRB2-like (endophilin)-interacting protein 1 has a major impact on fat mass.

OBJECTIVE: The SH3-domain GRB2-like (endophilin)-interacting protein 1 (SGIP1) gene has been shown to be differentially expressed in the hypothalamus of lean versus obese Israeli sand rats (Psammomys obesus), and is suspected of having a role in regulating food intake. The purpose of this study was to assess the role of genetic variation in SGIP1 in human disease. SUBJECTS: We performed single-nucleotide polymorphism (SNP) genotyping in a large family pedigree cohort from the island of Mauritius. The Mauritius Family Study (MFS) consists of 400 individuals from 24 Indo-Mauritian families recruited from the genetically homogeneous population of Mauritius. We measured markers of the metabolic syndrome, including diabetes and obesity-related phenotypes such as fasting plasma glucose, waist:hip ratio, body mass index and fat mass. RESULTS: Statistical genetic analysis revealed associations between SGIP1 polymorphisms and fat mass (in kilograms) as measured by bioimpedance. SNP genotyping identified associations between several genetic variants and fat mass, with the strongest association for rs2146905 (P=4.7 × 10(-5)). A strong allelic effect was noted for several SNPs where fat mass was reduced by up to 9.4% for individuals homozygous for the minor allele. CONCLUSIONS: Our results show association between genetic variants in SGIP1 and fat mass. We provide evidence that variation in SGIP1 is a potentially important determinant of obesity-related traits in humans.

OS046. Genome-wide association scans identify novel maternalsusceptibility loci for preeclampsia.

INTRODUCTION: We have successfully utilized a family-based study design to localize several positional candidate preeclampsia susceptibility genes to chromosomes 2q22(ACVR2A,LCT,LRP1B,RND3,GCA),5q (ERAP2) and 13q(TNFSF13B). We now report on our continued positional cloning efforts using an alternative genome-wide association (GWA) mapping strategy in large Caucasian case-control cohorts from Australia and Norway. OBJECTIVES: To identify maternal genetic risk loci for preeclampsia. METHODS: The unrelated Australian samples (545 cases,547 controls) were genotyped using Illumina BeadChip technology (700K loci) and have been analyzed using PLINK. All unrelated Norwegian samples were genotyped across several Illumina BeadChip substrates and consist of 847 cases (700K loci) and 638 controls. The Norwegian control samples originate from other HUNT studies pertaining to migraine (n=95,700K loci), lung cancer (n=89,370K loci) and normal brain pathology (n=454,2.5M loci). To analyze a concordant set of 2.5-3 million genotypes across all Norwegian samples we are currently using MaCH to impute those loci not directly genotyped. The Norwegian GWA data will be analyzed in SOLAR utilizing empirical kinship estimates to account for any distant relatedness. RESULTS: 1078 Australian samples (538 cases,540 controls) and 648, 175 SNPs passed our quality control metrics. Two SNP associations (rs7579169,p=3.6×10(-7); rs12711941,p=4.3×10(-7)) satisfied our genome-wide significant threshold (p<5.1×10(-7)). These SNPs reside less than 15kb downstream from the 3 terminus of the Inhibin, beta B (INHBB) gene on 2q14.2. Sequencing of the INHBB locus in our patient cohort identified a third intergenic SNP to significantly associate with preeclampsia (rs7576192,p=1.5×10(-7)). These three SNPs confer risk (OR>1.56) and are in strong linkage disequilibrium with each other (r(2)>0.9) but not with any other genotyped SNP ±200kb. The analysis of the Norwegian GWAS is underway. CONCLUSION: The Australian GWAS has identified a novel preeclampsia risk locus on chromosome 2q. The INHBB gene closest to our SNP associations is a plausible positional candidate susceptibility gene. There is a substantive body of evidence implicating inhibins, activins and other members of the TGF-ßsuperfamily to have a role in the development of preeclampsia. The biological connection between ACVR2A and INHBB leads us to speculate that our linkage-based and GWA-based study designs, respectively, have identified a key biological pathway involved in susceptibility to preeclampsia.