Ravindranath Duggirala

Cortical Thickness or Grey Matter Volume? The Importance of Selecting the Phenotype for Imaging Genetics Studies

Choosing the appropriate neuroimaging phenotype is critical to successfully identify genes that influence brain structure or function. While neuroimaging methods provide numerous potential phenotypes, their role for imaging genetics studies is unclear. Here we examine the relationship between brain volume, grey matter volume, cortical thickness and surface area, from a genetic standpoint. Four hundred and eighty-six individuals from randomly ascertained extended pedigrees with high-quality T1-weighted neuroanatomic MRI images participated in the study. Surface-based and voxel-based representations of brain structure were derived, using automated methods, and these measurements were analysed using a variance-components method to identify the heritability of these traits and their genetic correlations. All neuroanatomic traits were significantly influenced by genetic factors. Cortical thickness and surface area measurements were found to be genetically and phenotypically independent. While both thickness and area influenced volume measurements of cortical grey matter, volume was more closely related to surface area than cortical thickness. This trend was observed for both the volume-based and surface-based techniques. The results suggest that surface area and cortical thickness measurements should be considered separately and preferred over gray matter volumes for imaging genetic studies.

Linkage of type 2 diabetes mellitus and of age at onset to a genetic location on chromosome 10q in Mexican Americans.

Since little is known about chromosomal locations harboring type 2 diabetes-susceptibility genes, we conducted a genomewide scan for such genes in a Mexican American population. We used data from 27 low-income extended Mexican American pedigrees consisting of 440 individuals for whom genotypic data are available for 379 markers. We used a variance-components technique to conduct multipoint linkage analyses for two phenotypes: type 2 diabetes (a discrete trait) and age at onset of diabetes (a truncated quantitative trait). For the multipoint analyses, a subset of 295 markers was selected on the basis of optimal spacing and informativeness. We found significant evidence that a susceptibility locus near the marker D10S587 on chromosome 10q influences age at onset of diabetes (LOD score 3.75) and is also linked with type 2 diabetes itself (LOD score 2.88). This susceptibility locus explains 63.8%+/-9.9% (P=. 000016) of the total phenotypic variation in age at onset of diabetes and 65.7%+/-10.9% (P=.000135) of the total variation in liability to type 2 diabetes. Weaker evidence was found for linkage of diabetes and of age at onset to regions on chromosomes 3p, 4q, and 9p. In conclusion, our strongest evidence for linkage to both age at onset of diabetes and type 2 diabetes itself in the Mexican American population was for a region on chromosome 10q.

Genetic control over the resting brain

The default-mode network, a coherent resting-state brain network, is thought to characterize basal neural activity. Aberrant default-mode connectivity has been reported in a host of neurological and psychiatric illnesses and in persons at genetic risk for such illnesses. Whereas the neurophysiologic mechanisms that regulate default-mode connectivity are unclear, there is growing evidence that genetic factors play a role. In this report, we estimate the importance of genetic effects on the default-mode network by examining covariation patterns in functional connectivity among 333 individuals from 29 randomly selected extended pedigrees. Heritability for default-mode functional connectivity was 0.424 ± 0.17 (P = 0.0046). Although neuroanatomic variation in this network was also heritable, the genetic factors that influence default-mode functional connectivity and gray-matter density seem to be distinct, suggesting that unique genes influence the structure and function of the network. In contrast, significant genetic correlations between regions within the network provide evidence that the same genetic factors contribute to variation in functional connectivity throughout the default mode. Specifically, the left parahippocampal region was genetically correlated with all other network regions. In addition, the posterior cingulate/precuneus region, medial prefrontal cortex, and right cerebellum seem to form a subnetwork. Default-mode functional connectivity is influenced by genetic factors that cannot be attributed to anatomic variation or a single region within the network. By establishing the heritability of default-mode functional connectivity, this experiment provides the obligatory evidence required before these measures can be considered as endophenotypes for psychiatric or neurological illnesses or to identify genes influencing intrinsic brain function.

Loss-of-function mutations in SLC30A8 protect against type 2 diabetes

Loss-of-function mutations protective against human disease provide in vivo validation of therapeutic targets, but none have yet been described for type 2 diabetes (T2D). Through sequencing or genotyping of ∼150,000 individuals across 5 ancestry groups, we identified 12 rare protein-truncating variants in SLC30A8, which encodes an islet zinc transporter (ZnT8) and harbors a common variant (p.Trp325Arg) associated with T2D risk and glucose and proinsulin levels. Collectively, carriers of protein-truncating variants had 65% reduced T2D risk (P = 1.7 × 10−6), and non-diabetic Icelandic carriers of a frameshift variant (p.Lys34Serfs*50) demonstrated reduced glucose levels (−0.17 s.d., P = 4.6 × 10−4). The two most common protein-truncating variants (p.Arg138* and p.Lys34Serfs*50) individually associate with T2D protection and encode unstable ZnT8 proteins. Previous functional study of SLC30A8 suggested that reduced zinc transport increases T2D risk, and phenotypic heterogeneity was observed in mouse Slc30a8 knockouts. In contrast, loss-of-function mutations in humans provide strong evidence that SLC30A8 haploinsufficiency protects against T2D, suggesting ZnT8 inhibition as a therapeutic strategy in T2D prevention.

A variance component approach to dichotomous trait linkage analysis using a threshold model

We developed and utilized a multipoint variance components method to test for linkage between a disease trait and markers on chromosome 5 in the simulated data provided in GAW10 Problem 2. We demonstrated that the discrete trait variance components method recovers unbiased estimates of quantitative trait locus (QTL) location and reasonable estimates of effect size. We also showed that dichotomization of (a continuous trait such as) Q1 diminished the power to detect linkage compared to direct analysis of Q1, and that extended pedigree analyses provided superior power to detect linkage compared to those in nuclear families.

Genetics of microstructure of cerebral white matter using diffusion tensor imaging

We analyzed the degree of genetic control over intersubject variability in the microstructure of cerebral white matter (WM) using diffusion tensor imaging (DTI). We performed heritability, genetic correlation and quantitative trait loci (QTL) analyses for the whole-brain and 10 major cerebral WM tracts. Average measurements for fractional anisotropy (FA), radial (L( perpendicular)) and axial (L( vertical line)) diffusivities served as quantitative traits. These analyses were done in 467 healthy individuals (182 males/285 females; average age 47.9+/-13.5 years; age range: 19-85 years), recruited from randomly-ascertained pedigrees of extended families. Significant heritability was observed for FA (h(2)=0.52+/-0.11; p=10(-7)) and L( perpendicular) (h(2)=0.37+/-0.14; p=0.001), while L( vertical line) measurements were not significantly heritable (h(2)=0.09+/-0.12; p=0.20). Genetic correlation analysis indicated that the FA and L( perpendicular) shared 46% of the genetic variance. Tract-wise analysis revealed a regionally diverse pattern of genetic control, which was unrelated to ontogenic factors, such as tract-wise age-of-peak FA values and rates of age-related change in FA. QTL analysis indicated linkages for whole-brain average FA (LOD=2.36) at the marker D15S816 on chromosome 15q25, and for L( perpendicular) (LOD=2.24) near the marker D3S1754 on the chromosome 3q27. These sites have been reported to have significant co-inheritance with two psychiatric disorders (major depression and obsessive-compulsive disorder) in which patients show characteristic alterations in cerebral WM. Our findings suggest that the microstructure of cerebral white matter is under a strong genetic control and further studies in healthy as well as patients with brain-related illnesses are imperative to identify the genes that may influence cerebral white matter.

Meta-analysis of genome-wide linkage studies in BMI and obesity

Objective: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI‐defined obesity using a nonparametric genome scan meta‐analysis.

A major susceptibility locus influencing plasma triglyceride concentrations is located on chromosome 15q in Mexican Americans.

Although several genetic forms of rare or syndromic hypertriglyceridemia have been reported, little is known about the specific chromosomal regions across the genome harboring susceptibility genes for common forms of hypertriglyceridemia. Therefore, we conducted a genomewide scan for susceptibility genes influencing plasma triglyceride (TG) levels in a Mexican American population. We used both phenotypic and genotypic data from 418 individuals distributed across 27 low-income, extended Mexican American families. For the analyses, TG values were log transformed (ln TG). We used a variance-components technique to conduct multipoint linkage analyses for localizing susceptibility genes that determine variation in TG levels. We used an approximately 10-15-cM map, which was made on the basis of information from 295 microsatellite markers. After accounting for the effects of sex and sex-specific age terms, we found significant evidence for linkage (LOD = 3.88) of ln TG levels to a genetic location between the markers GABRB3 and D15S165 on chromosome 15q. This putative locus explains 39.7+/-7% (P=.000012) of total phenotypic variation in ln TG levels. Suggestive evidence was found for linkage of ln TG levels to two different locations on chromosome 7, which are approximately 85 cM apart from each other. Also, there is some evidence for linkage of high-density lipoprotein cholesterol concentrations to a genetic location near one of the regions on chromosome 7. In conclusion, we found strong evidence for linkage of ln TG levels to a genetic location on chromosome 15q in a Mexican American population, which is prone to disease conditions such as type 2 diabetes and the insulin-resistance syndrome that are associated with hypertriglyceridemia. This putative locus appears to have a major influence on ln TG variation.

Genetic Basis of Variation in Carotid Artery Wall Thickness

BACKGROUND AND PURPOSE Other than the documented associations of risk factors and carotid artery wall thickness, the genetic basis of variation in carotid artery intimal-medial thickness (IMT) is unknown. The purpose of this study was to examine the extent to which variation in common carotid artery (CCA) IMT and internal carotid artery (ICA) IMT are under genetic control. METHODS The sibship data used for this analysis were part of an epidemiological survey in Mexico City. The CCA and ICA analyses were based on 46 and 44 sibships of various sizes, respectively. The CCA and ICA IMTs were measured with carotid ultrasonography. Using a robust variance decomposition method, we performed genetic analyses of CCA IMT and ICA IMT measurements with models incorporating several cardiovascular risk factors (eg, lipids, diabetes, blood pressure, and smoking) as covariates. RESULTS After accounting for the effects of covariates, we detected high heritabilities for CCA IMT (h2 = 0.92 +/- 0.05, P = .001) and ICA IMT (h2 = 0.86 +/- 0.13, P = .029). Genes accounted for 66.0% of the total variation in CCA IMT, whereas 27.7% of variation was attributable to covariates. For ICA IMT, genes explained a high proportion (74.9%) of total phenotypic variation. The covariates accounted for 11.5% of variation in ICA IMT. CONCLUSIONS Our results suggest that substantial proportions of phenotypic variance in CCA IMT and ICA IMT are attributable to shared genetic factors.

Haplotypes of Transcription Factor 7–Like 2 (TCF7L2) Gene and Its Upstream Region Are Associated With Type 2 Diabetes and Age of Onset in Mexican Americans

TCF7L2 acts as both a repressor and transactivator of genes, as directed by the Wnt signaling pathway. Recently, several highly correlated sequence variants located within a haplotype block of the TCF7L2 gene were observed to associate with type 2 diabetes in three Caucasian cohorts. We previously reported linkage of type 2 diabetes in the San Antonio Family Diabetes Study (SAFADS) cohort consisting of extended pedigrees of Mexican Americans to the region of chromosome 10q harboring TCF7L2. We therefore genotyped 11 single nucleotide polymorphisms (SNPs) from nine haplotype blocks across the gene in 545 SAFADS subjects (178 diabetic) to investigate their role in diabetes pathogenesis. We observed nominal association between four SNPs (rs10885390, rs7903146, rs12255372, and rs3814573) in three haplotype blocks and type 2 diabetes, age at diagnosis, and 2-h glucose levels (P = 0.001–0.055). Furthermore, we identified a common protective haplotype defined by these four SNPs that was significantly associated with type 2 diabetes and age at diagnosis (P = 4.2 × 10−5, relative risk [RR] 0.69; P = 6.7 × 10−6, respectively) and a haplotype that confers diabetes risk that contains the rare alleles at SNPs rs10885390 and rs12255372 (P = 0.02, RR 1.64). These data provide evidence that variation in the TCF7L2 genomic region may affect risk for type 2 diabetes in Mexican Americans, but the attributable risk may be lower than in Caucasian populations.