Ravi Duggirala

Multi-site genetic analysis of diffusion images and voxelwise heritability analysis: a pilot project of the ENIGMA-DTI working group.

The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium was set up to analyze brain measures and genotypes from multiple sites across the world to improve the power to detect genetic variants that influence the brain. Diffusion tensor imaging (DTI) yields quantitative measures sensitive to brain development and degeneration, and some common genetic variants may be associated with white matter integrity or connectivity. DTI measures, such as the fractional anisotropy (FA) of water diffusion, may be useful for identifying genetic variants that influence brain microstructure. However, genome-wide association studies (GWAS) require large populations to obtain sufficient power to detect and replicate significant effects, motivating a multi-site consortium effort. As part of an ENIGMA-DTI working group, we analyzed high-resolution FA images from multiple imaging sites across North America, Australia, and Europe, to address the challenge of harmonizing imaging data collected at multiple sites. Four hundred images of healthy adults aged 18-85 from four sites were used to create a template and corresponding skeletonized FA image as a common reference space. Using twin and pedigree samples of different ethnicities, we used our common template to evaluate the heritability of tract-derived FA measures. We show that our template is reliable for integrating multiple datasets by combining results through meta-analysis and unifying the data through exploratory mega-analyses. Our results may help prioritize regions of the FA map that are consistently influenced by additive genetic factors for future genetic discovery studies. Protocols and templates are publicly available at (http://enigma.loni.ucla.edu/ongoing/dti-working-group/).

High dimensional endophenotype ranking in the search for major depression risk genes

BACKGROUND Despite overwhelming evidence that major depression is highly heritable, recent studies have localized only a single depression-related locus reaching genome-wide significance and have yet to identify a causal gene. Focusing on family-based studies of quantitative intermediate phenotypes or endophenotypes, in tandem with studies of unrelated individuals using categorical diagnoses, should improve the likelihood of identifying major depression genes. However, there is currently no empirically derived statistically rigorous method for selecting optimal endophentypes for mental illnesses. Here, we describe the endophenotype ranking value, a new objective index of the genetic utility of endophenotypes for any heritable illness. METHODS Applying endophenotype ranking value analysis to a high-dimensional set of over 11,000 traits drawn from behavioral/neurocognitive, neuroanatomic, and transcriptomic phenotypic domains, we identified a set of objective endophenotypes for recurrent major depression in a sample of Mexican American individuals (n = 1122) from large randomly selected extended pedigrees. RESULTS Top-ranked endophenotypes included the Beck Depression Inventory, bilateral ventral diencephalon volume, and expression levels of the RNF123 transcript. To illustrate the utility of endophentypes in this context, each of these traits were utlized along with disease status in bivariate linkage analysis. A genome-wide significant quantitative trait locus was localized on chromsome 4p15 (logarithm of odds = 3.5) exhibiting pleiotropic effects on both the endophenotype (lymphocyte-derived expression levels of the RNF123 gene) and disease risk. CONCLUSIONS The wider use of quantitative endophenotypes, combined with unbiased methods for selecting among these measures, should spur new insights into the biological mechanisms that influence mental illnesses like major depression.

Genome-wide scans for diabetic nephropathy and albuminuria in multiethnic populations: The Family Investigation of Nephropathy and Diabetes (FIND)

The Family Investigation of Nephropathy and Diabetes (FIND) was initiated to map genes underlying susceptibility to diabetic nephropathy. A total of 11 centers participated under a single collection protocol to recruit large numbers of diabetic sibling pairs concordant and discordant for diabetic nephropathy. We report the findings from the first-phase genetic analyses in 1,227 participants from 378 pedigrees of European-American, African-American, Mexican-American, and American Indian descent recruited from eight centers. Model-free linkage analyses, using a dichotomous definition for diabetic nephropathy in 397 sibling pairs, as well as the quantitative trait urinary albumin-to-creatinine ratio (ACR), were performed using the Haseman-Elston linkage test on 404 microsatellite markers. The strongest evidence of linkage to the diabetic nephropathy trait was on chromosomes 7q21.3, 10p15.3, 14q23.1, and 18q22.3. In ACR (883 diabetic sibling pairs), the strongest linkage signals were on chromosomes 2q14.1, 7q21.1, and 15q26.3. These results confirm regions of linkage to diabetic nephropathy on chromosomes 7q, 10p, and 18q from prior reports, making it important that genes underlying these peaks be evaluated for their contribution to nephropathy susceptibility. Large family collections consisting of multiple members with diabetes and advanced nephropathy are likely to accelerate the identification of genes causing diabetic nephropathy, a life-threatening complication of diabetes.

Heritability of the Severity of Diabetic Retinopathy: The FIND-Eye Study

PURPOSE Diabetic retinopathy (DR) and diabetic nephropathy (DN) are serious microvascular complications of diabetes mellitus. Correlations between severity of DR and DN and computed heritability estimates for DR were determined in a large, multiethnic sample of diabetic families. The hypothesis was that (1) the severity of DR correlates with the presence and severity of nephropathy in individuals with diabetes mellitus, and (2) the severity of DR is under significant familial influence in members of multiplex diabetic families. METHODS The Family Investigation of Nephropathy and Diabetes (FIND) was designed to evaluate the genetic basis of DN in American Indians, European Americans, African Americans, and Mexican Americans. FIND enrolled probands with advanced DN, along with their diabetic siblings who were concordant and discordant for nephropathy. These diabetic family members were invited to participate in the FIND-Eye study to determine whether inherited factors underlie susceptibility to DR and its severity. FIND-Eye participants underwent eye examinations and had fundus photographs taken. The severity of DR was graded by using the Early Treatment Diabetic Retinopathy Study Classification (ETDRS). Sib-sib correlations were calculated with the SAGE 5.0 program FCOR, to estimate heritability of retinopathy severity. RESULTS This report summarizes the results for the first 2368 diabetic subjects from 767 families enrolled in FIND-Eye; nearly 50% were Mexican American, the largest single ethnicity within FIND. The overall prevalence of DR was high; 33.4% had proliferative DR; 7.5%, 22.8%, and 9.5% had severe, moderate, and mild nonproliferative DR, respectively; 26.6% had no DR. The severity of DR was significantly associated with severity of DN, both by phenotypic category and by increasing serum creatinine concentration (chi(2) = 658.14, df = 20; P < 0.0001). The sib-sib correlation for DR severity was 0.1358 in the total sample and 0.1224 when limited to the Mexican-American sample. Broad sense heritabilities for DR were 27% overall and 24% in Mexican-American families. The polygenic heritability of liability for proliferative DR approximated 25% in this FIND-Eye sample. CONCLUSIONS These data confirm that the severity of DR parallels the presence and severity of nephropathy in individuals with diabetes mellitus. The severity of DR in members of multiplex diabetic families appears to have a significant familial connection.

Genome-Wide Association and Trans-ethnic Meta-Analysis for Advanced Diabetic Kidney Disease: Family Investigation of Nephropathy and Diabetes (FIND).

Diabetic kidney disease (DKD) is the most common etiology of chronic kidney disease (CKD) in the industrialized world and accounts for much of the excess mortality in patients with diabetes mellitus. Approximately 45% of U.S. patients with incident end-stage kidney disease (ESKD) have DKD. Independent of glycemic control, DKD aggregates in families and has higher incidence rates in African, Mexican, and American Indian ancestral groups relative to European populations. The Family Investigation of Nephropathy and Diabetes (FIND) performed a genome-wide association study (GWAS) contrasting 6,197 unrelated individuals with advanced DKD with healthy and diabetic individuals lacking nephropathy of European American, African American, Mexican American, or American Indian ancestry. A large-scale replication and trans-ethnic meta-analysis included 7,539 additional European American, African American and American Indian DKD cases and non-nephropathy controls. Within ethnic group meta-analysis of discovery GWAS and replication set results identified genome-wide significant evidence for association between DKD and rs12523822 on chromosome 6q25.2 in American Indians (P = 5.74x10-9). The strongest signal of association in the trans-ethnic meta-analysis was with a SNP in strong linkage disequilibrium with rs12523822 (rs955333; P = 1.31x10-8), with directionally consistent results across ethnic groups. These 6q25.2 SNPs are located between the SCAF8 and CNKSR3 genes, a region with DKD relevant changes in gene expression and an eQTL with IPCEF1, a gene co-translated with CNKSR3. Several other SNPs demonstrated suggestive evidence of association with DKD, within and across populations. These data identify a novel DKD susceptibility locus with consistent directions of effect across diverse ancestral groups and provide insight into the genetic architecture of DKD.

Genetic basis of neurocognitive decline and reduced white-matter integrity in normal human brain aging

Significance Identification of genes associated with brain aging should improve our understanding of the biological processes that govern normal age-related decline. In randomly selected pedigrees, we documented profound aging effects from young adulthood to old age (18–83 years) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for shared genetic determination was observed. Applying a gene-by-environment interaction analysis where age is an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration with age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. Identifying brain-aging traits is a critical first step in delineating the biological mechanisms of successful aging. Identification of genes associated with brain aging should markedly improve our understanding of the biological processes that govern normal age-related decline. However, challenges to identifying genes that facilitate successful brain aging are considerable, including a lack of established phenotypes and difficulties in modeling the effects of aging per se, rather than genes that influence the underlying trait. In a large cohort of randomly selected pedigrees (n = 1,129 subjects), we documented profound aging effects from young adulthood to old age (18–83 y) on neurocognitive ability and diffusion-based white-matter measures. Despite significant phenotypic correlation between white-matter integrity and tests of processing speed, working memory, declarative memory, and intelligence, no evidence for pleiotropy between these classes of phenotypes was observed. Applying an advanced quantitative gene-by-environment interaction analysis where age is treated as an environmental factor, we demonstrate a heritable basis for neurocognitive deterioration as a function of age. Furthermore, by decomposing gene-by-aging (G × A) interactions, we infer that different genes influence some neurocognitive traits as a function of age, whereas other neurocognitive traits are influenced by the same genes, but to differential levels, from young adulthood to old age. In contrast, increasing white-matter incoherence with age appears to be nongenetic. These results clearly demonstrate that traits sensitive to the genetic influences on brain aging can be identified, a critical first step in delineating the biological mechanisms of successful aging.

Whole Brain and Regional Hyperintense White Matter Volume and Blood Pressure Overlap of Genetic Loci Produced by Bivariate, Whole-Genome Linkage Analyses

Background and Purpose— The volume of T2-hyperintense white matter (HWM) is an important neuroimaging marker of cerebral integrity with a demonstrated high heritability. Pathophysiology studies have shown that the regional, ependymal, and subcortical HWM lesions are associated with elevated arterial pulse pressure and arterial blood pressure (BP), respectively. We performed bivariate, whole-genome linkage analyses for HWM volumes and BP measurements to identify chromosomal regions that contribute jointly to both traits in a population of healthy Mexican Americans. Our aims were to localize novel quantitative trait loci acting pleiotropically on these phenotypes and to replicate previous genetic findings on whole brain HWM volume and BP measurements. Methods— BP measurements and volumes of whole-brain (WB), subcortical, and ependymal HWM lesions, measured from high-resolution (1 mm3) 3-dimensional fluid-attenuated inversion recovery images, served as focal quantitative phenotypes. Data were collected from 357 (218 females; mean age=47.9±13.2 years) members of large extended families who participated in the San Antonio Family Heart Study. Results— Bivariate genomewide linkage analyses localized a significant quantitative trait locus influencing WB and regional (ependymal) HWM volumes and pulse pressure and systolic BP to chromosomal location 1q24 between markers D1S196 and D1S1619. Several other chromosomal regions (1q42, 10q24-q26, and 15q26) exhibited suggestive linkages. The results of the post hoc analyses that excluded 55 subjects taking antihypertensive medication showed no substantive differences from the results obtained in the full cohort. Conclusion— This study confirms several previously observed quantitative trait loci influencing BP and cerebral integrity and identifies a novel significant quantitative trait locus at chromosome 1q24. The genetic results strongly support a role for pleiotropically acting genes jointly influencing BP and cerebral white matter integrity.

Influence of age, sex and genetic factors on the human brain

We report effects of age, age2, sex and additive genetic factors on variability in gray matter thickness, surface area and white matter integrity in 1,010 subjects from the Genetics of Brain Structure and Function Study. Age was more strongly associated with gray matter thickness and fractional anisotropy of water diffusion in white matter tracts, while sex was more strongly associated with gray matter surface area. Widespread heritability of neuroanatomic traits was observed, suggesting that brain structure is under strong genetic control. Furthermore, our findings indicate that neuroimaging-based measurements of cerebral variability are sensitive to genetic mediation. Fundamental studies of genetic influence on the brain will help inform gene discovery initiatives in both clinical and normative samples.

Discovering schizophrenia endophenotypes in randomly ascertained pedigrees.

BACKGROUND Although case-control approaches are beginning to disentangle schizophrenias complex polygenic burden, other methods will likely be necessary to fully identify and characterize risk genes. Endophenotypes, traits genetically correlated with an illness, can help characterize the impact of risk genes by providing genetically relevant traits that are more tractable than the behavioral symptoms that classify mental illness. Here, we present an analytic approach for discovering and empirically validating endophenotypes in extended pedigrees with very few affected individuals. Our approach indexes each family members risk as a function of shared genetic kinship with an affected individual, often referred to as the coefficient of relatedness. To demonstrate the utility of this approach, we search for neurocognitive and neuroanatomic endophenotypes for schizophrenia in large unselected multigenerational pedigrees. METHODS A fixed-effects test within the variance component framework was performed on neurocognitive and cortical surface area traits in 1606 Mexican-American individuals from large, randomly ascertained extended pedigrees who participated in the Genetics of Brain Structure and Function study. As affecteds were excluded from analyses, results were not influenced by disease state or medication usage. RESULTS Despite having sampled just 6 individuals with schizophrenia, our sample provided 233 individuals at various levels of genetic risk for the disorder. We identified three neurocognitive measures (digit-symbol substitution, facial memory, and emotion recognition) and six medial temporal and prefrontal cortical surfaces associated with liability for schizophrenia. CONCLUSIONS With our novel analytic approach, one can discover and rank endophenotypes for schizophrenia, or any heritable disease, in randomly ascertained pedigrees.

Genome-wide significant localization for working and spatial memory: Identifying genes for psychosis using models of cognition

It is well established that risk for developing psychosis is largely mediated by the influence of genes, but identifying precisely which genes underlie that risk has been problematic. Focusing on endophenotypes, rather than illness risk, is one solution to this problem. Impaired cognition is a well‐established endophenotype of psychosis. Here we aimed to characterize the genetic architecture of cognition using phenotypically detailed models as opposed to relying on general IQ or individual neuropsychological measures. In so doing we hoped to identify genes that mediate cognitive ability, which might also contribute to psychosis risk. Hierarchical factor models of genetically clustered cognitive traits were subjected to linkage analysis followed by QTL region‐specific association analyses in a sample of 1,269 Mexican American individuals from extended pedigrees. We identified four genome wide significant QTLs, two for working and two for spatial memory, and a number of plausible and interesting candidate genes. The creation of detailed models of cognition seemingly enhanced the power to detect genetic effects on cognition and provided a number of possible candidate genes for psychosis.