A framework for detecting noncoding rare-variant associations of large-scale whole-genome sequencing studies.

Large-scale whole-genome sequencing studies have enabled analysis of noncoding rare-variant (RV) associations with complex human diseases and traits. Variant-set analysis is a powerful approach to study RV association. However, existing methods have limited ability in analyzing the noncoding genome. We propose a computationally efficient and robust noncoding RV association detection framework, STAARpipeline, to automatically annotate a whole-genome sequencing study and perform flexible noncoding RV association analysis, including gene-centric analysis and fixed window-based and dynamic window-based non-gene-centric analysis by incorporating variant functional annotations. In gene-centric analysis, STAARpipeline uses STAAR to group noncoding variants based on functional categories of genes and incorporate multiple functional annotations. In non-gene-centric analysis, STAARpipeline uses SCANG-STAAR to incorporate dynamic window sizes and multiple functional annotations. We apply STAARpipeline to identify noncoding RV sets associated with four lipid traits in 21,015 discovery samples from the Trans-Omics for Precision Medicine (TOPMed) program and replicate several of them in an additional 9,123 TOPMed samples. We also analyze five non-lipid TOPMed traits.

Minimal Relationship between Local Gyrification and General Cognitive Ability in Humans.

Previous studies suggest that gyrification is associated with superior cognitive abilities in humans, but the strength of this relationship remains unclear. Here, in two samples of related individuals (total N = 2882), we calculated an index of local gyrification (LGI) at thousands of cortical surface points using structural brain images and an index of general cognitive ability (g) using performance on cognitive tests. Replicating previous studies, we found that phenotypic and genetic LGI-g correlations were positive and statistically significant in many cortical regions. However, all LGI-g correlations in both samples were extremely weak, regardless of whether they were significant or nonsignificant. For example, the median phenotypic LGI-g correlation was 0.05 in one sample and 0.10 in the other. These correlations were even weaker after adjusting for confounding neuroanatomical variables (intracranial volume and local cortical surface area). Furthermore, when all LGIs were considered together, at least 89% of the phenotypic variance of g remained unaccounted for. We conclude that the association between LGI and g is too weak to have profound implications for our understanding of the neurobiology of intelligence. This study highlights potential issues when focusing heavily on statistical significance rather than effect sizes in large-scale observational neuroimaging studies.

Neurocognitive impairment in type 2 diabetes: evidence for shared genetic aetiology.

AIMS/HYPOTHESIS: Type 2 diabetes is associated with cognitive impairments, but it is unclear whether common genetic factors influence both type 2 diabetes risk and cognition. METHODS: Using data from 1892 Mexican-American individuals from extended pedigrees, including 402 with type 2 diabetes, we examined possible pleiotropy between type 2 diabetes and cognitive functioning, as measured by a comprehensive neuropsychological test battery. RESULTS: Negative phenotypic correlations (ρp) were observed between type 2 diabetes and measures of attention (Continuous Performance Test [CPT d']: ρp = -0.143, p = 0.001), verbal memory (California Verbal Learning Test [CVLT] recall: ρp = -0.111, p = 0.004) and face memory (Penn Face Memory Test [PFMT]: ρp = -0.127, p = 0.002; PFMT Delayed: ρp = -0.148, p = 2 × 10-4), replicating findings of cognitive impairment in type 2 diabetes. Negative genetic correlations (ρg) were also observed between type 2 diabetes and measures of attention (CPT d': ρg = -0.401, p = 0.001), working memory (digit span backward test: ρg = -0.380, p = 0.005), and face memory (PFMT: ρg = -0.476, p = 2 × 10-4; PFMT Delayed: ρg = -0.376, p = 0.005), suggesting that the same genetic factors underlying risk for type 2 diabetes also influence poor cognitive performance in these domains. Performance in these domains was also associated with type 2 diabetes risk using an endophenotype ranking value approach. Specifically, on measures of attention (CPT d': ß = -0.219, p = 0.005), working memory (digit span backward: ß = -0.326, p = 0.035), and face memory (PFMT: ß = -0.171, p = 0.023; PFMT Delayed: ß = -0.215, p = 0.005), individuals with type 2 diabetes showed the lowest performance, while unaffected/unrelated individuals showed the highest performance, and those related to an individual with type 2 diabetes performed at an intermediate level. CONCLUSIONS/INTERPRETATION: These findings suggest that cognitive impairment may be a useful endophenotype of type 2 diabetes and, therefore, help to elucidate the pathophysiological underpinnings of this chronic disease. DATA AVAILABILITY: The data analysed in this study is available in dbGaP: www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001215.v2.p2.

Family-based analyses reveal novel genetic overlap between cytokine interleukin-8 and risk for suicide attempt.

BACKGROUND: Suicide is major public health concern. It is imperative to find robust biomarkers so that at-risk individuals can be identified in a timely and reliable manner. Previous work suggests mechanistic links between increased cytokines and risk for suicide, but questions remain regarding the etiology of this association, as well as the roles of sex and BMI. METHODS: Analyses were conducted using a randomly-ascertained extended-pedigree sample of 1882 Mexican-American individuals (60% female, mean age = 42.04, range = 18-97). Genetic correlations were calculated using a variance components approach between the cytokines TNF-α, IL-6 and IL-8, and Lifetime Suicide Attempt and Current Suicidal Ideation. The potentially confounding effects of sex and BMI were considered. RESULTS: 159 individuals endorse a Lifetime Suicide Attempt. IL-8 and IL-6 shared significant genetic overlap with risk for suicide attempt (ρg = 0.49, pFDR = 7.67 × 10-03; ρg = 0.53, pFDR = 0.01), but for IL-6 this was attenuated when BMI was included as a covariate (ρg = 0.37, se = 0.23, pFDR = 0.12). Suicide attempts were significantly more common in females (pFDR = 0.01) and the genetic overlap between IL-8 and risk for suicide attempt was significant in females (ρg = 0.56, pFDR = 0.01), but not in males (ρg = 0.44, pFDR = 0.30). DISCUSSION: These results demonstrate that: IL-8 shares genetic influences with risk for suicide attempt; females drove this effect; and BMI should be considered when assessing the association between IL-6 and suicide. This finding represents a significant advancement in knowledge by demonstrating that cytokine alterations are not simply a secondary manifestation of suicidal behavior, but rather, the pathophysiology of suicide attempts is, at least partly, underpinned by the same biological mechanisms responsible for regulating inflammatory response.

Contribution of Inbred Singletons to Variance Component Estimation of Heritability and Linkage.

OBJECTIVES: An interesting consequence of consanguinity is that the inbred singleton becomes informative for genetic variance. We determine the contribution of an inbred singleton to variance component analysis of heritability and linkage. METHODS: Statistical theory for the power of variance component analysis of quantitative traits is used to determine the expected contribution of an inbred singleton to likelihood-ratio tests of heritability and linkage. RESULTS: In variance component models, an inbred singleton contributes relatively little to a test of heritability but can contribute substantively to a test of linkage. For small-to-moderate quantitative trait locus (QTL) effects and a level of inbreeding comparable to matings between first cousins (the preferred form of union in many human populations), an inbred singleton can carry nearly 25% of the information of a non-inbred sib pair. In more highly inbred contexts available with experimental animal populations, nonhuman primate colonies, and some human subpopulations, the contribution of an inbred singleton relative to a sib pair can exceed 50%. CONCLUSIONS: Inbred individuals, even in isolation from other members of a sample, can contribute to variance component estimation and tests of heritability and linkage. Under certain conditions, the informativeness of the inbred singleton can approach that of a non-inbred sib pair.

Epigenetic Age Acceleration Assessed with Human White-Matter Images.

The accurate estimation of age using methylation data has proved a useful and heritable biomarker, with acceleration in epigenetic age predicting a number of age-related phenotypes. Measures of white matter integrity in the brain are also heritable and highly sensitive to both normal and pathological aging processes across adulthood. We consider the phenotypic and genetic interrelationships between epigenetic age acceleration and white matter integrity in humans. Our goal was to investigate processes that underlie interindividual variability in age-related changes in the brain. Using blood taken from a Mexican-American extended pedigree sample (n = 628; age = 23.28-93.11 years), epigenetic age was estimated using the method developed by Horvath (2013). For n = 376 individuals, diffusion tensor imaging scans were also available. The interrelationship between epigenetic age acceleration and global white matter integrity was investigated with variance decomposition methods. To test for neuroanatomical specificity, 16 specific tracts were additionally considered. We observed negative phenotypic correlations between epigenetic age acceleration and global white matter tract integrity (ρpheno = -0.119, p = 0.028), with evidence of shared genetic (ρgene = -0.463, p = 0.013) but not environmental influences. Negative phenotypic and genetic correlations with age acceleration were also seen for a number of specific white matter tracts, along with additional negative phenotypic correlations between granulocyte abundance and white matter integrity. These findings (i.e., increased acceleration in epigenetic age in peripheral blood correlates with reduced white matter integrity in the brain and shares common genetic influences) provide a window into the neurobiology of aging processes within the brain and a potential biomarker of normal and pathological brain aging.SIGNIFICANCE STATEMENT Epigenetic measures can be used to predict age with a high degree of accuracy and so capture acceleration in biological age, relative to chronological age. The white matter tracts within the brain are also highly sensitive to aging processes. We show that increased biological aging (measured using epigenetic data from blood samples) is correlated with reduced integrity of white matter tracts within the human brain (measured using diffusion tensor imaging) with data from a large sample of Mexican-American families. Given the family design of the sample, we are also able to demonstrate that epigenetic aging and white matter tract integrity also share common genetic influences. Therefore, epigenetic age may be a potential, and accessible, biomarker of brain aging.

Shared Genetic Factors Influence Head Motion During MRI and Body Mass Index.

Head movements are typically viewed as a nuisance to functional magnetic resonance imaging (fMRI) analysis, and are particularly problematic for resting state fMRI. However, there is growing evidence that head motion is a behavioral trait with neural and genetic underpinnings. Using data from a large randomly ascertained extended pedigree sample of Mexican Americans (n = 689), we modeled the genetic structure of head motion during resting state fMRI and its relation to 48 other demographic and behavioral phenotypes. A replication analysis was performed using data from the Human Connectome Project, which uses an extended twin design (n = 864). In both samples, head motion was significantly heritable (h2 = 0.313 and 0.427, respectively), and phenotypically correlated with numerous traits. The most strongly replicated relationship was between head motion and body mass index, which showed evidence of shared genetic influences in both data sets. These results highlight the need to view head motion in fMRI as a complex neurobehavioral trait correlated with a number of other demographic and behavioral phenotypes. Given this, when examining individual differences in functional connectivity, the confounding of head motion with other traits of interest needs to be taken into consideration alongside the critical important of addressing head motion artifacts.

TRAK2, a novel regulator of ABCA1 expression, cholesterol efflux and HDL biogenesis.

Aims: The recent failures of HDL-raising therapies have underscored our incomplete understanding of HDL biology. Therefore there is an urgent need to comprehensively investigate HDL metabolism to enable the development of effective HDL-centric therapies. To identify novel regulators of HDL metabolism, we performed a joint analysis of human genetic, transcriptomic, and plasma HDL-cholesterol (HDL-C) concentration data and identified a novel association between trafficking protein, kinesin binding 2 (TRAK2) and HDL-C concentration. Here we characterize the molecular basis of the novel association between TRAK2 and HDL-cholesterol concentration. Methods and results: Analysis of lymphocyte transcriptomic data together with plasma HDL from the San Antonio Family Heart Study (n = 1240) revealed a significant negative correlation between TRAK2 mRNA levels and HDL-C concentration, HDL particle diameter and HDL subspecies heterogeneity. TRAK2 siRNA-mediated knockdown significantly increased cholesterol efflux to apolipoprotein A-I and isolated HDL from human macrophage (THP-1) and liver (HepG2) cells by increasing the mRNA and protein expression of the cholesterol transporter ATP-binding cassette, sub-family A member 1 (ABCA1). The effect of TRAK2 knockdown on cholesterol efflux was abolished in the absence of ABCA1, indicating that TRAK2 functions in an ABCA1-dependent efflux pathway. TRAK2 knockdown significantly increased liver X receptor (LXR) binding at the ABCA1 promoter, establishing TRAK2 as a regulator of LXR-mediated transcription of ABCA1. Conclusion: We show, for the first time, that TRAK2 is a novel regulator of LXR-mediated ABCA1 expression, cholesterol efflux, and HDL biogenesis. TRAK2 may therefore be an important target in the development of anti-atherosclerotic therapies.

Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants.

We searched a gene expression dataset comprised of 634 schizophrenia (SZ) cases and 713 controls for expression outliers (i.e., extreme tails of the distribution of transcript expression values) with SZ cases overrepresented compared with controls. These outlier genes were enriched for brain expression and for genes known to be associated with neurodevelopmental disorders. SZ cases showed higher outlier burden (i.e., total outlier events per subject) than controls for genes within copy number variants (CNVs) associated with SZ or neurodevelopmental disorders. Outlier genes were enriched for CNVs and for rare putative regulatory variants, but this only explained a small proportion of the outlier subjects, highlighting the underlying presence of additional genetic and potentially, epigenetic mechanisms.

Novel epigenetic determinants of type 2 diabetes in Mexican-American families.

Although DNA methylation is now recognized as an important mediator of complex diseases, the extent to which the genetic basis of such diseases is accounted for by DNA methylation is unknown. In the setting of large, extended families representing a minority, high-risk population of the USA, we aimed to characterize the role of epigenome-wide DNA methylation in type 2 diabetes (T2D). Using Illumina HumanMethylation450 BeadChip arrays, we tested for association of DNA methylation at 446 356 sites with age, sex and phenotypic traits related to T2D in 850 pedigreed Mexican-American individuals. Robust statistical analyses showed that (i) 15% of the methylome is significantly heritable, with a median heritability of 0.14; (ii) DNA methylation at 14% of CpG sites is associated with nearby sequence variants; (iii) 22% and 3% of the autosomal CpG sites are associated with age and sex, respectively; (iv) 53 CpG sites were significantly associated with liability to T2D, fasting blood glucose and insulin resistance; (v) DNA methylation levels at five CpG sites, mapping to three well-characterized genes (TXNIP, ABCG1 and SAMD12) independently explained 7.8% of the heritability of T2D (vi) methylation at these five sites was unlikely to be influenced by neighboring DNA sequence variation. Our study has identified novel epigenetic indicators of T2D risk in Mexican Americans who have increased risk for this disease. These results provide new insights into potential treatment targets of T2D.

Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.

Initial results from sequencing studies suggest that there are relatively few low-frequency (<5%) variants associated with large effects on common phenotypes. We performed low-pass whole-genome sequencing in 680 individuals from the InCHIANTI study to test two primary hypotheses: (i) that sequencing would detect single low-frequency-large effect variants that explained similar amounts of phenotypic variance as single common variants, and (ii) that some common variant associations could be explained by low-frequency variants. We tested two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common variant-common phenotype associations-11 132 cis-gene expression traits in 450 individuals and 93 circulating biomarkers in all 680 individuals. From a total of 11 657 229 high-quality variants of which 6 129 221 and 5 528 008 were common and low frequency (<5%), respectively, low frequency-large effect associations comprised 7% of detectable cis-gene expression traits [89 of 1314 cis-eQTLs at P < 1 × 10(-06) (false discovery rate ∼5%)] and one of eight biomarker associations at P < 8 × 10(-10). Very few (30 of 1232; 2%) common variant associations were fully explained by low-frequency variants. Our data show that whole-genome sequencing can identify low-frequency variants undetected by genotyping based approaches when sample sizes are sufficiently large to detect substantial numbers of common variant associations, and that common variant associations are rarely explained by single low-frequency variants of large effect.

ADAM19: A Novel Target for Metabolic Syndrome in Humans and Mice.

Obesity is one of the most prevalent metabolic diseases in the Western world and correlates directly with insulin resistance, which may ultimately culminate in type 2 diabetes (T2D). We sought to ascertain whether the human metalloproteinase A Disintegrin and Metalloproteinase 19 (ADAM19) correlates with parameters of the metabolic syndrome in humans and mice. To determine the potential novel role of ADAM19 in the metabolic syndrome, we first conducted microarray studies on peripheral blood mononuclear cells from a well-characterised human cohort. Secondly, we examined the expression of ADAM19 in liver and gonadal white adipose tissue using an in vivo diet induced obesity mouse model. Finally, we investigated the effect of neutralising ADAM19 on diet induced weight gain, insulin resistance in vivo, and liver TNF-α levels. Significantly, we show that, in humans, ADAM19 strongly correlates with parameters of the metabolic syndrome, particularly BMI, relative fat, HOMA-IR, and triglycerides. Furthermore, we identified that ADAM19 expression was markedly increased in the liver and gonadal white adipose tissue of obese and T2D mice. Excitingly, we demonstrate in our diet induced obesity mouse model that neutralising ADAM19 therapy results in weight loss, improves insulin sensitivity, and reduces liver TNF-α levels. Our novel data suggest that ADAM19 is pro-obesogenic and enhances insulin resistance. Therefore, neutralisation of ADAM19 may be a potential therapeutic approach to treat obesity and T2D.

Exome sequences of multiplex, multigenerational families reveal schizophrenia risk loci with potential implications for neurocognitive performance.

Schizophrenia is a serious mental illness, involving disruptions in thought and behavior, with a worldwide prevalence of about one percent. Although highly heritable, much of the genetic liability of schizophrenia is yet to be explained. We searched for susceptibility loci in multiplex, multigenerational families affected by schizophrenia, targeting protein-altering variation with in silico predicted functional effects. Exome sequencing was performed on 136 samples from eight European-American families, including 23 individuals diagnosed with schizophrenia or schizoaffective disorder. In total, 11,878 non-synonymous variants from 6,396 genes were tested for their association with schizophrenia spectrum disorders. Pathway enrichment analyses were conducted on gene-based test results, protein-protein interaction (PPI) networks, and epistatic effects. Using a significance threshold of FDR < 0.1, association was detected for rs10941112 (p = 2.1 × 10-5 ; q-value = 0.073) in AMACR, a gene involved in fatty acid metabolism and previously implicated in schizophrenia, with significant cis effects on gene expression (p = 5.5 × 10-4 ), including brain tissue data from the Genotype-Tissue Expression project (minimum p = 6.0 × 10-5 ). A second SNP, rs10378 located in TMEM176A, also shows risk effects in the exome data (p = 2.8 × 10-5 ; q-value = 0.073). PPIs among our top gene-based association results (p < 0.05; n = 359 genes) reveal significant enrichment of genes involved in NCAM-mediated neurite outgrowth (p = 3.0 × 10-5 ), while exome-wide SNP-SNP interaction effects for rs10941112 and rs10378 indicate a potential role for kinase-mediated signaling involved in memory and learning. In conclusion, these association results implicate AMACR and TMEM176A in schizophrenia risk, whose effects may be modulated by genes involved in synaptic plasticity and neurocognitive performance.

GWAS and transcriptional analysis prioritize ITPR1 and CNTN4 for a serum uric acid 3p26 QTL in Mexican Americans.

BACKGROUND: The variation in serum uric acid concentrations is under significant genetic influence. Elevated SUA concentrations have been linked to increased risk for gout, kidney stones, chronic kidney disease, and cardiovascular disease whereas reduced serum uric acid concentrations have been linked to multiple sclerosis, Parkinson's disease and Alzheimer's disease. Previously, we identified a novel locus on chromosome 3p26 affecting serum uric acid concentrations in Mexican Americans from San Antonio Family Heart Study. As a follow up, we examined genome-wide single nucleotide polymorphism data in an extended cohort of 1281 Mexican Americans from multigenerational families of the San Antonio Family Heart Study and the San Antonio Family Diabetes/Gallbladder Study. We used a linear regression-based joint linkage/association test under an additive model of allelic effect, while accounting for non-independence among family members via a kinship variance component. RESULTS: Univariate genetic analysis indicated serum uric acid concentrations to be significant heritable (h (2) = 0.50 ± 0.05, p < 4 × 10(-35)), and linkage analysis of serum uric acid concentrations confirmed our previous finding of a novel locus on 3p26 (LOD = 4.9, p < 1 × 10(-5)) in the extended sample. Additionally, we observed strong association of serum uric acid concentrations with variants in following candidate genes in the 3p26 region; inositol 1,4,5-trisphosphate receptor, type 1 (ITPR1), contactin 4 (CNTN4), decapping mRNA 1A (DCP1A); transglutaminase 4 (TGM4) and rho guanine nucleotide exchange factor (GEF) 26 (ARHGEF26) [p < 3 × 10(-7); minor allele frequencies ranged between 0.003 and 0.42] and evidence of cis-regulation for ITPR1 transcripts. CONCLUSION: Our results confirm the importance of the chromosome 3p26 locus and genetic variants in this region in the regulation of serum uric acid concentrations.

Recurrent major depression and right hippocampal volume: A bivariate linkage and association study.

Previous work has shown that the hippocampus is smaller in the brains of individuals suffering from major depressive disorder (MDD) than those of healthy controls. Moreover, right hippocampal volume specifically has been found to predict the probability of subsequent depressive episodes. This study explored the utility of right hippocampal volume as an endophenotype of recurrent MDD (rMDD). We observed a significant genetic correlation between the two traits in a large sample of Mexican American individuals from extended pedigrees (ρg = -0.34, p = 0.013). A bivariate linkage scan revealed a significant pleiotropic quantitative trait locus on chromosome 18p11.31-32 (LOD = 3.61). Bivariate association analysis conducted under the linkage peak revealed a variant (rs574972) within an intron of the gene SMCHD1 meeting the corrected significance level (χ(2) = 19.0, p = 7.4 × 10(-5)). Univariate association analyses of each phenotype separately revealed that the same variant was significant for right hippocampal volume alone, and also revealed a suggestively significant variant (rs12455524) within the gene DLGAP1 for rMDD alone. The results implicate right-hemisphere hippocampal volume as a possible endophenotype of rMDD, and in so doing highlight a potential gene of interest for rMDD risk.

A genome-wide integrative genomic study localizes genetic factors influencing antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA-1).

Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10(-15) for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.

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

Genome-wide genetic and transcriptomic investigation of variation in antibody response to dietary antigens.

Increased immunoglobulin G (IgG) response to dietary antigens can be associated with gastrointestinal dysfunction and autoimmunity. The underlying processes contributing to these adverse reactions remain largely unknown, and it is likely that genetic factors play a role. Here, we estimate heritability and attempt to localize genetic factors influencing IgG antibody levels against food-derived antigens using an integrative genomics approach. IgG antibody levels were determined by ELISA in >1,300 Mexican Americans for the following food antigens: wheat gliadin; bovine casein; and two forms of bovine serum albumin (BSA-a and BSA-b). Pedigree-based variance components methods were used to estimate additive genetic heritability (h(2) ), perform genome-wide association analyses, and identify transcriptional signatures (based on 19,858 transcripts from peripheral blood lymphocytes). Heritability estimates were significant for all traits (0.15-0.53), and shared environment (based on shared residency among study participants) was significant for casein (0.09) and BSA-a (0.33). Genome-wide significant evidence of association was obtained only for antibody to gliadin (P = 8.57 × 10(-8) ), mapping to the human leukocyte antigen II region, with HLA-DRA and BTNL2 as the best candidate genes. Lack of association of known celiac disease risk alleles HLA-DQ2.5 and -DQ8 with antigliadin antibodies in the studied population suggests a separate genetic etiology. Significant transcriptional signatures were found for all IgG levels except BSA-b. These results demonstrate that individual genetic differences contribute to food antigen antibody measures in this population. Further investigations may elucidate the underlying immunological processes involved.

Transcriptome study of differential expression in schizophrenia.

Schizophrenia genome-wide association studies (GWAS) have identified common SNPs, rare copy number variants (CNVs) and a large polygenic contribution to illness risk, but biological mechanisms remain unclear. Bioinformatic analyses of significantly associated genetic variants point to a large role for regulatory variants. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using microarrays on lymphoblastoid cell lines (LCLs) from 413 cases and 446 controls. Regression analysis identified 95 transcripts differentially expressed by affection status at a genome-wide false discovery rate (FDR) of 0.05, while simultaneously controlling for confounding effects. These transcripts represented 89 genes with functions such as neurotransmission, gene regulation, cell cycle progression, differentiation, apoptosis, microRNA (miRNA) processing and immunity. This functional diversity is consistent with schizophrenia's likely significant pathophysiological heterogeneity. The overall enrichment of immune-related genes among those differentially expressed by affection status is consistent with hypothesized immune contributions to schizophrenia risk. The observed differential expression of extended major histocompatibility complex (xMHC) region histones (HIST1H2BD, HIST1H2BC, HIST1H2BH, HIST1H2BG and HIST1H4K) converges with the genetic evidence from GWAS, which find the xMHC to be the most significant susceptibility locus. Among the differentially expressed immune-related genes, B3GNT2 is implicated in autoimmune disorders previously tied to schizophrenia risk (rheumatoid arthritis and Graves' disease), and DICER1 is pivotal in miRNA processing potentially linking to miRNA alterations in schizophrenia (e.g. MIR137, the second strongest GWAS finding). Our analysis provides novel candidate genes for further study to assess their potential contribution to schizophrenia.

Genome-wide significant linkage of schizophrenia-related neuroanatomical trait to 12q24.

The insula and medial prefrontal cortex (mPFC) share functional, histological, transcriptional, and developmental characteristics, and they serve higher cognitive functions of theoretical relevance to schizophrenia and related disorders. Meta-analyses and multivariate analysis of structural magnetic resonance imaging (MRI) scans indicate that gray matter density and volume reductions in schizophrenia are the most consistent and pronounced in a network primarily composed of the insula and mPFC. We used source-based morphometry, a multivariate technique optimized for structural MRI, in a large sample of randomly ascertained pedigrees (N = 887) to derive an insula-mPFC component and to investigate its genetic determinants. Firstly, we replicated the insula-mPFC gray matter component as an independent source of gray matter variation in the general population, and verified its relevance to schizophrenia in an independent case-control sample. Secondly, we showed that the neuroanatomical variation defined by this component is largely determined by additive genetic variation (h(2) = 0.59), and genome-wide linkage analysis resulted in a significant linkage peak at 12q24 (LOD = 3.76). This region has been of significant interest to psychiatric genetics as it contains the Darier's disease locus and other proposed susceptibility genes (e.g., DAO, NOS1), and it has been linked to affective disorders and schizophrenia in multiple populations. Thus, in conjunction with previous clinical studies, our data imply that one or more psychiatric risk variants at 12q24 are co-inherited with reductions in mPFC and insula gray matter concentration. © 2015 Wiley Periodicals, Inc.