Todd M. Darlington

Genetic risk factors in two Utah pedigrees at high risk for suicide

We have used unique population-based data resources to identify 22 high-risk extended pedigrees that show clustering of suicide over twice that expected from demographically adjusted incidence rates. In this initial study of genetic risk factors, we focused on two high-risk pedigrees. In the first of these (pedigree 12), 10/19 (53%) of the related suicides were female, and the average age at death was 30.95. In the second (pedigree 5), 7/51 (14%) of the suicides were female and the average age at death was 36.90. Six decedents in pedigree 12 and nine in pedigree 5 were genotyped with the Illumina HumanExome BeadChip. Genotypes were analyzed using the Variant Annotation, Analysis, and Search program package that computes likelihoods of risk variants using the functional impact of the DNA variation, aggregative scoring of multiple variants across each gene and pedigree structure. We prioritized variants that were: (1) shared across pedigree members, (2) rare in other Utah suicides not related to these pedigrees, (3) ⩽ 5% in genotyping data from 398 other Utah population controls and (4) ⩽5% frequency in publicly available sequence data from 1358 controls and/or in dbSNP. Results included several membrane protein genes (ANO5, and TMEM141 for pedigree 12 and FAM38A and HRCT1 for pedigree 5). Other genes with known neuronal involvement and/or previous associations with psychiatric conditions were also identified, including NFKB1, CASP9, PLXNB1 and PDE11A in pedigree 12, and THOC1, and AUTS2 in pedigree 5. Although the study is limited to variants included on the HumanExome BeadChip, these findings warrant further exploration, and demonstrate the utility of this high-risk pedigree resource to identify potential genes or gene pathways for future development of targeted interventions.

Mesolimbic transcriptional response to hedonic substitution of voluntary exercise and voluntary ethanol consumption.

The mesolimbic dopaminergic pathway has been implicated in many rewarding behaviors, including the consumption of ethanol and voluntary exercise. It has become apparent that different rewarding stimuli activate this pathway, and therefore it is possible for these behaviors to influence each other, i.e. hedonic substitution. Using adult female C57BL/6J mice, we demonstrate that voluntary access to a running wheel substantially reduces the consumption and preference of ethanol. Furthermore, we examined gene expression of several genes involved in regulating the mesolimbic dopaminergic pathway, which we hypothesized to be the main pathway involved in hedonic substitution. In the striatum, we observed a reduction in mRNA expression of Drd1a due to exercise. Hippocampal Bdnf mRNA increased in response to exercise and decreased in response to ethanol. Furthermore, there was an interaction effect of exercise and ethanol on the expression of Slc18a2 in the midbrain. These data suggest an important role for this pathway, and especially for Bdnf and Slc18a2 in regulating hedonic substitution.

Transcriptome analysis of Inbred Long Sleep and Inbred Short Sleep mice

Many studies have utilized the Inbred Long Sleep and Inbred Short Sleep mouse strains to model the genetic influence on initial sensitivity to ethanol. The mechanisms underlying this divergent phenotype are still not completely understood. In this study, we attempt to identify genes that are differentially expressed between these two strains and to identify baseline networks of co‐expressed genes, which may provide insight regarding their phenotypic differences. We examined the whole brain and striatal transcriptomes of both strains, using next generation RNA sequencing techniques. Many genes were differentially expressed between strains, including several in chromosomal regions previously shown to influence initial sensitivity to ethanol. These results are in concordance with a similar sample of striatal transcriptomes measured using microarrays. In addition to the higher dynamic range, RNA‐Seq is not hindered by high background noise or polymorphisms in probesets as with microarray technology, and we are able to analyze exome sequence of abundant genes. Furthermore, utilizing Weighted Gene Co‐expression Network Analysis, we identified several modules of co‐expressed genes corresponding to strain differences. Several candidate genes were identified, including protein phosphatase 1 regulatory unit 1b (Ppp1r1b), prodynorphin (Pdyn), proenkephalin (Penk), ras association (RalGDS/AF‐6) domain family member 2 (Rassf2), myosin 1d (Myo1d) and transthyretin (Ttr). In addition, we propose a role for potassium channel activity as well as map kinase signaling in the observed phenotypic differences between the two strains.

Voluntary wheel running reduces voluntary consumption of ethanol in mice: identification of candidate genes through striatal gene expression profiling.

Hedonic substitution, where wheel running reduces voluntary ethanol consumption, has been observed in prior studies. Here, we replicate and expand on previous work showing that mice decrease voluntary ethanol consumption and preference when given access to a running wheel. While earlier work has been limited mainly to behavioral studies, here we assess the underlying molecular mechanisms that may account for this interaction. From four groups of female C57BL/6J mice (control, access to two‐bottle choice ethanol, access to a running wheel, and access to both two‐bottle choice ethanol and a running wheel), mRNA‐sequencing of the striatum identified differential gene expression. Many genes in ethanol preference quantitative trait loci were differentially expressed due to running. Furthermore, we conducted Weighted Gene Co‐expression Network Analysis and identified gene networks corresponding to each effect behavioral group. Candidate genes for mediating the behavioral interaction between ethanol consumption and wheel running include multiple potassium channel genes, Oprm1, Prkcg, Stxbp1, Crhr1, Gabra3, Slc6a13, Stx1b, Pomc, Rassf5 and Camta2. After observing an overlap of many genes and functional groups previously identified in studies of initial sensitivity to ethanol, we hypothesized that wheel running may induce a change in sensitivity, thereby affecting ethanol consumption. A behavioral study examining Loss of Righting Reflex to ethanol following exercise trended toward supporting this hypothesis. These data provide a rich resource for future studies that may better characterize the observed transcriptional changes in gene networks in response to ethanol consumption and wheel running.

Combined genome-wide linkage and targeted association analysis of head circumference in autism spectrum disorder families

BackgroundIt has long been recognized that there is an association between enlarged head circumference (HC) and autism spectrum disorder (ASD), but the genetics of HC in ASD is not well understood. In order to investigate the genetic underpinning of HC in ASD, we undertook a genome-wide linkage study of HC followed by linkage signal targeted association among a sample of 67 extended pedigrees with ASD.MethodsHC measurements on members of 67 multiplex ASD extended pedigrees were used as a quantitative trait in a genome-wide linkage analysis. The Illumina 6K SNP linkage panel was used, and analyses were carried out using the SOLAR implemented variance components model. Loci identified in this way formed the target for subsequent association analysis using the Illumina OmniExpress chip and imputed genotypes. A modification of the qTDT was used as implemented in SOLAR.ResultsWe identified a linkage signal spanning 6p21.31 to 6p22.2 (maximum LOD = 3.4). Although targeted association did not find evidence of association with any SNP overall, in one family with the strongest evidence of linkage, there was evidence for association (rs17586672, p = 1.72E−07).ConclusionsAlthough this region does not overlap with ASD linkage signals in these same samples, it has been associated with other psychiatric risk, including ADHD, developmental dyslexia, schizophrenia, specific language impairment, and juvenile bipolar disorder. The genome-wide significant linkage signal represents the first reported observation of a potential quantitative trait locus for HC in ASD and may be relevant in the context of complex multivariate risk likely leading to ASD.

Novel pedigree analysis implicates DNA repair and chromatin remodeling in multiple myeloma risk

The high-risk pedigree (HRP) design is an established strategy to discover rare, highly-penetrant, Mendelian-like causal variants. Its success, however, in complex traits has been modest, largely due to challenges of genetic heterogeneity and complex inheritance models. We describe a HRP strategy that addresses intra-familial heterogeneity, and identifies inherited segments important for mapping regulatory risk. We apply this new Shared Genomic Segment (SGS) method in 11 extended, Utah, multiple myeloma (MM) HRPs, and subsequent exome sequencing in SGS regions of interest in 1063 MM / MGUS (monoclonal gammopathy of undetermined significance–a precursor to MM) cases and 964 controls from a jointly-called collaborative resource, including cases from the initial 11 HRPs. One genome-wide significant 1.8 Mb shared segment was found at 6q16. Exome sequencing in this region revealed predicted deleterious variants in USP45 (p.Gln691* and p.Gln621Glu), a gene known to influence DNA repair through endonuclease regulation. Additionally, a 1.2 Mb segment at 1p36.11 is inherited in two Utah HRPs, with coding variants identified in ARID1A (p.Ser90Gly and p.Met890Val), a key gene in the SWI/SNF chromatin remodeling complex. Our results provide compelling statistical and genetic evidence for segregating risk variants for MM. In addition, we demonstrate a novel strategy to use large HRPs for risk-variant discovery more generally in complex traits.

Genome-wide association study of suicide death: Results from the first wave of Utah completed suicide data

Objective Suicide death is a highly preventable, yet growing, worldwide health crisis. To date, there has been a lack of adequately powered genomic studies of suicide, with no sizeable suicide death cohorts available for study. To address this limitation, we conducted the first comprehensive genomic analysis of suicide death, using a previously unpublished suicide cohort. Methods The analysis sample consisted of 3,413 population-ascertained cases of European ancestry and 14,810 ancestrally matched controls. Analytical methods included principle components analysis for ancestral matching and adjusting for population stratification, linear mixed model genome-wide association testing (conditional on genetic relatedness matrix), gene and gene set enrichment testing, polygenic score analyses, as well as SNP heritability and genetic correlation estimation using LD score regression. Results GWAS identified two genome-wide significant loci (6 SNPs, p<5×10−8). Gene-based analyses implicated 19 genes on chromosomes 13, 15, 16, 17, and 19 (q<0.05). Suicide heritability was estimated h2 =0.2463, SE = 0.0356 using summary statistics from a multivariate logistic GWAS adjusting for ancestry. Notably, suicide polygenic scores were robustly predictive of out of sample suicide death, as were polygenic scores for several other psychiatric disorders and psychological traits, particularly behavioral disinhibition and major depressive disorder. Conclusions In this report, we identify multiple genome-wide significant loci/genes, and demonstrate robust polygenic score prediction of suicide death case-control status, adjusting for ancestry, in independent training and test sets. Additionally, we report that suicide death cases have increased genetic risk for behavioral disinhibition, major depression, autism spectrum disorder, psychosis, and alcohol use disorder relative to controls. Results demonstrate the ability of polygenic scores to robustly, and multidimensionally, predict suicide death case-control status.Background: Heritability of suicide risk is estimated at 43%, thus genetic risk likely plays an important role in completion of suicide. Previous genetic research has focused primarily on suicidal behavior or ideation rather than actual completed suicide. And previous genome-wide association studies of completion of suicide have been very small due to the difficulty in obtaining suicide sample data, and have been unable to identify genome-wide significant variants, likely due to power limitations. This study presents results from the first wave of a large Utah sample of completed suicides, and represent the most statistically powerful sample of completed suicide to date. Methods: Tissue samples from 1321 decedents were collected via partnership with the Utah Office of the Medical Examiner and genotyped using the Illumina Infinium PsychArray platform. Bioconductor package RaMWAS (A.S.) was used on post-QC hard call data (271,894 common variants) to conduct GWAS. Because the sample is from Utah, the authors were able to conduct a relatively direct comparison with 1000 Genomes controls also from Utah (CEU), as well as European controls (EUR). The first GWAS with Utah CEU controls (n of only 99) was followed by a second GWAS with EUR controls (n = 503) with and without CEU included in the control sample. Results: Analyses identified 8 SNPs in 6 genes associated with the completion of suicide. Six SNPs met genome-widesignificanceat5x10- 8 .Two of these variant hits were replicated using EUR controls not including the CEU sample, though the case sample was the same in both analyses. Subsequent QC steps (linkage disequilibrium analysis and EUR GWAS replication) further substantiated significant results implicating cytochrome P450 genes. Conclusions: This GWAS and partial replication of findings across control samples, using hard call genotype data, represents a significant step toward understanding the genetic architecture of suicide. These are late breaking results, and in January this group will follow up with analyses using the full 2 waves (N = 4800 cases), a far larger control group, and imputed data to ~11 million variants. Analyses to date implicate cytochrome P450 sites involved in metabolism of arachidonic acid and related inflammatory mediators. Results implicate inflammation in suicide risk, and also add to the growing body of evidence that lung function may be tied to suicide.

Genome-wide significant regions in 43 Utah high-risk families implicate multiple genes involved in risk for completed suicide

Suicide is the 10th leading cause of death in the United States. Although environment has undeniable impact, evidence suggests that genetic factors play a significant role in completed suicide. We linked a resource of ~ 4500 DNA samples from completed suicides obtained from the Utah Medical Examiner to genealogical records and medical records data available on over eight million individuals. This linking has resulted in the identification of high-risk extended families (7–9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed Illumina PsychArray genotypes from suicide cases in 43 high-risk families, identifying 30 distinct shared genomic segments with genome-wide evidence (p = 2.02E-07–1.30E-18) of segregation with completed suicide. The 207 genes implicated by the shared regions provide a focused set of genes for further study; 18 have been previously associated with suicide risk. Although PsychArray variants do not represent exhaustive variation within the 207 genes, we investigated these for specific segregation within the high-risk families, and for association of variants with predicted functional impact in ~ 1300 additional Utah suicides unrelated to the discovery families. None of the limited PsychArray variants explained the high-risk family segregation; sequencing of these regions will be needed to discover segregating risk variants, which may be rarer or regulatory. However, additional association tests yielded four significant PsychArray variants (SP110, rs181058279; AGBL2, rs76215382; SUCLA2, rs121908538; APH1B, rs745918508), raising the likelihood that these genes confer risk of completed suicide.

Identification of genome-wide significant shared genomic segments in large extended Utah families at high risk for completed suicide

Suicide is the 10th leading cause of death in the US. While environment has undeniable impact, evidence suggests genetic factors play a significant role in completed suicide. We linked a resource of >4,500 DNA samples from completed suicides obtained from the Utah Medical Examiner to genealogical records and medical records data available on over 8 million individuals. This linking has resulted in the identification of high-risk extended families (7-9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed Illumina PsychArray genotypes from suicide cases in 43 high-risk families, identifying 30 distinct shared genomic segments with genome-wide evidence (p=2.02E-07 to 1.30E-18) of segregation with completed suicide. The 207 genes implicated by the shared regions provide a focused set of genes for further study; 18 have been previously associated with suicide risk. While PsychArray variants do not represent exhaustive variation within the 207 genes, we investigated these for specific segregation within the high-risk families, and for association of variants with predicted functional impact in ~1300 additional Utah suicides unrelated to the discovery families. None of the limited PsychArray variants explained the high-risk family segregation; sequencing of these regions will be needed to discover segregating risk variants, which may be rarer or regulatory. However, additional association tests yielded four significant PsychArray variants (SP110, rs181058279; AGBL2, rs76215382; SUCLA2, rs121908538; APH1B, rs745918508), raising the likelihood that these genes confer risk of completed suicide.Suicide is the 10th leading cause of death in the US. While environment has undeniable impact, evidence suggests that genetic factors play a major role in completed suicide. We have >4,500 DNA samples from completed suicides through a collaboration with the Utah Medical Examiner. We have linked the records from these cases to the Utah Population Database which includes multi-generation genealogies, demographic data, and medical information on over 8 million individuals. This linking has resulted in extended families (7-9 generations) with significant familial risk of completed suicide. Familial aggregation across distant relatives minimizes effects of shared environment, provides more genetically homogeneous risk groups, and magnifies genetic risks through familial repetition. We analyzed DNA from 215 suicide cases in 43 of our largest high-risk families and identified 16 regions with genome-wide significance in 10 families. Of the 163 genes in these regions, 25% were associated with psychiatric risk. We also found 13 regions with genome-wide suggestive evidence where the region overlaps in >1 family (p-values from 4.63E-09 to

High-risk Autism Spectrum Disorder Utah pedigrees: a novel Shared Genomic Segments analysis.

Progress in gene discovery for Autism Spectrum Disorder (ASD) has been rapid over the past decade, with major successes in validation of risk of predominantly rare, penetrant, de novo and inherited mutations in over 100 genes (de Rubies et al., 2015; Sanders et al., 2015). However, the majority of individuals with ASD diagnoses do not carry a rare, penetrant genetic risk factor. In fact, recent estimates suggest that most of the genetic liability of ASD is due to as yet undiscovered common, less penetrant inherited variation (Gaugler et al., 2014) which is much more difficult to detect. The study of extended, high-risk families adds significant information in our search for these common inherited risk factors. Here, we present results of a new, powerful pedigree analysis method (Shared Genomic Segments—SGS) on three large families from the Utah Autism Research Program. The method improves upon previous methods by allowing for within-family heterogeneity, and identifying exact region boundaries and subsets of cases who share for targeted follow-up analyses. Our SGS analyses identified one genome-wide significant shared segment on chromosome 17 (q21.32, p=1.47x10-8). Additional regions with suggestive evidence were identified on chromosomes 3, 4, 6, 8, 11, 13, 14, 15, and 18. Several of these segments showed evidence of sharing across families. Genes of interest in these regions include ATP8A1, DOCK3, CACNA2D2, ITGB3, AMBRA1, FOLH1, DGKZ, MTHFS, ARNT2, BTN2A2, BTN3A1, BTN3A3, BTN2A1, and BTN1A1. We are exploring multiple other lines of evidence to follow up these implicated regions and genes.