Browsing by Author "Budde, John P."

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    A genome wide association study of alcohol dependence symptom counts in extended pedigrees identifies C15orf53
    (Springer Nature, 2013) Wang, Jen-Chyong; Foroud, Tatiana; Hinrichs, Anthony L.; Le, Nhung X. H.; Bertelsen, Sarah; Budde, John P.; Harari, Oscar; Koller, Daniel L.; Wetherill, Leah; Agrawal, Arpana; Almasy, Laura; Brooks, Andrew I.; Bucholz, Kathleen; Dick, Danielle; Hesselbrock, Victor; Johnson, Eric O.; Kang, Sun; Kapoor, Manav; Kramer, John; Kuperman, Samuel; Madden, Pamela A. F.; Manz, Niklas; Martin, Nicholas G.; McClintick, Jeanette N.; Montgomery, Grant W.; Nurnberger, John I., Jr.; Rangaswamy, Madhavi; Rice, John; Schuckit, Marc; Tischfield, Jay A.; Whitfield, John B.; Xuei, Xiaoling; Porjesz, Bernice; Heath, Andrew C.; Edenberg, Howard J.; Bierut, Laura J.; Goate, Alison M.; Medical and Molecular Genetics, School of Medicine
    Several studies have identified genes associated with alcohol-use disorders (AUDs), but the variation in each of these genes explains only a small portion of the genetic vulnerability. The goal of the present study was to perform a genome-wide association study (GWAS) in extended families from the Collaborative Study on the Genetics of Alcoholism to identify novel genes affecting risk for alcohol dependence (AD). To maximize the power of the extended family design, we used a quantitative endophenotype, measured in all individuals: number of alcohol-dependence symptoms endorsed (symptom count (SC)). Secondary analyses were performed to determine if the single nucleotide polymorphisms (SNPs) associated with SC were also associated with the dichotomous phenotype, DSM-IV AD. This family-based GWAS identified SNPs in C15orf53 that are strongly associated with DSM-IV alcohol-dependence symptom counts (P=4.5 × 10(-8), inflation-corrected P=9.4 × 10(-7)). Results with DSM-IV AD in the regions of interest support our findings with SC, although the associations were less significant. Attempted replications of the most promising association results were conducted in two independent samples: nonoverlapping subjects from the Study of Addiction: Genes and Environment (SAGE) and the Australian Twin Family Study of AUDs (OZALC). Nominal association of C15orf53 with SC was observed in SAGE. The variant that showed strongest association with SC, rs12912251 and its highly correlated variants (D'=1, r(2) 0.95), have previously been associated with risk for bipolar disorder.
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    Circular RNA detection identifies circPSEN1 alterations in brain specific to autosomal dominant Alzheimer's disease
    (BMC, 2022-03-04) Chen, Hsiang‑Han; Eteleeb, Abdallah; Wang, Ciyang; Fernandez, Maria Victoria; Budde, John P.; Bergmann, Kristy; Norton, Joanne; Wang, Fengxian; Ebl, Curtis; Morris, John C.; Perrin, Richard J.; Bateman, Randall J.; McDade, Eric; Xiong, Chengjie; Goate, Alison; Farlow, Martin; Chhatwal, Jasmeer; Schofield, Peter R.; Chui, Helena; Harari, Oscar; Cruchaga, Carlos; Ibanez, Laura; Dominantly Inherited Alzheimer Network; Neurology, School of Medicine
    Background: Autosomal-dominant Alzheimer's disease (ADAD) is caused by pathogenic mutations in APP, PSEN1, and PSEN2, which usually lead to an early age at onset (< 65). Circular RNAs are a family of non-coding RNAs highly expressed in the nervous system and especially in synapses. We aimed to investigate differences in brain gene expression of linear and circular transcripts from the three ADAD genes in controls, sporadic AD, and ADAD. Methods: We obtained and sequenced RNA from brain cortex using standard protocols. Linear counts were obtained using the TOPMed pipeline; circular counts, using python package DCC. After stringent quality control (QC), we obtained the counts for PSEN1, PSEN2 and APP genes. Only circPSEN1 passed QC. We used DESeq2 to compare the counts across groups, correcting for biological and technical variables. Finally, we performed in-silico functional analyses using the Circular RNA interactome website and DIANA mirPath software. Results: Our results show significant differences in gene counts of circPSEN1 in ADAD individuals, when compared to sporadic AD and controls (ADAD = 21, AD = 253, Controls = 23-ADADvsCO: log2FC = 0.794, p = 1.63 × 10-04, ADADvsAD: log2FC = 0.602, p = 8.22 × 10-04). The high gene counts are contributed by two circPSEN1 species (hsa_circ_0008521 and hsa_circ_0003848). No significant differences were observed in linear PSEN1 gene expression between cases and controls, indicating that this finding is specific to the circular forms. In addition, the high circPSEN1 levels do not seem to be specific to PSEN1 mutation carriers; the counts are also elevated in APP and PSEN2 mutation carriers. In-silico functional analyses suggest that circPSEN1 is involved in several pathways such as axon guidance (p = 3.39 × 10-07), hippo signaling pathway (p = 7.38 × 10-07), lysine degradation (p = 2.48 × 10-05) or Wnt signaling pathway (p = 5.58 × 10-04) among other KEGG pathways. Additionally, circPSEN1 counts were able to discriminate ADAD from sporadic AD and controls with an AUC above 0.70. Conclusions: Our findings show the differential expression of circPSEN1 is increased in ADAD. Given the biological function previously ascribed to circular RNAs and the results of our in-silico analyses, we hypothesize that this finding might be related to neuroinflammatory events that lead or that are caused by the accumulation of amyloid-beta.
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    Cis-Regulatory Variants Affect CHRNA5 mRNA Expression in Populations of African and European Ancestry
    (Public Library of Science, 2013-11-26) Wang, Jen-Chyong; Spiegel, Noah; Bertelsen, Sarah; Le, Nhung; McKenna, Nicholas; Budde, John P.; Harari, Oscar; Kapoor, Manav; Brooks, Andrew; Hancock, Dana; Tischfield, Jay; Foroud, Tatiana; Bierut, Laura J.; Steinbach, Joe Henry; Edenberg, Howard J.; Traynor, Bryan J.; Goate, Alison M.; Medical and Molecular Genetics, School of Medicine
    Variants within the gene cluster encoding α3, α5, and β4 nicotinic receptor subunits are major risk factors for substance dependence. The strongest impact on risk is associated with variation in the CHRNA5 gene, where at least two mechanisms are at work: amino acid variation and altered mRNA expression levels. The risk allele of the non-synonymous variant (rs16969968; D398N) primarily occurs on the haplotype containing the low mRNA expression allele. In populations of European ancestry, there are approximately 50 highly correlated variants in the CHRNA5-CHRNA3-CHRNB4 gene cluster and the adjacent PSMA4 gene region that are associated with CHRNA5 mRNA levels. It is not clear which of these variants contribute to the changes in CHRNA5 transcript level. Because populations of African ancestry have reduced linkage disequilibrium among variants spanning this gene cluster, eQTL mapping in subjects of African ancestry could potentially aid in defining the functional variants that affect CHRNA5 mRNA levels. We performed quantitative allele specific gene expression using frontal cortices derived from 49 subjects of African ancestry and 111 subjects of European ancestry. This method measures allele-specific transcript levels in the same individual, which eliminates other biological variation that occurs when comparing expression levels between different samples. This analysis confirmed that substance dependence associated variants have a direct cis-regulatory effect on CHRNA5 transcript levels in human frontal cortices of African and European ancestry and identified 10 highly correlated variants, located in a 9 kb region, that are potential functional variants modifying CHRNA5 mRNA expression levels.
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    CYP2A6 metabolism in the development of smoking behaviors in young adults
    (Wiley, 2018-01) Olfson, Emily; Bloom, Joseph; Bertelsen, Sarah; Budde, John P.; Breslau, Naomi; Brooks, Andrew; Culverhouse, Robert; Chan, Grace; Chen, Li-Shiun; Chorlian, David; Dick, Danielle M.; Edenberg, Howard J.; Hartz, Sarah; Hatsukami, Dorothy; Hesselbrock, Victor M.; Johnson, Eric O.; Kramer, John R.; Kuperman, Samuel; Meyers, Jacquelyn L.; Nurnberger, John; Porjesz, Bernice; Saccone, Nancy L.; Schuckit, Marc A.; Stitzel, Jerry; Tischfield, Jay A.; Rice, John P.; Goate, Alison; Bierut, Laura J.; Biochemistry and Molecular Biology, School of Medicine
    Cytochrome P450 2A6 (CYP2A6) encodes the enzyme responsible for the majority of nicotine metabolism. Previous studies support that slow metabolizers smoke fewer cigarettes once nicotine dependent but provide conflicting results on the role of CYP2A6 in the development of dependence. By focusing on the critical period of young adulthood, this study examines the relationship of CYP2A6 variation and smoking milestones. A total of 1209 European American young adults enrolled in the Collaborative Study on the Genetics of Alcoholism were genotyped for CYP2A6 variants to calculate a previously well-validated metric that estimates nicotine metabolism. This metric was not associated with the transition from never smoking to smoking initiation nor with the transition from initiation to daily smoking (P > 0.4). But among young adults who had become daily smokers (n = 506), decreased metabolism was associated with increased risk of nicotine dependence (P = 0.03) (defined as Fagerström Test for Nicotine Dependence score ≥4). This finding was replicated in the Collaborative Genetic Study of Nicotine Dependence with 335 young adult daily smokers (P = 0.02). Secondary meta-analysis indicated that slow metabolizers had a 53 percent increased odds (OR = 1.53, 95 percent CI 1.11-2.11, P = 0.009) of developing nicotine dependence compared with normal metabolizers. Furthermore, secondary analyses examining four-level response of time to first cigarette after waking (>60, 31-60, 6-30, ≤5 minutes) demonstrated a robust effect of the metabolism metric in Collaborative Study on the Genetics of Alcoholism (P = 0.03) and Collaborative Genetic Study of Nicotine Dependence (P = 0.004), illustrating the important role of this measure of dependence. These findings highlight the complex role of CYP2A6 variation across different developmental stages of smoking behaviors.
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    Metabolomic and lipidomic signatures in autosomal dominant and late-onset Alzheimer's disease brains
    (Wiley, 2023) Novotny, Brenna C.; Fernandez, Maria Victoria; Wang, Ciyang; Budde, John P.; Bergmann, Kristy; Eteleeb, Abdallah M.; Bradley, Joseph; Webster, Carol; Ebl, Curtis; Norton, Joanne; Gentsch, Jen; Dube, Umber; Wang, Fengxian; Morris, John C.; Bateman, Randall J.; Perrin, Richard J.; McDade, Eric; Xiong, Chengjie; Chhatwal, Jasmeer; Dominantly Inherited Alzheimer Network (DIAN) Study Group; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's Disease Metabolomics Consortium (ADMC); Goate, Alison; Farlow, Martin; Schofield, Peter; Chui, Helena; Karch, Celeste M.; Cruchaga, Carlos; Benitez, Bruno A.; Harari, Oscar; Neurology, School of Medicine
    Introduction: The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain. Methods: We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ɛ4, and TREM2 risk variant carriers, and sporadic AD (sAD). Results: We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration. Discussion: AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation. Highlights: APP/PSEN1/PSEN2 and TREM2 variant carriers show distinct metabolic changes. A total of 133 metabolites were differentially abundant in AD genetic groups. β-citrylglutamate is differentially abundant in autosomal dominant, TREM2, and sporadic AD. A 16-metabolite profile shows differences between Alzheimer's disease (AD) genetic groups. The identified metabolic profile is associated with duration of disease.
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    Single-nucleus RNA-sequencing of autosomal dominant Alzheimer disease and risk variant carriers
    (Springer Nature, 2023-04-21) Brase, Logan; You, Shih-Feng; D'Oliveira Albanus, Ricardo; Del-Aguila, Jorge L.; Dai, Yaoyi; Novotny, Brenna C.; Soriano-Tarraga, Carolina; Dykstra, Taitea; Fernandez, Maria Victoria; Budde, John P.; Bergmann, Kristy; Morris, John C.; Bateman, Randall J.; Perrin, Richard J.; McDade, Eric; Xiong, Chengjie; Goate, Alison M.; Farlow, Martin; Dominantly Inherited Alzheimer Network (DIAN); Sutherland, Greg T.; Kipnis, Jonathan; Karch, Celeste M.; Benitez, Bruno A.; Harari, Oscar; Neurology, School of Medicine
    Genetic studies of Alzheimer disease (AD) have prioritized variants in genes related to the amyloid cascade, lipid metabolism, and neuroimmune modulation. However, the cell-specific effect of variants in these genes is not fully understood. Here, we perform single-nucleus RNA-sequencing (snRNA-seq) on nearly 300,000 nuclei from the parietal cortex of AD autosomal dominant (APP and PSEN1) and risk-modifying variant (APOE, TREM2 and MS4A) carriers. Within individual cell types, we capture genes commonly dysregulated across variant groups. However, specific transcriptional states are more prevalent within variant carriers. TREM2 oligodendrocytes show a dysregulated autophagy-lysosomal pathway, MS4A microglia have dysregulated complement cascade genes, and APOEε4 inhibitory neurons display signs of ferroptosis. All cell types have enriched states in autosomal dominant carriers. We leverage differential expression and single-nucleus ATAC-seq to map GWAS signals to effector cell types including the NCK2 signal to neurons in addition to the initially proposed microglia. Overall, our results provide insights into the transcriptional diversity resulting from AD genetic architecture and cellular heterogeneity. The data can be explored on the online browser (http://web.hararilab.org/SNARE/).