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Item An endophenotype approach to the genetics of alcohol dependence: a genome wide association study of fast beta EEG in families of African ancestry(Nature Publishing Group, 2017-12) Meyers, JL; Zhang, J; Wang, JC; Su, J; Kuo, SI; Kapoor, M; Wetherill, L; Bertelsen, S; Lai, D; Salvatore, JE; Kamarajan, C; Chorlian, D; Agrawal, A; Almasy, L; Bauer, L; Bucholz, KK; Chan, G; Hesselbrock, V; Koganti, L; Kramer, J; Kuperman, S; Manz, N; Pandey, A; Seay, M; Scott, D; Taylor, RE; Dick, DM; Edenberg, HJ; Goate, A; Foroud, T; Porjesz, B; Medical and Molecular Genetics, School of MedicineFast beta (20-28 Hz) electroencephalogram (EEG) oscillatory activity may be a useful endophenotype for studying the genetics of disorders characterized by neural hyperexcitability, including substance use disorders (SUDs). However, the genetic underpinnings of fast beta EEG have not previously been studied in a population of African-American ancestry (AA). In a sample of 2382 AA individuals from 482 families drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a genome-wide association study (GWAS) on resting-state fast beta EEG power. To further characterize our genetic findings, we examined the functional and clinical/behavioral significance of GWAS variants. Ten correlated single-nucleotide polymorphisms (SNPs) (r2>0.9) located in an intergenic region on chromosome 3q26 were associated with fast beta EEG power at P<5 × 10-8. The most significantly associated SNP, rs11720469 (β: -0.124; P<4.5 × 10-9), is also an expression quantitative trait locus for BCHE (butyrylcholinesterase), expressed in thalamus tissue. Four of the genome-wide SNPs were also associated with Diagnostic and Statistical Manual of Mental Disorders Alcohol Dependence in COGA AA families, and two (rs13093097, rs7428372) were replicated in an independent AA sample (Gelernter et al.). Analyses in the AA adolescent/young adult (offspring from COGA families) subsample indicated association of rs11720469 with heavy episodic drinking (frequency of consuming 5+ drinks within 24 h). Converging findings presented in this study provide support for the role of genetic variants within 3q26 in neural and behavioral disinhibition. These novel genetic findings highlight the importance of including AA populations in genetics research on SUDs and the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.Item Endophenotype-based in silico network medicine discovery combined with insurance record data mining identifies sildenafil as a candidate drug for Alzheimer’s disease(Springer Nature, 2021) Fang, Jiansong; Zhang, Pengyue; Zhou, Yadi; Chiang, Chien-Wei; Tan, Juan; Hou, Yuan; Stauffer, Shaun; Li, Lang; Pieper, Andrew A.; Cummings, Jeffrey; Cheng, Feixiong; Biostatistics and Health Data Science, School of MedicineWe developed an endophenotype disease module-based methodology for Alzheimer's disease (AD) drug repurposing and identified sildenafil as a potential disease risk modifier. Based on retrospective case-control pharmacoepidemiologic analyses of insurance claims data for 7.23 million individuals, we found that sildenafil usage was significantly associated with a 69% reduced risk of AD (hazard ratio = 0.31, 95% confidence interval 0.25-0.39, P<1.0×10-8). Propensity score stratified analyses confirmed that sildenafil is significantly associated with a decreased risk of AD across all four drug cohorts we tested (diltiazem, glimepiride, losartan and metformin) after adjusting age, sex, race, and disease comorbidities. We also found that sildenafil increases neurite growth and decreases phospho-tau expression in AD patient-induced pluripotent stem cells-derived neuron models, supporting mechanistically its potential beneficial effect in Alzheimer's disease. The association between sildenafil use and decreased incidence of AD does not establish causality or its direction, which requires a randomized clinical trial approach.Item Further Analyses of Genetic Association Between GRM8 and Alcohol Dependence Symptoms Among Young Adults(Rutgers Center of Alcohol Studies, 2015-05) Long, Elizabeth C.; Aliev, Fazil; Wang, Jen-Chyong; Edenberg, Howard J.; Nurnberger Jr., John; Hesselbrock, Victor; Porjesz, Bernice; Dick, Danielle M.; Department of Biochemistry & Molecular Biology, IU School of MedicineObjective: The gene GRM8, a metabotropic glutamate receptor, has emerged as a gene of interest for its possible role in the development of alcohol dependence, with evidence of association with an electrophysiological endophenotype and level of response to alcohol as well as suggestive evidence of association with alcohol dependence. Method: The present study further investigated the association between GRM8 and alcohol dependence symptom counts among young adults using a new sample of individuals collected as part of the prospective sample (ages 18–26 years; N = 842) from the Collaborative Study on the Genetics of Alcoholism (COGA). Results: Two single-nucleotide polymorphisms were significantly associated with alcohol dependence in European Americans using the Nyholt corrected p value of .007: rs886003 (β = -.212, p = .0002) and rs17862325 (β = -.234, p < .0001), but not in African Americans, likely because of the lower power to detect association in this group. Conclusions: These results further implicate the role of glutamate receptor genes such as GRM8 in the development of alcohol dependence.Item Genetic and environment effects on structural neuroimaging endophenotype for bipolar disorder: a novel molecular approach(Springer Nature, 2022-04-04) Hu, Bo; Cha, Jungwon; Fullerton, Janice M.; Hesam-Shariati, Sonia; Nakamura, Kunio; Nurnberger, John I.; Anand, Amit; Psychiatry, School of MedicineWe investigated gene-environment effects on structural brain endophenotype in bipolar disorder (BD) using a novel method of combining polygenic risk scores with epigenetic signatures since traditional methods of examining the family history and trauma effects have significant limitations. The study enrolled 119 subjects, including 55 BD spectrum (BDS) subjects diagnosed with BD or major depressive disorder (MDD) with subthreshold BD symptoms and 64 non-BDS subjects comprising 32 MDD subjects without BD symptoms and 32 healthy subjects. The blood samples underwent genome-wide genotyping and methylation quantification. We derived polygenic risk score (PRS) and methylation profile score (MPS) as weighted summations of risk single nucleotide polymorphisms and methylation probes, respectively, which were considered as molecular measures of genetic and environmental risks for BD. Linear regression was used to relate PRS, MPS, and their interaction to 44 brain structure measures quantified from magnetic resonance imaging (MRI) on 47 BDS subjects, and the results were compared with those based on family history and childhood trauma. After multiplicity corrections using false discovery rate (FDR), MPS was found to be negatively associated with the volume of the medial geniculate thalamus (FDR = 0.059, partial R2 = 0.208). Family history, trauma scale, and PRS were not associated with any brain measures. PRS and MPS show significant interactions on whole putamen (FDR = 0.09, partial R2 = 0.337). No significant gene-environment interactions were identified for the family history and trauma scale. PRS and MPS generally explained greater proportions of variances of the brain measures (range of partial R2 = [0.008, 0.337]) than the clinical risk factors (range = [0.004, 0.228]).Item The Genetic Architecture of Alzheimer's Disease Endophenotypes(2022-05) Jacobson, Tanner Young; Saykin, Andrew J.; Nho, Kwangsik; Foroud, Tatiana; Zhang, Chi; Cao, ShaAlzheimer’s Disease (AD) is one of the most common forms of dementia and is known to have a strong genetic component, but known genetic loci do not fully account for the observed genetic heritability of late onset AD. This genetic complexity is further complicated by disease heterogeneity, with non-uniform presentation and progression of AD neuropathology. Endophenotypes lie upstream of observed AD clinical outcomes and downstream of genetic contributors, allowing for a biological understanding of genetic effects. Understanding the genetic architecture of AD endophenotypes can aid in breaking down AD genetic complexity and heterogeneity. In this study we utilized a variety of models to evaluate the genetic contributors to pathological change and heterogeneity in the top markers of AD pathology: amyloid, tau, neurodegeneration, and cerebrovascular (A/T/N/V framework). Additional composite quantitative measures of cognitive performance were used to relate to downstream AD presentation. These biomarkers allow the investigation of genetic effects contributing to the disease over the stages of disease progression from amyloid deposition to neurofibrillary tangle formation, disruption of metabolism, brain atrophy, and finally to clinical outcomes. First, we performed genome-wide association studies (GWAS) for AD endophenotypes at baseline using a cross-sectional regression model. This method identified sixteen novel or replicated loci, with six (SRSF10, MAPT, XKR3, KIAA1671, ZNF826P, and LOC100507506) associated across multiple A/T/N biomarkers. Cross-sectional data was further utilized to identify three genetic loci (BACH2, EP300, PACRG-AS1) that showed disease stage specific interaction effects. We built upon those results by performing a longitudinal association analysis with linear-mixed effects modeling. Gene enrichment analysis of these results identified 19 significant genetic regions associated with linear longitudinal change in AD endophenotypes. To further break down longitudinal heterogeneity, a latent class mixed model approach was utilized to identify subgroups of longitudinal progression within cognitive and MRI measures, with 16 genetic loci associated with membership in different classes. The genetic patterns of these subgroups show biological relevance in AD. The methods and results from this study provide insight into the complex genetic architecture of AD endophenotypes and a foundation to build upon for future studies into AD genetic architecture.Item Identifying progressive imaging genetic patterns via multi-task sparse canonical correlation analysis: a longitudinal study of the ADNI cohort(Oxford University Press, 2019-07) Du, Lei; Liu, Kefei; Zhu, Lei; Yao, Xiaohui; Risacher, Shannon L.; Guo, Lei; Saykin, Andrew J.; Shen, Li; Radiology & Imaging Sciences, IU School of MedicineMotivation Identifying the genetic basis of the brain structure, function and disorder by using the imaging quantitative traits (QTs) as endophenotypes is an important task in brain science. Brain QTs often change over time while the disorder progresses and thus understanding how the genetic factors play roles on the progressive brain QT changes is of great importance and meaning. Most existing imaging genetics methods only analyze the baseline neuroimaging data, and thus those longitudinal imaging data across multiple time points containing important disease progression information are omitted. Results We propose a novel temporal imaging genetic model which performs the multi-task sparse canonical correlation analysis (T-MTSCCA). Our model uses longitudinal neuroimaging data to uncover that how single nucleotide polymorphisms (SNPs) play roles on affecting brain QTs over the time. Incorporating the relationship of the longitudinal imaging data and that within SNPs, T-MTSCCA could identify a trajectory of progressive imaging genetic patterns over the time. We propose an efficient algorithm to solve the problem and show its convergence. We evaluate T-MTSCCA on 408 subjects from the Alzheimer’s Disease Neuroimaging Initiative database with longitudinal magnetic resonance imaging data and genetic data available. The experimental results show that T-MTSCCA performs either better than or equally to the state-of-the-art methods. In particular, T-MTSCCA could identify higher canonical correlation coefficients and capture clearer canonical weight patterns. This suggests that T-MTSCCA identifies time-consistent and time-dependent SNPs and imaging QTs, which further help understand the genetic basis of the brain QT changes over the time during the disease progression. Availability and implementation The software and simulation data are publicly available at https://github.com/dulei323/TMTSCCA. Supplementary information Supplementary data are available at Bioinformatics online.Item Incidence of cognitively defined late-onset Alzheimer's dementia subgroups from a prospective cohort study(Elsevier, 2017-12) Crane, Paul K.; Trittschuh, Emily; Mukherjee, Shubhabrata; Saykin, Andrew J.; Sanders, Elizabeth; Larson, Eric B.; McCurry, Susan M.; McCormick, Wayne; Bowen, James D.; Grabowski, Thomas; Moore, Mackenzie; Gross, Alden L.; Keene, Dirk; Bird, Thomas E.; Gibbons, Laura E.; Mez, Jesse; Radiology and Imaging Sciences, School of MedicineINTRODUCTION: There may be biologically relevant heterogeneity within typical late-onset Alzheimer's dementia. METHODS: We analyzed cognitive data from people with incident late-onset Alzheimer's dementia from a prospective cohort study. We determined individual averages across memory, visuospatial functioning, language, and executive functioning. We identified domains with substantial impairments relative to that average. We compared demographic, neuropathology, and genetic findings across groups defined by relative impairments. RESULTS: During 32,286 person-years of follow-up, 869 people developed Alzheimer's dementia. There were 393 (48%) with no domain with substantial relative impairments. Some participants had isolated relative impairments in memory (148, 18%), visuospatial functioning (117, 14%), language (71, 9%), and executive functioning (66, 8%). The group with isolated relative memory impairments had higher proportions with ≥ APOE ε4 allele, more extensive Alzheimer's-related neuropathology, and higher proportions with other Alzheimer's dementia genetic risk variants. DISCUSSION: A cognitive subgrouping strategy may identify biologically distinct subsets of people with Alzheimer's dementia.Item Leveraging large multi-center cohorts of Alzheimer disease endophenotypes to understand the role of Klotho heterozygosity on disease risk(PLOS, 2022-05-26) Ali, Muhammad; Sung, Yun Ju; Wang, Fengxian; Fernández, Maria V.; Morris, John C.; Fagan, Anne M.; Blennow, Kaj; Zetterberg, Henrik; Heslegrave, Amanda; Johansson, Per M.; Svensson, Johan; Nellgård, Bengt; Lleó, Alberto; Alcolea, Daniel; Clarimon, Jordi; Rami, Lorena; Molinuevo, José Luis; Suárez-Calvet, Marc; Morenas-Rodríguez, Estrella; Kleinberger, Gernot; Haass, Christian; Ewers, Michael; Levin, Johannes; Farlow, Martin R.; Perrin, Richard J.; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Dominantly Inherited Alzheimer Network (DIAN); Cruchaga, Carlos; Neurology, School of MedicineTwo genetic variants in strong linkage disequilibrium (rs9536314 and rs9527025) in the Klotho (KL) gene, encoding a transmembrane protein, implicated in longevity and associated with brain resilience during normal aging, were recently shown to be associated with Alzheimer disease (AD) risk in cognitively normal participants who are APOE ε4 carriers. Specifically, the participants heterozygous for this variant (KL-SVHET+) showed lower risk of developing AD. Furthermore, a neuroprotective effect of KL-VSHET+ has been suggested against amyloid burden for cognitively normal participants, potentially mediated via the regulation of redox pathways. However, inconsistent associations and a smaller sample size of existing studies pose significant hurdles in drawing definitive conclusions. Here, we performed a well-powered association analysis between KL-VSHET+ and five different AD endophenotypes; brain amyloidosis measured by positron emission tomography (PET) scans (n = 5,541) or cerebrospinal fluid Aβ42 levels (CSF; n = 5,093), as well as biomarkers associated with tau pathology: the CSF Tau (n = 5,127), phosphorylated Tau (pTau181; n = 4,778) and inflammation: CSF soluble triggering receptor expressed on myeloid cells 2 (sTREM2; n = 2,123) levels. Our results found nominally significant associations of KL-VSHET+ status with biomarkers for brain amyloidosis (e.g., CSF Aβ positivity; odds ratio [OR] = 0.67 [95% CI, 0.55-0.78], β = 0.72, p = 0.007) and tau pathology (e.g., biomarker positivity for CSF Tau; OR = 0.39 [95% CI, 0.19-0.77], β = -0.94, p = 0.007, and pTau; OR = 0.50 [95% CI, 0.27-0.96], β = -0.68, p = 0.04) in cognitively normal participants, 60-80 years old, who are APOE e4-carriers. Our work supports previous findings, suggesting that the KL-VSHET+ on an APOE ε4 genotype background may modulate Aβ and tau pathology, thereby lowering the intensity of neurodegeneration and incidence of cognitive decline in older controls susceptible to AD.Item Quantitative trait loci identification for brain endophenotypes via new additive model with random networks(Oxford University Press, 2018-09) Wang, Xiaoqian; Chen, Hong; Yan, Jingwen; Nho, Kwangsik; Risacher, Shannon L.; Saykin, Andrew J.; Shen, Li; Huang, Heng; Radiology and Imaging Sciences, School of MedicineMotivation: The identification of quantitative trait loci (QTL) is critical to the study of causal relationships between genetic variations and disease abnormalities. We focus on identifying the QTLs associated to the brain endophenotypes in imaging genomics study for Alzheimer's Disease (AD). Existing research works mainly depict the association between single nucleotide polymorphisms (SNPs) and the brain endophenotypes via the linear methods, which may introduce high bias due to the simplicity of the models. Since the influence of QTLs on brain endophenotypes is quite complex, it is desired to design the appropriate non-linear models to investigate the associations of genotypes and endophenotypes. Results: In this paper, we propose a new additive model to learn the non-linear associations between SNPs and brain endophenotypes in Alzheimer's disease. Our model can be flexibly employed to explain the non-linear influence of QTLs, thus is more adaptive for the complex distribution of the high-throughput biological data. Meanwhile, as an important computational learning theory contribution, we provide the generalization error analysis for the proposed approach. Unlike most previous theoretical analysis under independent and identically distributed samples assumption, our error bound is based on m-dependent observations, which is more appropriate for the high-throughput and noisy biological data. Experiments on the data from Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort demonstrate the promising performance of our approach for identifying biological meaningful SNPs.Item Sex-specific genetic architecture of late-life memory performance(Wiley, 2024) Eissman, Jaclyn M.; Archer, Derek B.; Mukherjee, Shubhabrata; Lee, Michael L.; Choi, Seo-Eun; Scollard, Phoebe; Trittschuh, Emily H.; Mez, Jesse B.; Bush, William S.; Kunkle, Brian W.; Naj, Adam C.; Gifford, Katherine A.; Alzheimer's Disease Neuroimaging Initiative (ADNI); Alzheimer's Disease Genetics Consortium (ADGC); The Alzheimer's Disease Sequencing Project (ADSP); Cuccaro, Michael L.; Cruchaga, Carlos; Pericak-Vance, Margaret A.; Farrer, Lindsay A.; Wang, Li-San; Schellenberg, Gerard D.; Mayeux, Richard P.; Haines, Jonathan L.; Jefferson, Angela L.; Kukull, Walter A.; Keene, C. Dirk; Saykin, Andrew J.; Thompson, Paul M.; Martin, Eden R.; Bennett, David A.; Barnes, Lisa L.; Schneider, Julie A.; Crane, Paul K.; Hohman, Timothy J.; Dumitrescu, Logan; Radiology and Imaging Sciences, School of MedicineBackground: Women demonstrate a memory advantage when cognitively healthy yet lose this advantage to men in Alzheimer's disease. However, the genetic underpinnings of this sex difference in memory performance remain unclear. Methods: We conducted the largest sex-aware genetic study on late-life memory to date (Nmales = 11,942; Nfemales = 15,641). Leveraging harmonized memory composite scores from four cohorts of cognitive aging and AD, we performed sex-stratified and sex-interaction genome-wide association studies in 24,216 non-Hispanic White and 3367 non-Hispanic Black participants. Results: We identified three sex-specific loci (rs67099044-CBLN2, rs719070-SCHIP1/IQCJ-SCHIP), including an X-chromosome locus (rs5935633-EGL6/TCEANC/OFD1), that associated with memory. Additionally, we identified heparan sulfate signaling as a sex-specific pathway and found sex-specific genetic correlations between memory and cardiovascular, immune, and education traits. Discussion: This study showed memory is highly and comparably heritable across sexes, as well as highlighted novel sex-specific genes, pathways, and genetic correlations that related to late-life memory. Highlights: Demonstrated the heritable component of late-life memory is similar across sexes. Identified two genetic loci with a sex-interaction with baseline memory. Identified an X-chromosome locus associated with memory decline in females. Highlighted sex-specific candidate genes and pathways associated with memory. Revealed sex-specific shared genetic architecture between memory and complex traits.