Browsing by Subject "Genetic loci"

Now showing 1 - 7 of 7
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    Genetic loci associated with skin pigmentation in African Americans and their effects on vitamin D deficiency
    (Public Library of Science, 2021-02-18) Batai, Ken; Cui, Zuxi; Arora, Amit; Shah-Williams, Ebony; Hernandez, Wenndy; Ruden, Maria; Hollowell, Courtney M. P.; Hooker, Stanley E.; Bathina, Madhavi; Murphy, Adam B.; Bonilla, Carolina; Kittles, Rick A.; Medical and Molecular Genetics, School of Medicine
    A recent genome-wide association study (GWAS) in African descent populations identified novel loci associated with skin pigmentation. However, how genomic variations affect skin pigmentation and how these skin pigmentation gene variants affect serum 25(OH) vitamin D variation has not been explored in African Americans (AAs). In order to further understand genetic factors that affect human skin pigmentation and serum 25(OH)D variation, we performed a GWAS for skin pigmentation with 395 AAs and a replication study with 681 AAs. Then, we tested if the identified variants are associated with serum 25(OH) D concentrations in a subset of AAs (n = 591). Skin pigmentation, Melanin Index (M-Index), was measured using a narrow-band reflectometer. Multiple regression analysis was performed to identify variants associated with M-Index and to assess their role in serum 25(OH)D variation adjusting for population stratification and relevant confounding variables. A variant near the SLC24A5 gene (rs2675345) showed the strongest signal of association with M-Index (P = 4.0 x 10-30 in the pooled dataset). Variants in SLC24A5, SLC45A2 and OCA2 together account for a large proportion of skin pigmentation variance (11%). The effects of these variants on M-Index was modified by sex (P for interaction = 0.009). However, West African Ancestry (WAA) also accounts for a large proportion of M-Index variance (23%). M-Index also varies among AAs with high WAA and high Genetic Score calculated from top variants associated with M-Index, suggesting that other unknown genomic factors related to WAA are likely contributing to skin pigmentation variation. M-Index was not associated with serum 25(OH)D concentrations, but the Genetic Score was significantly associated with vitamin D deficiency (serum 25(OH)D levels less than 12 ng/mL) (OR, 1.30; 95% CI, 1.04-1.64). The findings support the hypothesis suggesting that skin pigmentation evolved responding to increased demand for subcutaneous vitamin D synthesis in high latitude environments.
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    Genome-wide association study identifies 48 common genetic variants associated with handedness
    (Springer Nature, 2021) Cuellar-Partida, Gabriel; Tung, Joyce Y.; Eriksson, Nicholas; Albrecht, Eva; Aliev, Fazil; Andreassen, Ole A.; Barroso, Inês; Beckmann, Jacques S.; Boks, Marco P.; Boomsma, Dorret I.; Boyd, Heather A.; Breteler, Monique M. B.; Campbell, Harry; Chasman, Daniel I.; Cherkas, Lynn F.; Davies, Gail; de Geus, Eco J. C.; Deary, Ian J.; Deloukas, Panos; Dick, Danielle M.; Duffy, David L.; Eriksson, Johan G.; Esko, Tõnu; Feenstra, Bjarke; Geller, Frank; Gieger, Christian; Giegling, Ina; Gordon, Scott D.; Han, Jiali; Hansen, Thomas F.; Hartmann, Annette M.; Hayward, Caroline; Heikkilä, Kauko; Hicks, Andrew A.; Hirschhorn, Joel N.; Hottenga, Jouke-Jan; Huffman, Jennifer E.; Hwang, Liang-Dar; Ikram, M. Arfan; Kaprio, Jaakko; Kemp, John P.; Khaw, Kay-Tee; Klopp, Norman; Konte, Bettina; Kutalik, Zoltan; Lahti, Jari; Li, Xin; Loos, Ruth J. F.; Luciano, Michelle; Magnusson, Sigurdur H.; Mangino, Massimo; Marques-Vidal, Pedro; Martin, Nicholas G.; McArdle, Wendy L.; McCarthy, Mark I.; Medina-Gomez, Carolina; Melbye, Mads; Melville, Scott A.; Metspalu, Andres; Milani, Lili; Mooser, Vincent; Nelis, Mari; Nyholt, Dale R.; O'Connell, Kevin S.; Ophoff, Roel A.; Palmer, Cameron; Palotie, Aarno; Palviainen, Teemu; Pare, Guillaume; Paternoster, Lavinia; Peltonen, Leena; Penninx, Brenda W. J. H.; Polasek, Ozren; Pramstaller, Peter P.; Prokopenko, Inga; Raikkonen, Katri; Ripatti, Samuli; Rivadeneira, Fernando; Rudan, Igor; Rujescu, Dan; Smit, Johannes H.; Smith, George Davey; Smoller, Jordan W.; Soranzo, Nicole; Spector, Tim D.; St. Pourcain, Beate; Starr, John M.; Stefánsson, Hreinn; Steinberg, Stacy; Teder-Laving, Maris; Thorleifsson, Gudmar; Stefánsson, Kári; Timpson, Nicholas J.; Uitterlinden, André G.; van Duijn, Cornelia M.; van Rooij, Frank J. A.; Vink, Jaqueline M.; Vollenweider, Peter; Vuoksimaa, Eero; Waeber, Gérard; Wareham, Nicholas J.; Warrington, Nicole; Waterworth, Dawn; Werge, Thomas; Wichmann, H-Erich; Widen, Elisabeth; Willemsen, Gonneke; Wright, Alan F.; Wright, Margaret J.; Xu, Mousheng; Zhao, Jing Hua; Kraft, Peter; Hinds, David A.; Lindgren, Cecilia M.; Mägi, Reedik; Neale, Benjamin M.; Evans, David M.; Medland, Sarah E.; Epidemiology, School of Public Health
    Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10-8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.
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    Insights into the genetic architecture of the human face
    (Springer Nature, 2021) White, Julie D.; Indencleef, Karlijne; Naqvi, Sahin; Eller, Ryan J.; Hoskens, Hanne; Roosenboom, Jasmien; Lee, Myoung Keun; Li, Jiarui; Mohammed, Jaaved; Richmond, Stephen; Quillen, Ellen E.; Norton, Heather L.; Feingold, Eleanor; Swigut, Tomek; Marazita, Mary L.; Peeters, Hilde; Hens, Greet; Shaffer, John R.; Wysocka, Joanna; Walsh, Susan; Weinberg, Seth M.; Shriver, Mark D.; Claes, Peter; Biology, School of Science
    The human face is complex and multipartite, and characterization of its genetic architecture remains challenging. Using a multivariate genome-wide association study meta-analysis of 8,246 European individuals, we identified 203 genome-wide-significant signals (120 also study-wide significant) associated with normal-range facial variation. Follow-up analyses indicate that the regions surrounding these signals are enriched for enhancer activity in cranial neural crest cells and craniofacial tissues, several regions harbor multiple signals with associations to different facial phenotypes, and there is evidence for potential coordinated actions of variants. In summary, our analyses provide insights into the understanding of how complex morphological traits are shaped by both individual and coordinated genetic actions.
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    Linkage Disequilibrium-Informed Deep Learning Framework to Identify Genetic Loci for Alzheimer’s Disease Using Whole Genome Sequencing Data
    (medRxiv, 2024-09-22) Jo, Taeho; Bice, Paula; Nho, Kwangsik; Saykin, Andrew J.; Alzheimer’s Disease Sequencing Project; Radiology and Imaging Sciences, School of Medicine
    The exponential growth of genomic datasets necessitates advanced analytical tools to effectively identify genetic loci from large-scale high throughput sequencing data. This study presents Deep-Block, a multi-stage deep learning framework that incorporates biological knowledge into its AI architecture to identify genetic regions as significantly associated with Alzheimer's disease (AD). The framework employs a three-stage approach: (1) genome segmentation based on linkage disequilibrium (LD) patterns, (2) selection of relevant LD blocks using sparse attention mechanisms, and (3) application of TabNet and Random Forest algorithms to quantify single nucleotide polymorphism (SNP) feature importance, thereby identifying genetic factors contributing to AD risk. The Deep-Block was applied to a large-scale whole genome sequencing (WGS) dataset from the Alzheimer's Disease Sequencing Project (ADSP), comprising 7,416 non-Hispanic white participants (3,150 cognitively normal older adults (CN), 4,266 AD). First, 30,218 LD blocks were identified and then ranked based on their relevance with Alzheimer's disease. Subsequently, the Deep-Block identified novel SNPs within the top 1,500 LD blocks and confirmed previously known variants, including APOE rs429358 and rs769449. The results were cross-validated against established AD-associated loci from the European Alzheimer's and Dementia Biobank (EADB) and the GWAS catalog. The Deep-Block framework effectively processes large-scale high throughput sequencing data while preserving interactions between SNPs in performing the dimensionality reduction, which can potentially introduce bias or lead to information loss. The Deep-Block approach identified both known and novel genetic variation, enhancing our understanding of the genetic architecture of and demonstrating the framework's potential for application in large-scale sequencing studies.
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    Novel Alzheimer Disease Risk Loci and Pathways in African American Individuals Using the African Genome Resources Panel
    (American Medical Association, 2021-01-01) Kunkle, Brian W.; Schmidt, Michael; Klein, Hans-Ulrich; Naj, Adam C.; Hamilton-Nelson, Kara L.; Larson, Eric B.; Evans, Denis A.; De Jager, Phil L.; Crane, Paul K.; Buxbaum, Joe D.; Ertekin-Taner, Nilufer; Go, Rodney C.P.; Obisesan, Thomas O.; Kamboh, Ilyas; Bennett, David A.; Hall, Kathleen S.; Goate, Alison M.; Foroud, Tatiana M.; Martin, Eden R.; Wang, Li-Sao; Byrd, Goldie S.; Farrer, Lindsay A.; Haines, Jonathan L.; Schellenberg, Gerard D.; Mayeux, Richard; Pericak-Vance, Margaret A.; Reitz, Christiane; Graff-Radford, Neill R.; Martinez, Izri; Ayodele, Temitope; Logue, Mark W.; Cantwell, Laura B.; Jean-Francois, Melissa; Kuzma, Amanda B.; Adams, L.D.; Vance, Jeffery M.; Cuccaro, Michael L.; Chung, Jaeyoon; Mez, Jesse; Lunetta, Kathryn L.; Jun, Gyungah R.; Lopez, Oscar L.; Hendrie, Hugh C.; Reiman, Eric M.; Kowall, Neil W.; Leverenz, James B.; Small, Scott A.; Levey, Allan I.; Golde, Todd E.; Saykin, Andrew J.; Starks, Takiyah D.; Albert, Marilyn S.; Hyman, Bradley T.; Petersen, Ronald C.; Sano, Mary; Wisniewski, Thomas; Vassar, Robert; Kaye, Jeffrey A.; Henderson, Victor W.; DeCarli, Charles; LaFerla, Frank M.; Brewer, James B.; Miller, Bruce L.; Swerdlow, Russell H.; Van Eldik, Linda J.; Paulson, Henry L.; Trojanowski, John Q.; Chui, Helena C.; Rosenberg, Roger N.; Craft, Suzanne; Grabowski, Thomas J.; Asthana, Sanjay; Morris, John C.; Strittmatter, Stephen M.; Kukull, Walter A.; Psychiatry, School of Medicine
    Importance: Compared with non-Hispanic White individuals, African American individuals from the same community are approximately twice as likely to develop Alzheimer disease. Despite this disparity, the largest Alzheimer disease genome-wide association studies to date have been conducted in non-Hispanic White individuals. In the largest association analyses of Alzheimer disease in African American individuals, ABCA7, TREM2, and an intergenic locus at 5q35 were previously implicated. Objective: To identify additional risk loci in African American individuals by increasing the sample size and using the African Genome Resource panel. Design, setting, and participants: This genome-wide association meta-analysis used case-control and family-based data sets from the Alzheimer Disease Genetics Consortium. There were multiple recruitment sites throughout the United States that included individuals with Alzheimer disease and controls of African American ancestry. Analysis began October 2018 and ended September 2019. Main outcomes and measures: Diagnosis of Alzheimer disease. Results: A total of 2784 individuals with Alzheimer disease (1944 female [69.8%]) and 5222 controls (3743 female [71.7%]) were analyzed (mean [SD] age at last evaluation, 74.2 [13.6] years). Associations with 4 novel common loci centered near the intracellular glycoprotein trafficking gene EDEM1 (3p26; P = 8.9 × 10-7), near the immune response gene ALCAM (3q13; P = 9.3 × 10-7), within GPC6 (13q31; P = 4.1 × 10-7), a gene critical for recruitment of glutamatergic receptors to the neuronal membrane, and within VRK3 (19q13.33; P = 3.5 × 10-7), a gene involved in glutamate neurotoxicity, were identified. In addition, several loci associated with rare variants, including a genome-wide significant intergenic locus near IGF1R at 15q26 (P = 1.7 × 10-9) and 6 additional loci with suggestive significance (P ≤ 5 × 10-7) such as API5 at 11p12 (P = 8.8 × 10-8) and RBFOX1 at 16p13 (P = 5.4 × 10-7) were identified. Gene expression data from brain tissue demonstrate association of ALCAM, ARAP1, GPC6, and RBFOX1 with brain β-amyloid load. Of 25 known loci associated with Alzheimer disease in non-Hispanic White individuals, only APOE, ABCA7, TREM2, BIN1, CD2AP, FERMT2, and WWOX were implicated at a nominal significance level or stronger in African American individuals. Pathway analyses strongly support the notion that immunity, lipid processing, and intracellular trafficking pathways underlying Alzheimer disease in African American individuals overlap with those observed in non-Hispanic White individuals. A new pathway emerging from these analyses is the kidney system, suggesting a novel mechanism for Alzheimer disease that needs further exploration. Conclusions and relevance: While the major pathways involved in Alzheimer disease etiology in African American individuals are similar to those in non-Hispanic White individuals, the disease-associated loci within these pathways differ.
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    Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci
    (Springer Nature, 2023) Mignogna, Gianmarco; Carey, Caitlin E.; Wedow, Robbee; Baya, Nikolas; Cordioli, Mattia; Pirastu, Nicola; Bellocco, Rino; Fiuza Malerbi, Kathryn; Nivard, Michel G.; Neale, Benjamin M.; Walters, Raymond K.; Ganna, Andrea; Medical and Molecular Genetics, School of Medicine
    Response to survey questionnaires is vital for social and behavioural research, and most analyses assume full and accurate response by participants. However, nonresponse is common and impedes proper interpretation and generalizability of results. We examined item nonresponse behaviour across 109 questionnaire items in the UK Biobank (N = 360,628). Phenotypic factor scores for two participant-selected nonresponse answers, 'Prefer not to answer' (PNA) and 'I don't know' (IDK), each predicted participant nonresponse in follow-up surveys (incremental pseudo-R2 = 0.056), even when controlling for education and self-reported health (incremental pseudo-R2 = 0.046). After performing genome-wide association studies of our factors, PNA and IDK were highly genetically correlated with one another (rg = 0.73 (s.e. = 0.03)) and with education (rg,PNA = -0.51 (s.e. = 0.03); rg,IDK = -0.38 (s.e. = 0.02)), health (rg,PNA = 0.51 (s.e. = 0.03); rg,IDK = 0.49 (s.e. = 0.02)) and income (rg,PNA = -0.57 (s.e. = 0.04); rg,IDK = -0.46 (s.e. = 0.02)), with additional unique genetic associations observed for both PNA and IDK (P < 5 × 10-8). We discuss how these associations may bias studies of traits correlated with item nonresponse and demonstrate how this bias may substantially affect genome-wide association studies. While the UK Biobank data are deidentified, we further protected participant privacy by avoiding exploring non-response behaviour to single questions, assuring that no information can be used to associate results with any particular respondents.
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    Sex-specific genetic predictors of memory, executive function, and language performance
    (Wiley, 2022) Eissman, Jaclyn M.; Smith, Alexandra N.; Mukherjee, Shubhabrata; Lee, Michael L.; Choi, Seo-Eun; Scollard, Phoebe; Trittschuh, Emily H.; Mez, Jesse B.; Bush, William S.; Engelman, Corinne D.; Lu, Qiongshi; Fardo, David W.; Widaman, Keith F.; Buckley, Rachel F.; Mormino, Elizabeth C.; Kunkle, Brian W.; Naj, Adam C.; Clark, Lindsay R.; Gifford, Katherine A.; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Alzheimer’s Disease Genetics Consortium (ADGC); A4 Study Team; 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.; Haines, Jonathan L.; Jefferson, Angela L.; Johnson, Sterling C.; Kukull, Walter A.; Albert, Marilyn S.; Keene, C. Dirk; Saykin, Andrew J.; Larson, Eric B.; Sperling, Reisa A.; Mayeux, Richard; 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 Medicine
    Background: Alzheimer’s disease (AD) is more prevalent in women than men, and robust evidence shows sex differences in the biological response to the AD neuropathological cascade. However, there is a lack of large-scale genetic studies on sex-specific genetic predictors of AD-related cognitive outcomes. Thus, we sought to elucidate the sex-specific genetic etiology of memory, executive function, and language performance. Method: This study included six cohorts of cognitive aging (Nmales=7,267, Nfemales=9,518). We applied psychometric approaches to build harmonized memory, executive function, and language composite scores. Next, for all domains, we calculated slopes from the cognitive scores (two or more timepoints) with linear mixed effects models. Then we performed sex-stratified and sex-interaction GWAS on these phenotypes, covarying for baseline age and the first three genetic principal components. We meta-analyzed across cohorts with a fixed-effects model. Sensitivity analyses for all models restricted the sample to cognitively unimpaired individuals. Result: In addition to well-established associations with cognition at the APOE locus, we identified three genetic loci that showed sex-specific effects with cognition. A chromosome 16 locus (rs114106271), a splicing-quantitative trait locus for RP11-152O14.4 and LINC02180 in the testis (GTEx), associated with baseline memory performance in men (β=0.13, P=2.40×10-8; PInteraction=8.96×10-6; Figures 1-2) but not in women (β=-0.01, P=0.76). A chromosome 14 locus (rs34074573), an expression-quantitative trait locus (GTEx) for HOMEZ (a homeobox gene), and for BCL2L2 (a previously reported AD risk gene), associated with longitudinal memory performance in men (β=-0.01, P=4.15×10-8; PInteraction=5.83×10-7; Figures 3-4) but not in women (β=0.001, P=0.09). Finally, a chromosome 6 locus (rs9382966) associated with longitudinal language performance in men with near genome-wide significance (β=-0.004, P=6.29×10-8; PInteraction=2.01×10-4) but not in women (β=-0.0003, P=0.61). Conclusion: Our results highlight some key sex differences in the genetic architecture of cognitive outcomes. Findings further suggest that some sex-specific genetic predictors have domain-specific associations, providing an exciting opportunity to better understand the molecular basis of memory, executive function, and language through genomic analysis. Although our findings need to be replicated, our GWAS analyses highlight the contribution of sex-specific genetic predictors beyond the APOE locus in conferring risk for late-life cognitive decline.