69 research outputs found

    Host determinants of HIV-1 control in African Americans

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    We performed a whole-genome association study of human immunodeficiency virus type 1 (HIV-1) set point among a cohort of African Americans (n = 515), and an intronic single-nucleotide polymorphism (SNP) in the HLA-B gene showed one of the strongest associations. We use a subset of patients to demonstrate that this SNP reflects the effect of the HLA-B*5703 allele, which shows a genome-wide statistically significant association with viral load set point (P = 5.6 x 10(-10)). These analyses therefore confirm a member of the HLA-B*57 group of alleles as the most important common variant that influences viral load variation in African Americans, which is consistent with what has been observed for individuals of European ancestry, among whom the most important common variant is HLA-B*5701

    Somatic variants in diverse genes leads to a spectrum of focal cortical malformations

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    Post-zygotically acquired genetic variants, or somatic variants, that arise during cortical development have emerged as important causes of focal epilepsies, particularly those due to malformations of cortical development. Pathogenic somatic variants have been identified in many genes within the PI3K-AKT-mTOR-signalling pathway in individuals with hemimegalencephaly and focal cortical dysplasia (type II), and more recently in SLC35A2 in individuals with focal cortical dysplasia (type I) or non-dysplastic epileptic cortex. Given the expanding role of somatic variants across different brain malformations, we sought to delineate the landscape of somatic variants in a large cohort of patients who underwent epilepsy surgery with hemimegalencephaly or focal cortical dysplasia. We evaluated samples from 123 children with hemimegalencephaly (n=16), focal cortical dysplasia type I and related phenotypes (n=48), focal cortical dysplasia type II (n=44), or focal cortical dysplasia type III (n=15). We performed high-depth exome sequencing in brain tissue-derived DNA from each case and identified somatic single nucleotide, indel and large copy number variants. In 75% of individuals with hemimegalencephaly and 29% with focal cortical dysplasia type II, we identified pathogenic variants in PI3K-AKT-mTOR pathway genes. Four of 48 cases with focal cortical dysplasia type I (8%) had a likely pathogenic variant in SLC35A2. While no other gene had multiple disease-causing somatic variants across the focal cortical dysplasia type I cohort, four individuals in this group had a single pathogenic or likely pathogenic somatic variant in CASK, KRAS, NF1 and NIPBL, genes previously associated with neurodevelopmental disorders. No rare pathogenic or likely pathogenic somatic variants in any neurological disease genes like those identified in the focal cortical dysplasia type I cohort were found in 63 neurologically normal controls (P=0.017), suggesting a role for these novel variants. We also identified a somatic loss-of-function variant in the known epilepsy gene, PCDH19, present in a small number of alleles in the dysplastic tissue from a female patient with focal cortical dysplasia IIIa with hippocampal sclerosis. In contrast to focal cortical dysplasia type II, neither focal cortical dysplasia type I nor III had somatic variants in genes that converge on a unifying biological pathway, suggesting greater genetic heterogeneity compared to type II. Importantly, we demonstrate that focal cortical dysplasia types I, II and III are associated with somatic gene variants across a broad range of genes, many associated with epilepsy in clinical syndromes caused by germline variants, as well as including some not previously associated with radiographically evident cortical brain malformations

    Genome-wide mapping for clinically relevant predictors of lamotrigine- and phenytoin-induced hypersensitivity reactions.

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    An association between carbamazepine-induced hypersensitivity and HLA-A*3101 has been reported in populations of both European and Asian descent. We aimed to investigate HLA-A*3101 and other common variants across the genome as markers for cutaneous adverse drug reactions (cADRs) attributed to lamotrigine and phenytoin

    Characteristics of undiagnosed diseases network applicants: implications for referring providers

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    Abstract Background The majority of undiagnosed diseases manifest with objective findings that warrant further investigation. The Undiagnosed Diseases Network (UDN) receives applications from patients whose symptoms and signs have been intractable to diagnosis; however, many UDN applicants are affected primarily by subjective symptoms such as pain and fatigue. We sought to characterize presenting symptoms, referral sources, and demographic factors of applicants to the UDN to identify factors that may determine application outcome and potentially differentiate between those with undiagnosed diseases (with more objective findings) and those who are less likely to have an undiagnosed disease (more subjective symptoms). Methods We used a systematic retrospective review of 151 consecutive Not Accepted and 50 randomly selected Accepted UDN applications. The primary outcome was whether an applicant was Accepted, or Not Accepted, and, if accepted, whether or not a diagnosis was made. Objective and subjective symptoms and information on prior specialty consultations were collected from provider referral letters. Demographic data and decision data on network acceptance were gathered from the UDN online portal. Results Fewer objective findings and more subjective symptoms were found in the Not Accepted applications. Not Accepted referrals also were from older individuals, reported a shorter period of illness, and were referred to the UDN by their primary care physicians. All of these differences reached statistical significance in comparison with Accepted applications. The frequency of subspecialty consults for diagnostic purposes prior to UDN application was similar in both groups. Conclusions The preponderance of subjective and lack of objective findings in the Not Accepted applications distinguish these from applicants that are accepted for evaluation and diagnostic efforts through the UDN. Not Accepted applicants are referred primarily by their primary care providers after multiple specialist consultations fail to yield answers. Distinguishing between patients with undiagnosed diseases with objective findings and those with primarily subjective findings can delineate patients who would benefit from further diagnostic processes from those who may have functional disorders and need alternative pathways for management of their symptoms. Trial registration clinicaltrials.gov NCT02450851 , posted May 21st 2015

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    A genome-wide association search for type 2 diabetes genes in African Americans.

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    African Americans are disproportionately affected by type 2 diabetes (T2DM) yet few studies have examined T2DM using genome-wide association approaches in this ethnicity. The aim of this study was to identify genes associated with T2DM in the African American population. We performed a Genome Wide Association Study (GWAS) using the Affymetrix 6.0 array in 965 African-American cases with T2DM and end-stage renal disease (T2DM-ESRD) and 1029 population-based controls. The most significant SNPs (n = 550 independent loci) were genotyped in a replication cohort and 122 SNPs (n = 98 independent loci) were further tested through genotyping three additional validation cohorts followed by meta-analysis in all five cohorts totaling 3,132 cases and 3,317 controls. Twelve SNPs had evidence of association in the GWAS (P<0.0071), were directionally consistent in the Replication cohort and were associated with T2DM in subjects without nephropathy (P<0.05). Meta-analysis in all cases and controls revealed a single SNP reaching genome-wide significance (P<2.5×10(-8)). SNP rs7560163 (P = 7.0×10(-9), OR (95% CI) = 0.75 (0.67-0.84)) is located intergenically between RND3 and RBM43. Four additional loci (rs7542900, rs4659485, rs2722769 and rs7107217) were associated with T2DM (P<0.05) and reached more nominal levels of significance (P<2.5×10(-5)) in the overall analysis and may represent novel loci that contribute to T2DM. We have identified novel T2DM-susceptibility variants in the African-American population. Notably, T2DM risk was associated with the major allele and implies an interesting genetic architecture in this population. These results suggest that multiple loci underlie T2DM susceptibility in the African-American population and that these loci are distinct from those identified in other ethnic populations

    Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses

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    Brassinosteroids (BRs) are a group of plant steroid hormones involved in regulating growth, development, and stress responses. Many components of the BR pathway have previously been identified and characterized. However, BR phenotyping experiments are typically performed in a low-throughput manner, such as on Petri plates. Additionally, the BR pathway affects drought responses, but drought experiments are time consuming and difficult to control. To mitigate these issues and increase throughput, we developed the Robotic Assay for Drought (RoAD) system to perform BR and drought response experiments in soil-grown Arabidopsis plants. RoAD is equipped with a robotic arm, a rover, a bench scale, a precisely controlled watering system, an RGB camera, and a laser profilometer. It performs daily weighing, watering, and imaging tasks and is capable of administering BR response assays by watering plants with Propiconazole (PCZ), a BR biosynthesis inhibitor. We developed image processing algorithms for both plant segmentation and phenotypic trait extraction to accurately measure traits including plant area, plant volume, leaf length, and leaf width. We then applied machine learning algorithms that utilize the extracted phenotypic parameters to identify image-derived traits that can distinguish control, drought-treated, and PCZ-treated plants. We carried out PCZ and drought experiments on a set of BR mutants and Arabidopsis accessions with altered BR responses. Finally, we extended the RoAD assays to perform BR response assays using PCZ in Zea mays (maize) plants. This study establishes an automated and non-invasive robotic imaging system as a tool to accurately measure morphological and growth-related traits of Arabidopsis and maize plants in 3D, providing insights into the BR-mediated control of plant growth and stress responses.This is the published version of the following article: Xiang, Lirong, Trevor M. Nolan, Yin Bao, Mitch Elmore, Taylor Tuel, Jingyao Gai, Dylan Shah et al. "Robotic Assay for Drought (RoAD): an automated phenotyping system for brassinosteroid and drought responses." The Plant Journal 107, no. 6 (2021): 1837-1853. DOI: 10.1111/tpj.15401. Copyright 2021 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. Posted with permission
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