scholarly journals Targeted analysis of genomic regions enriched in African ancestry reveals novel classical HLA alleles associated with asthma in Southwestern Europeans

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eva Suarez-Pajes ◽  
Claudio Díaz-García ◽  
Héctor Rodríguez-Pérez ◽  
Jose M. Lorenzo-Salazar ◽  
Itahisa Marcelino-Rodríguez ◽  
...  
Keyword(s):  
Meta Analysis ◽  
African Ancestry ◽  
Genetic Ancestry ◽  
Asthma Prevalence ◽  
Hla Alleles ◽  
Targeted Analysis ◽  
Risk Variants ◽  
Genetic Risks ◽  
Hla Dqa1 ◽  
Genomic Regions

AbstractDespite asthma has a considerable genetic component, an important proportion of genetic risks remain unknown, especially for non-European populations. Canary Islanders have the largest African genetic ancestry observed among Southwestern Europeans and the highest asthma prevalence in Spain. Here we examined broad chromosomal regions previously associated with an excess of African genetic ancestry in Canary Islanders, with the aim of identifying novel risk variants associated with asthma susceptibility. In a two-stage cases-control study, we revealed a variant within HLA-DQB1 significantly associated with asthma risk (rs1049213, meta-analysis p = 1.30 × 10–7, OR [95% CI] = 1.74 [1.41–2.13]) previously associated with asthma and broad allergic phenotype. Subsequent fine-mapping analyses of classical HLA alleles revealed a novel allele significantly associated with asthma protection (HLA-DQA1*01:02, meta-analysis p = 3.98 × 10–4, OR [95% CI] = 0.64 [0.50–0.82]) that had been linked to infectious and autoimmune diseases, and peanut allergy. HLA haplotype analyses revealed a novel haplotype DQA1*01:02-DQB1*06:04 conferring asthma protection (meta-analysis p = 4.71 × 10–4, OR [95% CI] = 0.47 [0.29– 0.73]).

scholarly journals Targeted Analysis of Loci Enriched in African Ancestry in the Canary Islanders Reveals Novel Classic HLA Alleles Associated with Asthma Risk

2020 ◽  
Author(s):  
J.M. Lorenzo-Salazar ◽  
C. Díaz-García ◽  
H. Rodríguez-Pérez ◽  
I. Marcelino-Rodríguez ◽  
A. Corrales ◽  
...  
Keyword(s):  
African Ancestry ◽  
Hla Alleles ◽  
Targeted Analysis ◽  
Asthma Risk

scholarly journals Population structure in the MHC region

2021 ◽  
Author(s):  
Andre S Marostica ◽  
Kelly Nunes ◽  
Erick C Castelli ◽  
Nayara SB Silva ◽  
Bruce Weir ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Bone Marrow ◽  
Population Structure ◽  
Balancing Selection ◽  
African Ancestry ◽  
Human Diversity ◽  
Hla Alleles ◽  
Hla Genes ◽  
Geographic Regions ◽  
Genomic Regions

In his 1972 "The apportionment of human diversity", Richard Lewontin showed that, when averaged over loci, genetic diversity is predominantly attributable to differences among individuals within populations. However, selection on specific genes and genomic regions can alter the apportionment of diversity. We examine genetic diversity at the HLA loci, located within the MHC region. HLA genes code for proteins that are critical to adaptive immunity and are well-documented targets of balancing selection. The SNPs within HLA genes show strong signatures of balancing selection on large timescales and are broadly shared among populations, with low FST values. However, when we analyze haplotypes defined by these SNPs (i.e., which define "HLA alleles"), we find marked differences in frequencies between geographic regions. These differences are not reflected in the FST values because of the extreme polymorphism at HLA loci, illustrating challenges in interpreting FST. Differences in the frequency of HLA alleles among geographic regions are relevant to bone-marrow transplantation, which requires genetic identity at HLA loci between patient and donor. We explore the case of Brazil's bone-marrow registry, where a deficit of enrolled volunteers with African ancestry reduces the chance of finding donors for individuals with an MHC region of African ancestry.

Functional Evaluation of RNLS, a Gene Harboring Risk Variants for Type 1 Diabetes in European and African Ancestry Subjects

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1702-P
Author(s):  
SUNA ONENGUT-GUMUSCU ◽  
NOAH VOGLER ◽  
MARIA FAIDAS ◽  
REBECCA R. PICKIN ◽  
ELAINE GERSZ ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
African Ancestry ◽  
Functional Evaluation ◽  
Risk Variants

scholarly journals Investigating regions of shared genetic variation in attention deficit/hyperactivity disorder and major depressive disorder: a GWAS meta-analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Victoria Powell ◽  
Joanna Martin ◽  
Anita Thapar ◽  
Frances Rice ◽  
Richard J. L. Anney
Keyword(s):  
Attention Deficit Hyperactivity Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genetic Correlation ◽  
Attention Deficit ◽  
Meta Analysis ◽  
Major Depressive ◽  
Hyperactivity Disorder ◽  
High Level ◽  
Genomic Regions

AbstractAttention deficit/hyperactivity disorder (ADHD) demonstrates a high level of comorbidity with major depressive disorder (MDD). One possible contributor to this is that the two disorders show high genetic correlation. However, the specific regions of the genome that may be responsible for this overlap are unclear. To identify variants associated with both ADHD and MDD, we performed a meta-analysis of GWAS of ADHD and MDD. All genome wide significant (p < 5 × 10–8) SNPs in the meta-analysis that were also strongly associated (p < 5 × 10–4) independently with each disorder were followed up. These putatively pleiotropic SNPs were tested for additional associations across a broad range of phenotypes. Fourteen linkage disequilibrium-independent SNPs were associated with each disorder separately (p < 5 × 10–4) and in the cross-disorder meta-analysis (p < 5 × 10–8). Nine of these SNPs had not been highlighted previously in either individual GWAS. Evidence supported nine of the fourteen SNPs acting as eQTL and two as brain eQTL. Index SNPs and their genomic regions demonstrated associations with other mental health phenotypes. Through conducting meta-analysis on ADHD and MDD only, our results build upon the previously observed genetic correlation between ADHD and MDD and reveal novel genomic regions that may be implicated in this overlap.

Trans-Ethnic Meta-Analysis of Interactions Between Genetics and Early-Life Socioeconomic Context on Memory Performance and Decline in Older Americans

2021 ◽  
Author(s):  
Jessica D Faul ◽  
Minjung Kho ◽  
Wei Zhao ◽  
Kalee E Rumfelt ◽  
Miao Yu ◽  
...  
Keyword(s):  
Parental Education ◽  
Association Studies ◽  
Memory Performance ◽  
Meta Analysis ◽  
African Ancestry ◽  
Later Life ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Multiple Testing Correction ◽  
Socioeconomic Context

Abstract Background Later-life cognitive function is influenced by genetics as well as early- and later-life socioeconomic context. However, few studies have examined the interaction between genetics and early childhood factors. Methods Using gene-based tests (interaction sequence kernel association test [iSKAT]/iSKAT optimal unified test), we examined whether common and/or rare exonic variants in 39 gene regions previously associated with cognitive performance, dementia, and related traits had an interaction with childhood socioeconomic context (parental education and financial strain) on memory performance or decline in European ancestry (EA, N = 10 468) and African ancestry (AA, N = 2 252) participants from the Health and Retirement Study. Results Of the 39 genes, 22 in EA and 19 in AA had nominally significant interactions with at least one childhood socioeconomic measure on memory performance and/or decline; however, all but one (father’s education by solute carrier family 24 member 4 [SLC24A4] in AA) were not significant after multiple testing correction (false discovery rate [FDR] &lt; .05). In trans-ethnic meta-analysis, 2 genes interacted with childhood socioeconomic context (FDR &lt; .05): mother’s education by membrane-spanning 4-domains A4A (MS4A4A) on memory performance, and father’s education by SLC24A4 on memory decline. Both interactions remained significant (p &lt; .05) after adjusting for respondent’s own educational attainment, apolipoprotein-ε4 allele (APOE ε4) status, lifestyle factors, body mass index, and comorbidities. For both interactions in EA and AA, the genetic effect was stronger in participants with low parental education. Conclusions Examination of common and rare variants in genes discovered through genome-wide association studies shows that childhood context may interact with key gene regions to jointly impact later-life memory function and decline. Genetic effects may be more salient for those with lower childhood socioeconomic status.

scholarly journals Type 1 diabetes susceptibility determined by HLA alleles and CTLA-4 and insulin genes polymorphisms in Brazilians

2009 ◽  
Vol 53 (3) ◽  
pp. 368-373 ◽  
Author(s):  
Alessandro Clayton Souza Ferreira ◽  
Karina Braga Gomes ◽  
Ivan Barbosa Machado Sampaio ◽  
Vanessa Cristina de Oliveira ◽  
Victor Cavalcanti Pardini ◽  
...  
Keyword(s):  
Genetic Markers ◽  
Multifactorial Disease ◽  
Environmental Aspects ◽  
Diabetes Susceptibility ◽  
Time Resolved ◽  
Hla Alleles ◽  
Significant Difference ◽  
Hla Dqa1

INTRODUCTION:Type 1A diabetes mellitus (T1ADM) is a multifactorial disease in which genetic and environmental aspects are important to its development. The association of genetic variations with disease has been demonstrated in several studies; however, the role of some gene loci has not yet been fully elucidated. OBJECTIVE:To compare the frequency of HLA alleles and polymorphism in CTLA-4 and insulin genes in Brazilians with T1ADM and individuals without the disease, as well as to identify genetic markers that are able to discriminate between diabetic and non-diabetic individuals. METHODS: The presence of HLA DQB1, DQA1 and DRB1 alleles, as well as the -2221 MspI polymorphism in the insulin gene and 49 A/G in the CTLA-4 gene were identified by the "Time-resolved fluorometer" technique after hybridization with probes labeled with Eu (III) / Sm (III) and Tb (III). RESULTS: The DQB1 *0302 and DQA1 *03 alleles were identified as predisposed to T1ADM, and the DQB1 *0301 allele presented a protective effect against the disease.The DQA1 label proved to be able to differentiate between 71.13% of the diabetic and non-diabetic individuals.This value increased to 82.47% when the DQB1 label was added. No significant difference in the frequency of polymorphisms in the insulin and CTLA-4 genes was observed between the two groups. CONCLUSIONS: The genetic markers that best characterized and discriminated diabetic and non-diabetic individuals were the HLA DQA1 and DQB1.alleles.

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