Browsing by Subject "Genetic heterogeneity"

Now showing 1 - 3 of 3
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    Beyond GWAS: Investigating Structural Variants and Their Segregation in Familial Alzheimer’s Disease
    (Wiley, 2025-01-09) Gunasekaran, Tamil Iniyan; Reyes-Dumeyer, Dolly; Corvelo, André; Clarke, Wayne E.; Evani, Uday S.; Byrska-Bishop, Marta S.; Basile, Anna O.; Runnels, Alexi; Musunuri, Rajeeva O.; Narzisi, Giuseppe; Faber, Kelley M.; Goate, Alison M.; Boeve, Brad F.; Cruchaga, Carlos; Pericak-Vance, Margaret A.; Haines, Jonathan L.; Rosenberg, Roger N.; Tsuang, Debby W.; Rivera Mejia, Diones; Medrano, Martin; Lantigua, Rafael A.; Sweet, Robert; Bennett, David A.; Wilson, Robert S.; Foroud, Tatiana M.; Dalgard, Clifton L.; Mayeux, Richard; Zody, Michael; Vardarajan, Badri N.; Medical and Molecular Genetics, School of Medicine
    Background: Late‐Onset Alzheimer’s Disease (LOAD) is characterized by genetic heterogeneity and there is no single model explaining the genetic mode of inheritance. To date, more than 70 genetic loci associated with AD have been identified but they explain only a small proportion of AD heritability. Structural variants (SVs) may explain some of the missing AD heritability, and specifically, their segregation in AD families has yet to be investigated. Method: We analyzed WGS data from 197 NHW families (926 subjects, 58.5% affected) and 214 CH families (1,340 subjects, 59.17% affected). Manta, Absinthe, and MELT were used for large insertions/deletions calling from short‐read WGS, combined with Sniffles2 calls from 4 ONT‐sequenced genomes and an external SV call set from HGSVC on 32 PacBio‐sequenced genomes from the 1000 Genomes Project. Genotyping produced a unified project‐level VCF. We identified 45,251 insertions and 76,566 deletions genome‐wide. Variants were tested for segregation and pathogenicity using Annot‐SV, cadd‐SV, and Variant Effect Predictor. Segregation required SV presence in all affected family members and only in unaffected members five years younger than average disease onset. Result: We identified 453 insertions and 598 deletions segregating in 78.68% and 87.31% of NHW families, respectively. In CH families, 432 insertions and 460 deletions were segregating in 75.23% and 72.90% of the families, respectively. Genes overlapping with the SVs exhibited high expression levels in brain tissues. Notably, around 93% of insertions and 76% of deletions segregating in NHW and CH families were less than 1 kilobase pair (1kbp) in length. A total of 79 insertions and 96 deletions were found to be segregating in both NHW and CH families. Interestingly, a segregating insertion was observed in CH families overlapping within the CACNA2D3 gene, which was previously reported in a CH GWAS for clinical AD. A deletion segregating in NHW overlapped with the PSEN1, and another in a CH family overlapped with the PTK2B gene. Conclusion: Our findings suggested that there are several SVs associated with familial AD across CH and NHW families. Prioritizing the SVs based on their effects on gene function and expression will be helpful in understanding their contributions in AD.
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    Exclusion of Class III malocclusion candidate loci in Brazilian families
    (SAGE Publications, 2011-10) Cruz, R.M.; Hartsfield, J.K., Jr.; Falcão-Alencar, G.; Koller, D.L.; Pereira, R.W.; Mah, J.; Ferrari, I.; Oliveira, S.F.; Medical and Molecular Genetics, School of Medicine
    The role played by genetic components in the etiology of the Class III phenotype, a class of dental malocclusion, is not yet understood. Regions that may be related to the development of Class III malocclusion have been suggested previously. The aim of this study was to search for genetic linkage with 6 microsatellite markers (D1S234, D4S3038, D6S1689, D7S503, D10S1483, and D19S566), near previously proposed candidate regions for Class III. We performed a two-point parametric linkage analysis for 42 affected individuals from 10 Brazilian families with a positive Class III malocclusion segregation. Analysis of our data indicated that there was no evidence for linkage of any of the 6 microsatellite markers to a Class III locus at = zero, with data supporting exclusion for 5 of the 6 markers evaluated. The present work reinforces that Class III is likely to demonstrate locus heterogeneity, and there is a dependency of the genetic background of the population in linkage studies.
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    Genetic Risk for Alcohol Use Disorder in Relation to Individual Symptom Criteria: Do Polygenic Indices Provide Unique Information for Understanding Severity and Heterogeneity?
    (medRxiv, 2024-09-23) Kim, Yongguk; Lane, Sean P.; Miller, Alex P.; Wilhelmsen, Kirk C.; Gizer, Ian R.; Psychiatry, School of Medicine
    Alcohol Use Disorder (AUD) is a heterogenous category with many unique configurations of symptoms. Previous investigations of AUD heterogeneity using molecular genetics methods studied the association between genetic liability and individual AUD symptoms at the latent level or focusing on a small number of genetic variants. Notably, these studies did not investigate potential severity differences between symptoms in their genetic analyses. Therefore, the current study aimed to examine the genetic risk for individual AUD symptom criteria by using a polygenic risk score (PRS) approach to assess the relative severity of each AUD symptom and test for associates with AUD symptoms above and beyond a unidimensional AUD construct. An AUD PRS was created using summary statistics obtained from published genome-wide association studies (GWAS), and Multiple Indicators Multiple Causes (MIMIC) models were employed to examine the effect of the PRS on overall AUD severity as well as on individual symptoms after accounting for this overall effect. The phenotypic severity of AUD symptoms was highly correlated with the genetic severity of AUD symptoms (r = 0.78). Results of MIMIC models indicated that the AUD PRS significantly predicted the AUD factor. Regression paths testing the unique, direct effects of the PRS on individual AUD symptoms, independent of the latent AUD factor, were not significant. These results imply that PRSs derived from GWAS of AUD influence symptom expression through a single genetic factor that is highly correlated with the relative severity of individual symptoms when measured at the phenotypic level. Item-level GWAS of AUD symptoms are needed to further parse heterogeneous symptom expression and allow for more nuanced tests of these conclusions.