scholarly journals Common and Rare Variants in the Exons and Regulatory Regions of Osteoporosis-Related Genes Improve Osteoporotic Fracture Risk Prediction

2014 ◽  
Vol 99 (11) ◽  
pp. E2400-E2411 ◽  
Author(s):  
Seung Hun Lee ◽  
Moo Il Kang ◽  
Seong Hee Ahn ◽  
Kyeong-Hye Lim ◽  
Gun Eui Lee ◽  
...  
Keyword(s):  
Fracture Risk ◽  
Osteoporotic Fracture ◽  
Rare Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Regulatory Regions ◽  
Genetic Profiling ◽  
Functional Variants

Context: Osteoporotic fracture risk is highly heritable, but genome-wide association studies have explained only a small proportion of the heritability to date. Genetic data may improve prediction of fracture risk in osteopenic subjects and assist early intervention and management. Objective: To detect common and rare variants in coding and regulatory regions related to osteoporosis-related traits, and to investigate whether genetic profiling improves the prediction of fracture risk. Design and Setting: This cross-sectional study was conducted in three clinical units in Korea. Participants: Postmenopausal women with extreme phenotypes (n = 982) were used for the discovery set, and 3895 participants were used for the replication set. Main Outcome Measure: We performed targeted resequencing of 198 genes. Genetic risk scores from common variants (GRS-C) and from common and rare variants (GRS-T) were calculated. Results: Nineteen common variants in 17 genes (of the discovered 34 functional variants in 26 genes) and 31 rare variants in five genes (of the discovered 87 functional variants in 15 genes) were associated with one or more osteoporosis-related traits. Accuracy of fracture risk classification was improved in the osteopenic patients by adding GRS-C to fracture risk assessment models (6.8%; P < .001) and was further improved by adding GRS-T (9.6%; P < .001). GRS-C improved classification accuracy for vertebral and nonvertebral fractures by 7.3% (P = .005) and 3.0% (P = .091), and GRS-T further improved accuracy by 10.2% (P < .001) and 4.9% (P = .008), respectively. Conclusions: Our results suggest that both common and rare functional variants may contribute to osteoporotic fracture and that adding genetic profiling data to current models could improve the prediction of fracture risk in an osteopenic individual.

Abstract 367: Extreme High-Density Lipoprotein Cholesterol Genetics: An Assortment of Large and Small Polygenic Effects

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Jacqueline S Dron ◽  
Jian Wang ◽  
Cécile Low-Kam ◽  
Sumeet A Khetarpal ◽  
John F Robinson ◽  
...  
Keyword(s):  
Large Scale ◽  
Genetic Basis ◽  
Rare Variants ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Copy Number Variations ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Targeted Next Generation Sequencing ◽  
Common Genetic Variants

Rationale: Although HDL-C levels are known to have a complex genetic basis, most studies have focused solely on identifying rare variants with large phenotypic effects to explain extreme HDL-C phenotypes. Objective: Here we concurrently evaluate the contribution of both rare and common genetic variants, as well as large-scale copy number variations (CNVs), towards extreme HDL-C concentrations. Methods: In clinically ascertained patients with low ( N =136) and high ( N =119) HDL-C profiles, we applied our targeted next-generation sequencing panel (LipidSeq TM ) to sequence genes involved in HDL metabolism, which were subsequently screened for rare variants and CNVs. We also developed a novel polygenic trait score (PTS) to assess patients’ genetic accumulations of common variants that have been shown by genome-wide association studies to associate primarily with HDL-C levels. Two additional cohorts of patients with extremely low and high HDL-C (total N =1,746 and N =1,139, respectively) were used for PTS validation. Results: In the discovery cohort, 32.4% of low HDL-C patients carried rare variants or CNVs in primary ( ABCA1 , APOA1 , LCAT ) and secondary ( LPL , LMF1 , GPD1 , APOE ) HDL-C–altering genes. Additionally, 13.4% of high HDL-C patients carried rare variants or CNVs in primary ( SCARB1 , CETP , LIPC , LIPG ) and secondary ( APOC3 , ANGPTL4 ) HDL-C–altering genes. For polygenic effects, patients with abnormal HDL-C profiles but without rare variants or CNVs were ~2-fold more likely to have an extreme PTS compared to normolipidemic individuals, indicating an increased frequency of common HDL-C–associated variants in these patients. Similar results in the two validation cohorts demonstrate that this novel PTS successfully quantifies common variant accumulation, further characterizing the polygenic basis for extreme HDL-C phenotypes. Conclusions: Patients with extreme HDL-C levels have various combinations of rare variants, common variants, or CNVs driving their phenotypes. Fully characterizing the genetic basis of HDL-C levels must extend to encompass multiple types of genetic determinants—not just rare variants—to further our understanding of this complex, controversial quantitative trait.

SMARCA2 common variant association and rare variant excess in Schizophrenia patients from an Algerian Trio Cohort

2011 ◽  
Vol 26 (S2) ◽  
pp. 1346-1346
Author(s):  
D. Benmessaoud ◽  
A.-M. Lepagnol-Bestel ◽  
M. Delepine ◽  
J. Hager ◽  
J.-M. Moalic ◽  
...  
Keyword(s):  
Rare Variants ◽  
Association Studies ◽  
Common Variant ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Fisher Test ◽  
Coding Regions ◽  
Genome Wide ◽  
Whole Exome ◽  
Positive Evolution

Genome wide association studies (GWAS) of Schizophrenia (SZ) patients have identified common variants in ten genes including SMARCA2 (Koga et al., HMG, 2009). We found that the SZ-GWAS genes are part of an interacting network centered on SMARCA2 (Loe-Mie et al., HMG, 2010). Furthermore, SMARCA2 was found disrupted in SZ (Walsh et al., Science, 2008). SMARCA2 encodes the ATPase (BRM) of the SWI/SNF chromatin remodeling complex that is at the interface of genome and environmental adaptation.Taking advantage of an Algerian trio cohort of one hundred SZ patients (Benmessaoud et al., BMC Psychiatry, 2008), we replicated the association of SNP rs2296212 localized in exon 33, already shown associated in Koga study and resulting in D1546E amino acid change in the SMARCA2 protein. We studied SMARCA2 codons and found that exon 33 displays a signature of positive evolution in the primate lineage.Our working hypothesis is that the coding regions displaying positive selection are target of novel rare variants. To address this question, we sequenced two exons displaying positive evolution and one exon without evidence of positive evolution.We found (i) that rare variants are significantly in excess in SZ-patients compared to their parents (p = 0.038, Fisher test) and (ii) a higher proportion of rare variants in the primate-accelerated exons compared with the non-evolutionary exon in SZ-patients (p = 0.032, Fisher test).SMARCA2 exon sequencing and whole exome sequencing from patients harboring SNP rs2296212 common variant are under progress. Altogether, these results are expected to give new insights into the genetic architecture of SZ.

scholarly journals Recent advances in the genetic association between osteoporotic fracture and sarcopenia

2021 ◽  
Vol 3 (1) ◽  
pp. 02-09
Author(s):  
Qiaocong Chen ◽  
◽  
Huiling Lou ◽  
Cheng Peng
Keyword(s):  
Fracture Risk ◽  
Osteoporotic Fracture ◽  
Musculoskeletal Diseases ◽  
Association Studies ◽  
Genetic Correlations ◽  
Osteoporotic Fractures ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Determinants ◽  
Genome Wide

The risk of osteoporotic fracture can be viewed as a function of loading conditions and the ability of the bone to withstand the load. Skeletal loads are dominated by muscle action. Recently, it has become clear that bone and muscle share genetic determinants. Involvement of the musculoskeletal system manifests as bone loss (osteoporosis) and muscle wasting (sarcopenia). There is clinical evidence that osteoporotic fractures are significantly associated with sarcopenia, and sarcopenia may be a potential predictive factor for fracture risk, which suggests that there may be shared genetic determinants between sarcopenia and osteoporotic fracture. In recent years, genome-wide association studies (GWASs) studies have found that both lean mass and hand grip strength are associated with fracture risk, which may provide a possible endophenotype for elucidating the potential genetic study of fracture risk. Our effort to understand the clinical and genetic correlations between osteoporotic fracture and sarcopenia is helpful to understand the interaction between muscle and bone, and to study the etiology of complex musculoskeletal diseases. Identifying potentially important genetic variations in bone and muscle, measuring these variations using state-of-the-art technology, and replicating these experiments in humans and large animals will provide potential drug or intervention targets for osteoporotic fracture valuable in the future. Keywords: Genetics, osteoporosis, fracture, sarcopenia, genome-wide association studies, single nucleotide polymorphism

scholarly journals A Novel Approach for the Simultaneous Analysis of Common and Rare Variants in Complex Traits

2012 ◽  
Vol 6 ◽  
pp. BBI.S8852 ◽  
Author(s):  
Ao Yuan ◽  
Guanjie Chen ◽  
Yanxun Zhou ◽  
Amy Bentley ◽  
Charles Rotimi
Keyword(s):  
Complex Traits ◽  
Rare Variants ◽  
Sequence Data ◽  
Association Studies ◽  
Simultaneous Analysis ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Disease Etiology ◽  
Novel Approach ◽  
Common Genetic Variants

Genome-wide association studies (GWAS) have been successful in detecting common genetic variants underlying common traits and diseases. Despite the GWAS success stories, the percent trait variance explained by GWAS signals, the so called “missing heritability” has been, at best, modest. Also, the predictive power of common variants identified by GWAS has not been encouraging. Given these observations along with the fact that the effects of rare variants are often, by design, unaccounted for by GWAS and the availability of sequence data, there is a growing need for robust analytic approaches to evaluate the contribution of rare variants to common complex diseases. Here we propose a new method that enables the simultaneous analysis of the association between rare and common variants in disease etiology. We refer to this method as SCARVA (simultaneous common and rare variants analysis). SCARVA is simple to use and is efficient. We used SCARVA to analyze two independent real datasets to identify rare and common variants underlying variation in obesity among participants in the Africa America Diabetes Mellitus (AADM) study and plasma triglyceride levels in the Dallas Heart Study (DHS). We found common and rare variants associated with both traits, consistent with published results.

scholarly journals Deep genotype imputation captures virtually all heritability of autoimmune vitiligo

2020 ◽  
Vol 29 (5) ◽  
pp. 859-863 ◽  
Author(s):  
Genevieve H L Roberts ◽  
Stephanie A Santorico ◽  
Richard A Spritz
Keyword(s):  
Complex Disease ◽  
Rare Variants ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Genome Wide ◽  
Autoimmune Vitiligo ◽  
Family Based ◽  
Project Data

Abstract Autoimmune vitiligo is a complex disease involving polygenic risk from at least 50 loci previously identified by genome-wide association studies. The objectives of this study were to estimate and compare vitiligo heritability in European-derived patients using both family-based and ‘deep imputation’ genotype-based approaches. We estimated family-based heritability (h2FAM) by vitiligo recurrence among a total 8034 first-degree relatives (3776 siblings, 4258 parents or offspring) of 2122 unrelated vitiligo probands. We estimated genotype-based heritability (h2SNP) by deep imputation to Haplotype Reference Consortium and the 1000 Genomes Project data in unrelated 2812 vitiligo cases and 37 079 controls genotyped genome wide, achieving high-quality imputation from markers with minor allele frequency (MAF) as low as 0.0001. Heritability estimated by both approaches was exceedingly high; h2FAM = 0.75–0.83 and h2SNP = 0.78. These estimates are statistically identical, indicating there is essentially no remaining ‘missing heritability’ for vitiligo. Overall, ~70% of h2SNP is represented by common variants (MAF > 0.01) and 30% by rare variants. These results demonstrate that essentially all vitiligo heritable risk is captured by array-based genotyping and deep imputation. These findings suggest that vitiligo may provide a particularly tractable model for investigation of complex disease genetic architecture and predictive aspects of personalized medicine.

scholarly journals Detecting association of rare and common variants by adaptive combination of P-values

2015 ◽  
Vol 97 ◽  
Author(s):  
YAJING ZHOU ◽  
YONG WANG
Keyword(s):  
Rare Variants ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Next Generation Sequencing Technology ◽  
Adaptive Combination ◽  
Genome Wide ◽  
Wide Range ◽  
Causal Variants ◽  
Burden Tests

SummaryGenome-wide association studies (GWAS) can detect common variants associated with diseases. Next generation sequencing technology has made it possible to detect rare variants. Most of association tests, including burden tests and nonburden tests, mainly target rare variants by upweighting rare variant effects and downweighting common variant effects. But there is increasing evidence that complex diseases are caused by both common and rare variants. In this paper, we extend the ADA method (adaptive combination of P-values; Lin et al., 2014) for rare variants only and propose a RC-ADA method (common and rare variants by adaptive combination of P-values). Our proposed method combines the per-site P-values with the weights based on minor allele frequencies (MAFs). The RC-ADA is robust to directions of effects of causal variants and inclusion of a high proportion of neutral variants. The performance of the RC-ADA method is compared with several other association methods. Extensive simulation studies show that the RC-ADA method is more powerful than other association methods over a wide range of models.

scholarly journals Assessing thyroid cancer risk using polygenic risk scores

2020 ◽  
Vol 117 (11) ◽  
pp. 5997-6002 ◽  
Author(s):  
Sandya Liyanarachchi ◽  
Julius Gudmundsson ◽  
Egil Ferkingstad ◽  
Huiling He ◽  
Jon G. Jonasson ◽  
...  
Keyword(s):  
Thyroid Cancer ◽  
Association Studies ◽  
Study Groups ◽  
Receiver Operating Curve ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Common Variants ◽  
Polygenic Risk

Genome-wide association studies (GWASs) have identified at least 10 single-nucleotide polymorphisms (SNPs) associated with papillary thyroid cancer (PTC) risk. Most of these SNPs are common variants with small to moderate effect sizes. Here we assessed the combined genetic effects of these variants on PTC risk by using summarized GWAS results to build polygenic risk score (PRS) models in three PTC study groups from Ohio (1,544 patients and 1,593 controls), Iceland (723 patients and 129,556 controls), and the United Kingdom (534 patients and 407,945 controls). A PRS based on the 10 established PTC SNPs showed a stronger predictive power compared with the clinical factors model, with a minimum increase of area under the receiver-operating curve of 5.4 percentage points (P≤ 1.0 × 10−9). Adding an extended PRS based on 592,475 common variants did not significantly improve the prediction power compared with the 10-SNP model, suggesting that most of the remaining undiscovered genetic risk in thyroid cancer is due to rare, moderate- to high-penetrance variants rather than to common low-penetrance variants. Based on the 10-SNP PRS, individuals in the top decile group of PRSs have a close to sevenfold greater risk (95% CI, 5.4–8.8) compared with the bottom decile group. In conclusion, PRSs based on a small number of common germline variants emphasize the importance of heritable low-penetrance markers in PTC.

scholarly journals Polygenic inheritance, GWAS, polygenic risk scores, and the search for functional variants

2020 ◽  
Vol 117 (32) ◽  
pp. 18924-18933
Author(s):  
Daniel J. M. Crouch ◽  
Walter F. Bodmer
Keyword(s):  
Genetic Association ◽  
Complex Traits ◽  
Rare Variants ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Mendelian Inheritance ◽  
Risk Scores ◽  
Polygenic Inheritance ◽  
Polygenic Risk ◽  
Functional Variants

The reconciliation between Mendelian inheritance of discrete traits and the genetically based correlation between relatives for quantitative traits was Fisher’s infinitesimal model of a large number of genetic variants, each with very small effects, whose causal effects could not be individually identified. The development of genome-wide genetic association studies (GWAS) raised the hope that it would be possible to identify single polymorphic variants with identifiable functional effects on complex traits. It soon became clear that, with larger and larger GWAS on more and more complex traits, most of the significant associations had such small effects, that identifying their individual functional effects was essentially hopeless. Polygenic risk scores that provide an overall estimate of the genetic propensity to a trait at the individual level have been developed using GWAS data. These provide useful identification of groups of individuals with substantially increased risks, which can lead to recommendations of medical treatments or behavioral modifications to reduce risks. However, each such claim will require extensive investigation to justify its practical application. The challenge now is to use limited genetic association studies to find individually identifiable variants of significant functional effect that can help to understand the molecular basis of complex diseases and traits, and so lead to improved disease prevention and treatment. This can best be achieved by 1) the study of rare variants, often chosen by careful candidate assessment, and 2) the careful choice of phenotypes, often extremes of a quantitative variable, or traits with relatively high heritability.

scholarly journals Rare variant analysis in eczema identifies exonic variants in DUSP1, NOTCH4 and SLC9A4

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Sarah Grosche ◽  
Ingo Marenholz ◽  
Jorge Esparza-Gordillo ◽  
Aleix Arnau-Soler ◽  
Erola Pairo-Castineira ◽  
...  
Keyword(s):  
Cell Function ◽  
Immune Cell ◽  
Rare Variants ◽  
Association Studies ◽  
Large Population ◽  
Low Frequency ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Functional Protein

AbstractPrevious genome-wide association studies revealed multiple common variants involved in eczema but the role of rare variants remains to be elucidated. Here, we investigate the role of rare variants in eczema susceptibility. We meta-analyze 21 study populations including 20,016 eczema cases and 380,433 controls. Rare variants are imputed with high accuracy using large population-based reference panels. We identify rare exonic variants in DUSP1, NOTCH4, and SLC9A4 to be associated with eczema. In DUSP1 and NOTCH4 missense variants are predicted to impact conserved functional domains. In addition, five novel common variants at SATB1-AS1/KCNH8, TRIB1/LINC00861, ZBTB1, TBX21/OSBPL7, and CSF2RB are discovered. While genes prioritized based on rare variants are significantly up-regulated in the skin, common variants point to immune cell function. Over 20% of the single nucleotide variant-based heritability is attributable to rare and low-frequency variants. The identified rare/low-frequency variants located in functional protein domains point to promising targets for novel therapeutic approaches to eczema.

scholarly journals MEPE loss-of-function variant associates with decreased bone mineral density and increased fracture risk

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Ida Surakka ◽  
◽  
Lars G. Fritsche ◽  
Wei Zhou ◽  
Joshua Backman ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Fracture Risk ◽  
Bone Mineral ◽  
Association Studies ◽  
Forearm Fracture ◽  
Risk Scores ◽  
Health Study ◽  
Loss Of Function ◽  
Mineral Density ◽  
Functional Variants

Abstract A major challenge in genetic association studies is that most associated variants fall in the non-coding part of the human genome. We searched for variants associated with bone mineral density (BMD) after enriching the discovery cohort for loss-of-function (LoF) mutations by sequencing a subset of the Nord-Trøndelag Health Study, followed by imputation in the remaining sample (N = 19,705), and identified ten known BMD loci. However, one previously unreported variant, LoF mutation in MEPE, p.(Lys70IlefsTer26, minor allele frequency [MAF] = 0.8%), was associated with decreased ultradistal forearm BMD (P-value = 2.1 × 10−18), and increased osteoporosis (P-value = 4.2 × 10−5) and fracture risk (P-value = 1.6 × 10−5). The MEPE LoF association with BMD and fractures was further evaluated in 279,435 UK (MAF = 0.05%, heel bone estimated BMD P-value = 1.2 × 10−16, any fracture P-value = 0.05) and 375,984 Icelandic samples (MAF = 0.03%, arm BMD P-value = 0.12, forearm fracture P-value = 0.005). Screening for the MEPE LoF mutations before adulthood could potentially prevent osteoporosis and fractures due to the lifelong effect on BMD observed in the study. A key implication for precision medicine is that high-impact functional variants missing from the publicly available cosmopolitan panels could be clinically more relevant than polygenic risk scores.

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