scholarly journals Polygenic Risk Score of Sporadic late Onset Alzheimer Disease Reveals a Shared Architecture with the Familial and Early Onset Forms

2017 ◽  
Author(s):  
Jorge L Del-Aguila ◽  
Benjamin Saef ◽  
Kathleen Black ◽  
Maria Victoria Fernandez ◽  
John Budde ◽  
...  
Keyword(s):  
Early Onset ◽  
Genetic Architecture ◽  
Late Onset ◽  
Age At Onset ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Risk Variants ◽  
Genome Wide ◽  
Load Risk

AbstractObjective:To determine whether the genetic architecture of sporadic late-onset Alzheimer’s Disease (sLOAD) has an effect on familial late-onset AD (fLOAD), sporadic early-onset (sEOAD) and autosomal dominant early-onset (eADAD).Methods:Polygenic risk scores (PRS) were constructed using previously identified 21 genome-wide significant loci for LOAD risk.Results:We found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. sEOAD showed the highest odds for the PRS (OR=2.27; p=1.29×10-7), followed by fLOAD (OR=1.75; p=1.12×10-7) and sLOAD (OR=1.40; p=1.21×10-3). PRS is associated with cerebrospinal fluid ptau181-Aβ42on eADAD.Conclusion:Our analysis confirms that the genetic factors identified for sLOAD also modulate risk in fLOAD and sEOAD cohorts. Furthermore, our results suggest that the burden of these risk variants is associated with familial clustering and earlier-onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.

Migraine, Human Genetics and a Passion for Science

2020 ◽  
Vol 23 (2) ◽  
pp. 105-106
Author(s):  
Dale R. Nyholt
Keyword(s):  
Genetic Architecture ◽  
Latent Class ◽  
Human Genetics ◽  
Polygenic Risk Score ◽  
Association Analyses ◽  
Polygenic Risk ◽  
The Past ◽  
Risk Variants ◽  
Genome Wide ◽  
Wide Range

AbstractThis note reflects on my collaborations with Nick Martin and the GenEpi group over the past 20 years. Over the past two decades, our work together has focused on gene mapping and understanding the genetic architecture of a wide range of traits with particular foci on migraine and common baldness. Our migraine research has included latent class and twin analyses cumulating in genome-wide association analyses which had identified 44 (34 new) risk variants for migraine. Leveraging these results through polygenic risk score analyses identified subgroups of patients likely to respond to triptans (an acute migraine drug), providing the first step toward precision medicine in migraine [Kogelman et al. (2019) Neurology Genetics, 5, e364].

scholarly journals Genetic Contributions to Early and Late Onset Ischemic Stroke

2021 ◽  
Author(s):  
Thomas Jaworek ◽  
Huichun Xu ◽  
Brady Gaynor ◽  
John Cole ◽  
Kristiina Rannikmae ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Venous Thromboembolism ◽  
Blood Group ◽  
Early Onset ◽  
Late Onset ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Blood Group A ◽  
Genome Wide ◽  
Group A

Abstract Objective: To determine the contribution of common genetic variants to risk of early onset ischemic stroke (IS). Methods: We performed a meta-analysis of genome-wide association studies of early onset IS, ages 18-59, using individual level data or summary statistics in 16,927 cases and 576,353 non-stroke controls from 48 different studies across North America, Europe, and Asia. We further compared effect sizes at our most genome-wide significant loci between early and late onset IS and compared polygenic risk scores for venous thromboembolism between early versus later onset IS. Results: We observed an association between early onset IS and ABO, a known stroke locus. The effect size of the peak ABO SNP, rs8176685, was significantly larger in early compared to late onset IS (OR 1.17 (95% C.I.: 1.11-1.22) vs 1.05 (0.99-1.12); p for interaction = 0.008). Analysis of genetically determined ABO blood groups revealed that early onset IS cases were more likely to have blood group A and less likely to have blood group O compared to both non-stroke controls and to late onset IS cases. Using polygenic risk scores, we observed that greater genetic risk for venous thromboembolism, another prothrombotic condition, was more strongly associated with early, compared to late, onset IS (p=0.008). Conclusion: The ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with early onset IS, compared with late onset IS, supporting a stronger role of prothrombotic factors in early onset IS.

scholarly journals Age-related late-onset disease heritability patterns and implications for genome-wide association studies

2018 ◽  
Author(s):  
Roman Teo Oliynyk
Keyword(s):  
Old Age ◽  
Cumulative Incidence ◽  
Late Onset ◽  
Association Studies ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Cerebral Stroke ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Genome Wide

AbstractBackgroundGenome-wide association studies and other computational biology techniques are gradually discovering the causal gene variants that contribute to late-onset human diseases. After more than a decade of genome-wide association study efforts, these can account for only a fraction of the heritability implied by familial studies, the so-called “missing heritability” problem.MethodsComputer simulations of polygenic late-onset diseases in an aging population have quantified the risk allele frequency decrease at older ages caused by individuals with higher polygenic risk scores becoming ill proportionately earlier. This effect is most prominent for diseases characterized by high cumulative incidence and high heritability, examples of which include Alzheimer’s disease, coronary artery disease, cerebral stroke, and type 2 diabetes.ResultsThe incidence rate for late-onset diseases grows exponentially for decades after early onset ages, guaranteeing that the cohorts used for genome-wide association studies overrepresent older individuals with lower polygenic risk scores, whose disease cases are disproportionately due to environmental causes such as old age itself. This mechanism explains the decline in clinical predictive power with age and the lower discovery power of familial studies of heritability and genome-wide association studies. It also explains the relatively constant-with-age heritability found for late-onset diseases of lower prevalence, exemplified by cancers.ConclusionsFor late-onset polygenic diseases showing high cumulative incidence together with high initial heritability, rather than using relatively old age-matched cohorts, study cohorts combining the youngest possible cases with the oldest possible controls may significantly improve the discovery power of genome-wide association studies.

scholarly journals Multiplex melanoma families are enriched for polygenic risk

2020 ◽  
Vol 29 (17) ◽  
pp. 2976-2985
Author(s):  
Matthew H Law ◽  
Lauren G Aoude ◽  
David L Duffy ◽  
Georgina V Long ◽  
Peter A Johansson ◽  
...  
Keyword(s):  
Cutaneous Melanoma ◽  
Cumulative Effect ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Single Family ◽  
Polygenic Risk ◽  
Complex Disorders ◽  
Risk Variants ◽  
High Penetrance ◽  
Genetic Risks

Abstract Cancers, including cutaneous melanoma, can cluster in families. In addition to environmental etiological factors such as ultraviolet radiation, cutaneous melanoma has a strong genetic component. Genetic risks for cutaneous melanoma range from rare, high-penetrance mutations to common, low-penetrance variants. Known high-penetrance mutations account for only about half of all densely affected cutaneous melanoma families, and the causes of familial clustering in the remainder are unknown. We hypothesize that some clustering is due to the cumulative effect of a large number of variants of individually small effect. Common, low-penetrance genetic risk variants can be combined into polygenic risk scores. We used a polygenic risk score for cutaneous melanoma to compare families without known high-penetrance mutations with unrelated melanoma cases and melanoma-free controls. Family members had significantly higher mean polygenic load for cutaneous melanoma than unrelated cases or melanoma-free healthy controls (Bonferroni-corrected t-test P = 1.5 × 10−5 and 6.3 × 10−45, respectively). Whole genome sequencing of germline DNA from 51 members of 21 families with low polygenic risk for melanoma identified a CDKN2A p.G101W mutation in a single family but no other candidate high-penetrance melanoma susceptibility genes. This work provides further evidence that melanoma, like many other common complex disorders, can arise from the joint action of multiple predisposing factors, including rare high-penetrance mutations, as well as via a combination of large numbers of alleles of small effect.

Performance of polygenic risk scores for cancer prediction in an academic biobank.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 1528-1528
Author(s):  
Heena Desai ◽  
Anh Le ◽  
Ryan Hausler ◽  
Shefali Verma ◽  
Anurag Verma ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Variants ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
European Americans ◽  
Genome Wide ◽  
Common Genetic Variants

1528 Background: The discovery of rare genetic variants associated with cancer have a tremendous impact on reducing cancer morbidity and mortality when identified; however, rare variants are found in less than 5% of cancer patients. Genome wide association studies (GWAS) have identified hundreds of common genetic variants significantly associated with a number of cancers, but the clinical utility of individual variants or a polygenic risk score (PRS) derived from multiple variants is still unclear. Methods: We tested the ability of polygenic risk score (PRS) models developed from genome-wide significant variants to differentiate cases versus controls in the Penn Medicine Biobank. Cases for 15 different cancers and cancer-free controls were identified using electronic health record billing codes for 11,524 European American and 5,994 African American individuals from the Penn Medicine Biobank. Results: The discriminatory ability of the 15 PRS models to distinguish their respective cancer cases versus controls ranged from 0.68-0.79 in European Americans and 0.74-0.93 in African Americans. Seven of the 15 cancer PRS trended towards an association with their cancer at a p<0.05 (Table), and PRS for prostate, thyroid and melanoma were significantly associated with their cancers at a bonferroni corrected p<0.003 with OR 1.3-1.6 in European Americans. Conclusions: Our data demonstrate that common variants with significant associations from GWAS studies can distinguish cancer cases versus controls for some cancers in an unselected biobank population. Given the small effects, future studies are needed to determine how best to incorporate PRS with other risk factors in the precision prediction of cancer risk. [Table: see text]

scholarly journals Estimating prevalence of human traits among populations from polygenic risk scores

2021 ◽  
Vol 15 (1) ◽  
Author(s):  
Britney E. Graham ◽  
Brian Plotkin ◽  
Louis Muglia ◽  
Jason H. Moore ◽  
Scott M. Williams
Keyword(s):  
Phenotypic Variation ◽  
Significant Proportion ◽  
Population Level ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Diverse Populations ◽  
Polygenic Risk ◽  
Risk Variants ◽  
Complex Architecture ◽  
Variance Explained

AbstractThe genetic basis of phenotypic variation across populations has not been well explained for most traits. Several factors may cause disparities, from variation in environments to divergent population genetic structure. We hypothesized that a population-level polygenic risk score (PRS) can explain phenotypic variation among geographic populations based solely on risk allele frequencies. We applied a population-specific PRS (psPRS) to 26 populations from the 1000 Genomes to four phenotypes: lactase persistence (LP), melanoma, multiple sclerosis (MS) and height. Our models assumed additive genetic architecture among the polymorphisms in the psPRSs, as is convention. Linear psPRSs explained a significant proportion of trait variance ranging from 0.32 for height in men to 0.88 for melanoma. The best models for LP and height were linear, while those for melanoma and MS were nonlinear. As not all variants in a PRS may confer similar, or even any, risk among diverse populations, we also filtered out SNPs to assess whether variance explained was improved using psPRSs with fewer SNPs. Variance explained usually improved with fewer SNPs in the psPRS and was as high as 0.99 for height in men using only 548 of the initial 4208 SNPs. That reducing SNPs improves psPRSs performance may indicate that missing heritability is partially due to complex architecture that does not mandate additivity, undiscovered variants or spurious associations in the databases. We demonstrated that PRS-based analyses can be used across diverse populations and phenotypes for population prediction and that these comparisons can identify the universal risk variants.

scholarly journals The Relationship Between Polygenic Risk Scores and Cognition in Schizophrenia

2019 ◽  
Author(s):  
Alexander L Richards ◽  
Antonio F Pardiñas ◽  
Aura Frizzati ◽  
Katherine E Tansey ◽  
Amy J Lynham ◽  
...  
Keyword(s):  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Related Factors ◽  
Polygenic Risk ◽  
Genome Wide ◽  
A Genome ◽  
Genetic Overlap ◽  
Individual Variant

Abstract Background Cognitive impairment is a clinically important feature of schizophrenia. Polygenic risk score (PRS) methods have demonstrated genetic overlap between schizophrenia, bipolar disorder (BD), major depressive disorder (MDD), educational attainment (EA), and IQ, but very few studies have examined associations between these PRS and cognitive phenotypes within schizophrenia cases. Methods We combined genetic and cognitive data in 3034 schizophrenia cases from 11 samples using the general intelligence factor g as the primary measure of cognition. We used linear regression to examine the association between cognition and PRS for EA, IQ, schizophrenia, BD, and MDD. The results were then meta-analyzed across all samples. A genome-wide association studies (GWAS) of cognition was conducted in schizophrenia cases. Results PRS for both population IQ (P = 4.39 × 10–28) and EA (P = 1.27 × 10–26) were positively correlated with cognition in those with schizophrenia. In contrast, there was no association between cognition in schizophrenia cases and PRS for schizophrenia (P = .39), BD (P = .51), or MDD (P = .49). No individual variant approached genome-wide significance in the GWAS. Conclusions Cognition in schizophrenia cases is more strongly associated with PRS that index cognitive traits in the general population than PRS for neuropsychiatric disorders. This suggests the mechanisms of cognitive variation within schizophrenia are at least partly independent from those that predispose to schizophrenia diagnosis itself. Our findings indicate that this cognitive variation arises at least in part due to genetic factors shared with cognitive performance in populations and is not solely due to illness or treatment-related factors, although our findings are consistent with important contributions from these factors.

scholarly journals Polygenic risk score of sporadic late-onset Alzheimer's disease reveals a shared architecture with the familial and early-onset forms

2017 ◽  
Vol 14 (2) ◽  
pp. 205-214 ◽  
Author(s):  
Carlos Cruchaga ◽  
Jorge L. Del-Aguila ◽  
Benjamin Saef ◽  
Kathleen Black ◽  
Maria Victoria Fernandez ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Score ◽  
Early Onset ◽  
Late Onset ◽  
Polygenic Risk Score ◽  
Polygenic Risk

scholarly journals A polygenic risk score for multiple myeloma risk prediction

2021 ◽  
Author(s):  
Federico Canzian ◽  
Chiara Piredda ◽  
Angelica Macauda ◽  
Daria Zawirska ◽  
Niels Frost Andersen ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Risk Score ◽  
Association Studies ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Epidemiologic Evidence ◽  
Risk Variants ◽  
Genome Wide ◽  
Weighted Score

AbstractThere is overwhelming epidemiologic evidence that the risk of multiple myeloma (MM) has a solid genetic background. Genome-wide association studies (GWAS) have identified 23 risk loci that contribute to the genetic susceptibility of MM, but have low individual penetrance. Combining the SNPs in a polygenic risk score (PRS) is a possible approach to improve their usefulness. Using 2361 MM cases and 1415 controls from the International Multiple Myeloma rESEarch (IMMEnSE) consortium, we computed a weighted and an unweighted PRS. We observed associations with MM risk with OR = 3.44, 95% CI 2.53–4.69, p = 3.55 × 10−15 for the highest vs. lowest quintile of the weighted score, and OR = 3.18, 95% CI 2.1 = 34–4.33, p = 1.62 × 10−13 for the highest vs. lowest quintile of the unweighted score. We found a convincing association of a PRS generated with 23 SNPs and risk of MM. Our work provides additional validation of previously discovered MM risk variants and of their combination into a PRS, which is a first step towards the use of genetics for risk stratification in the general population.

scholarly journals Impute.me: an open source, non-profit tool for using data from DTC genetic testing to calculate and interpret polygenic risk scores

2019 ◽  
Author(s):  
Lasse Folkersen ◽  
Oliver Pain ◽  
Andres Ingasson ◽  
Thomas Werge ◽  
Cathryn M. Lewis ◽  
...  
Keyword(s):  
Open Source ◽  
Public Perception ◽  
Disease Risk ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Complex Disorders ◽  
Risk Variants ◽  
Genome Wide ◽  
The Impact

AbstractTo date, interpretation of genomic information has focused on single variants conferring disease risk, but most disorders of major public concern have a polygenic architecture. Polygenic risk scores (PRS) give a single measure of disease liability by summarising disease risk across hundreds of thousands of genetic variants. They can be calculated in any genome-wide genotype data-source, using a prediction model based on genome-wide summary statistics from external studies.As genome-wide association studies increase in power, the predictive ability for disease risk will also increase. While PRS are unlikely ever to be fully diagnostic, they may give valuable medical information for risk stratification, prognosis, or treatment response prediction.Public engagement is therefore becoming important on the potential use and acceptability of PRS. However, the current public perception of genetics is that it provides ‘Yes/No’ answers about the presence/absence of a condition, or the potential for developing a condition, which in not the case for common, complex disorders with of polygenic architecture.Meanwhile, unregulated third-party applications are being developed to satisfy consumer demand for information on the impact of lower risk variants on common diseases that are highly polygenic. Often applications report results from single SNPs and disregard effect size, which is highly inappropriate for common, complex disorders where everybody carries risk variants.Tools are therefore needed to communicate our understanding of genetic predisposition as a continuous trait, where a genetic liability confers risk for disease. Impute.me is one such a tool, whose focus is on education and information on common, complex disorders with polygenetic architecture. Its research-focused open-source website allows users to upload consumer genetics data to obtain PRS, with results reported on a population-level normal distribution. Diseases can only be browsed by ICD10-chapter-location or alphabetically, thus prompting the user to consider genetic risk scores in a medical context of relevance to the individual.Here we present an overview of the implementation of the impute.me site, along with analysis of typical usage-patterns, which may advance public perception of genomic risk and precision medicine.

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