scholarly journals Assessing the genetic correlations between early growth parameters and bone mineral density: A polygenic risk score analysis

Bone ◽  
2018 ◽  
Vol 116 ◽  
pp. 301-306 ◽  
Author(s):  
Xiao Liang ◽  
CuiYan Wu ◽  
Hongmou Zhao ◽  
Li Liu ◽  
Yanan Du ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Bone Mineral ◽  
Risk Score ◽  
Growth Parameters ◽  
Genetic Correlations ◽  
Early Growth ◽  
Polygenic Risk Score ◽  
Mineral Density ◽  
Polygenic Risk ◽  
Score Analysis

scholarly journals Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study

2017 ◽  
Vol 48 (9) ◽  
pp. 1532-1539 ◽  
Author(s):  
E. Neilson ◽  
C. Bois ◽  
T.-K. Clarke ◽  
L. Hall ◽  
E. C. Johnstone ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Familial Risk ◽  
Positive Association ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Score Analysis ◽  
Increased Risk ◽  
Heritable Disorder ◽  
Diagnostic Symptoms

AbstractBackgroundSchizophrenia is a highly heritable disorder, linked to several structural abnormalities of the brain. More specifically, previous findings have suggested that increased gyrification in frontal and temporal regions are implicated in the pathogenesis of schizophrenia.MethodsThe current study included participants at high familial risk of schizophrenia who remained well (n= 31), who developed sub-diagnostic symptoms (n= 28) and who developed schizophrenia (n= 9) as well as healthy controls (HC) (n= 16). We first tested whether individuals at high familial risk of schizophrenia carried an increased burden of trait-associated alleles using polygenic risk score analysis. We then assessed the extent to which polygenic risk was associated with gyral folding in the frontal and temporal lobes.ResultsWe found that individuals at high familial risk of schizophrenia who developed schizophrenia carried a significantly greater burden of risk-conferring variants for the disorder compared to those at high risk (HR) who developed sub-diagnostic symptoms or remained well and HC. Furthermore, within the HR cohort, there was a significant and positive association between schizophrenia polygenic risk score and bilateral frontal gyrification.ConclusionsThese results suggest that polygenic risk for schizophrenia impacts upon early neurodevelopment to confer greater gyral folding in adulthood and an increased risk of developing the disorder.

scholarly journals POLYGENIC RISK SCORE ANALYSIS OF ALZHEIMER’S DISEASE IN CASES WITHOUT APOE4 OR APOE2 ALLELES

2018 ◽  
pp. 1-4
Author(s):  
V. Escott-Price ◽  
A. Myers ◽  
M. Huentelman ◽  
M. Shoai ◽  
J. Hardy
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Score ◽  
Clinical Trial Design ◽  
Polygenic Risk Score ◽  
Carrier Status ◽  
Predictive Utility ◽  
Polygenic Risk ◽  
Score Analysis ◽  
E4 Allele

The We and others have previously shown that polygenic risk score analysis (PRS) has considerable predictive utility for identifying those at high risk of developing Alzheimer’s disease (AD) with an area under the curve (AUC) of >0.8. However, by far the greatest determinant of this risk is the apolipoprotein E locus with the E4 allele alone giving an AUC of ~0.68 and the inclusion of the protective E2 allele increasing this to ~0.69 in a clinical cohort. An important question is to determine how good PRS is at predicting risk in those who do not carry the E4 allele (E3 homozygotes, E3E2 and E2E2) and in those who carry neither the E4 or E2 allele (i.e. E3 homozygotes). Previous studies have shown that PRS remains a significant predictor of AD risk in clinical cohorts after controlling for APOE ε4 carrier status. In this study we assess the accuracy of PRS prediction in a cohort of pathologically confirmed AD cases and controls. The exclusion of APOE4 carriers has surprisingly little effect on the PRS prediction accuracy (AUC ~0.83 [95% CI: 0.80-0.86]), and the accuracy remained higher than that in clinical cohorts with APOE included as a predictor. From a practical perspective this suggests that PRS analysis will have predictive utility even in E4 negative individuals and may be useful in clinical trial design.

scholarly journals A polygenic risk score analysis of psychosis endophenotypes across brain functional, structural, and cognitive domains

2017 ◽  
Vol 177 (1) ◽  
pp. 21-34 ◽  
Author(s):  
Siri Ranlund ◽  
Stella Calafato ◽  
Johan H. Thygesen ◽  
Kuang Lin ◽  
Wiepke Cahn ◽  
...  
Keyword(s):  
Risk Score ◽  
Polygenic Risk Score ◽  
Cognitive Domains ◽  
Polygenic Risk ◽  
Score Analysis

scholarly journals Gut microbiota is associated with bone mineral density

2021 ◽  
Vol 10 (11) ◽  
pp. 734-741
Author(s):  
Bolun Cheng ◽  
Yan Wen ◽  
Xuena Yang ◽  
Shiqiang Cheng ◽  
Li Liu ◽  
...  
Keyword(s):  
Bone Mineral Density ◽  
Gut Microbiota ◽  
Bone Mineral ◽  
Interaction Analysis ◽  
Population Based ◽  
Polygenic Risk Score ◽  
Regulation Mechanism ◽  
Mineral Density ◽  
Phospholipase D1 ◽  
The Individual

Aims Despite the interest in the association of gut microbiota with bone health, limited population-based studies of gut microbiota and bone mineral density (BMD) have been made. Our aim is to explore the possible association between gut microbiota and BMD. Methods A total of 3,321 independent loci of gut microbiota were used to calculate the individual polygenic risk score (PRS) for 114 gut microbiota-related traits. The individual genotype data were obtained from UK Biobank cohort. Linear regressions were then conducted to evaluate the possible association of gut microbiota with L1-L4 BMD (n = 4,070), total BMD (n = 4,056), and femur total BMD (n = 4,054), respectively. PLINK 2.0 was used to detect the single-nucleotide polymorphism (SNP) × gut microbiota interaction effect on the risks of L1-L4 BMD, total BMD, and femur total BMD, respectively. Results We detected five, three, and seven candidate gut microbiota-related traits for L1-L4 BMD, total BMD, and femur BMD, respectively, such as genus Dialister (p = 0.004) for L1-L4 BMD, and genus Eisenbergiella (p = 0.046) for total BMD. We also detected two common gut microbiota-related traits shared by L1-L4 BMD, total BMD, and femur total BMD, including genus Escherichia Shigella and genus Lactococcus. Interaction analysis of BMD detected several genes that interacted with gut microbiota, such as phospholipase D1 ( PLD1) and endomucin ( EMCN) interacting with genus Dialister in total BMD, and COL12A1 and Discs Large MAGUK Scaffold Protein 2 ( DLG2) interacting with genus Lactococcus in femur BMD. Conclusion Our results suggest associations between gut microbiota and BMD, which will be helpful to further explore the regulation mechanism and intervention gut microbiota of BMD. Cite this article: Bone Joint Res 2021;10(11):734–741.

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