. Polygenic hazard score, amyloid deposition and Alzheimer's neurodegeneration. Brain. 2019 Feb 1;142(2):460-470. PubMed.

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  1. There is no consensus among the scientific community on how PHS can be used for clinical management, much less for DTC tests. One can easily find experts who contest the accuracy and utility of PHS, particularly regarding their utility for personalized screening. There is no regulation or public education framework (that I know of) specific for PHS, so I think it is still very early to make such tests available to consumers, even if all limitations and disclosures are made available on websites and reports.

    View all comments by Rita Guerreiro
  2. The PHS is associated with amyloid PET and various markers of neurodegeneration and may be useful in a research setting to track disease progression.

    The diagnostic and prognostic accuracy of the PHS are not yet known. For these and other reasons, it is premature to share PHS scores with consumers. For instance, the SNP results from various direct-to-consumer labs may not be accurate, leading to miscalculation of the PHS. Even if the calculation of the PHS is accurate, it is just a risk factor and not an indication that someone will (or will not) develop the disease.

    Just as people without the e4 variant of APOE still develop dementia due to Alzheimer’s, those with a low PHS may still develop the disease. As with other genetic testing results, it is important to work with a genetic counselor or other healthcare professional to discuss family, insurance, and emotional considerations of learning results.

    View all comments by Jessica Langbaum
  3. Tan and colleagues report an association of polygenic hazard score (PHS) with numerous factors, including Aβ and tau accumulation, neurodegeneration, cognitive decline, etc. Prior to PHS analyses, Desikan et al. selected common genetic variants (SNPs) based on their association with AD at p-value≤10-5 in the publically available IGAP dataset (Lambert et al., 2013). They only use 31 SNPs, which mostly represent genome-wide AD associated loci. The effect sizes for age-specific, or “hazard” risk, of these SNPs are very similar to the general AD risk effect sizes. We have recently demonstrated that the PHS constructed as suggested by Desikan et al. is a shortened version of the polygenic risk score (PRS) (Leonenko et al., 2019) and, similar to PRS, is capable of predicting AD and related phenotypes over and above APOE (as shown in Escott-Price et al., 2015Escott-Price et al., 2017). 

    However, the prediction accuracy of the PHS was not reported in Desikan et al. and therefore the predictive utility of PHS is not clear. Furthermore, although APOE and GWAS SNPs show strong association with late-onset AD, the genetic heritability explained by these loci is not high (h2=5.1 percent [95 percent CI: 3.9 percent to 6.3 percent]) (Escott-Price et al., 2017) as compared with genome-wide estimates (h2=24 percent to 53 percent) (Ridge et al., 2016; Ridge et al., 2013; Lee et al., 2013). The maximum prediction accuracy which can be achieved based upon APOE and GWAS significant loci is limited (maximum prediction accuracy AUC=66 percent [95 percent CI: 64 percent to 67 percent]), and is insufficient for clinical applications or trials (Lewis and Vassos, 2017). 

    PRS as defined in Escott-Price et al., 2015 shows prediction accuracy of AUC= 75 percent to 84 percent in clinical and pathology confirmed samples, respectively (Escott-Price et al., 2015Escott-Price et al., 2017). These AUC estimates are very close to the maximum prediction accuracy that can be achieved based upon SNP-based heritability captured by the whole genome (Escott-Price et al., 2017), and may potentially be used for AD risk prediction with more confidence.

    In conclusion, a modified version of this PHS may have a limited predictive utility and low accuracy, and may be misleading for clinical trials and/or the general public.

    References:

    . Genetic assessment of age-associated Alzheimer disease risk: Development and validation of a polygenic hazard score. PLoS Med. 2017 Mar;14(3):e1002258. Epub 2017 Mar 21 PubMed.

    . Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet. 2013 Dec;45(12):1452-8. Epub 2013 Oct 27 PubMed.

    . Polygenic risk and hazard scores for Alzheimer's disease prediction. Ann Clin Transl Neurol. 2019 Mar;6(3):456-465. Epub 2019 Feb 18 PubMed.

    . Common polygenic variation enhances risk prediction for Alzheimer's disease. Brain. 2015 Dec;138(Pt 12):3673-84. Epub 2015 Oct 21 PubMed.

    . Polygenic risk score analysis of pathologically confirmed Alzheimer disease. Ann Neurol. 2017 Aug;82(2):311-314. Epub 2017 Aug 9 PubMed.

    . Polygenic score prediction captures nearly all common genetic risk for Alzheimer's disease. Neurobiol Aging. 2017 Jan;49:214.e7-214.e11. Epub 2016 Aug 5 PubMed.

    . Assessment of the genetic variance of late-onset Alzheimer's disease. Neurobiol Aging. 2016 May;41:200.e13-20. Epub 2016 Mar 3 PubMed.

    . Alzheimer's disease: analyzing the missing heritability. PLoS One. 2013;8(11):e79771. Epub 2013 Nov 7 PubMed.

    . Estimation and partitioning of polygenic variation captured by common SNPs for Alzheimer's disease, multiple sclerosis and endometriosis. Hum Mol Genet. 2013 Feb 15;22(4):832-41. PubMed.

    . Prospects for using risk scores in polygenic medicine. Genome Med. 2017 Nov 13;9(1):96. PubMed.

    View all comments by Valentina Escott-Price

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