Polygenic score prediction captures nearly all common genetic risk for Alzheimer's disease

Escott‐Price, Valentina; Shoai, Maryam; Pither, Richard; Williams, Julie; Hardy, John

doi:10.1016/j.neurobiolaging.2016.07.018

Cited by 156 publications

(134 citation statements)

References 24 publications

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“…Remarkably, this actual AUC value is quite close to the upper limit AUCmax = 82% (95% C.I. = 78–85%) (68) that could be achieved given the genetic epidemiology of the disease, namely disease prevalence (2%) and SNP-heritability (24%) (69,70), indicating that the polygenic risk profiling captures the SNP-heritability very well and is quite suitable for AD genetic risk prediction.…”

Section: The Role Of Genetics In Precision Medicine For Ad – From Gensupporting

confidence: 65%

Precision Medicine - The Golden Gate for Detection, Treatment and Prevention of Alzheimer’s Disease

Hampel¹,

O’Bryant

Castrillo

et al. 2016

J Prev Alz Dis

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During this decade, breakthrough conceptual shifts have commenced to emerge in the field of Alzheimer’s disease (AD) recognizing risk factors and the non-linear dynamic continuum of complex pathophysiologies amongst a wide dimensional spectrum of multi-factorial brain proteinopathies/neurodegenerative diseases. As is the case in most fields of medicine, substantial advancements in detecting, treating and preventing AD will likely evolve from the generation and implementation of a systematic precision medicine strategy. This approach will likely be based on the success found from more advanced research fields, such as oncology. Precision medicine will require integration and transfertilization across fragmented specialities of medicine and direct reintegration of Neuroscience, Neurology and Psychiatry into a continuum of medical sciences away from the silo approach. Precision medicine is biomarker-guided medicine on systems-levels that takes into account methodological advancements and discoveries of the comprehensive pathophysiological profiles of complex multi-factorial neurodegenerative diseases, such as late-onset sporadic AD. This will allow identifying and characterizing the disease processes at the asymptomatic preclinical stage, where pathophysiological and topographical abnormalities precede overt clinical symptoms by many years to decades. In this respect, the uncharted territory of the AD preclinical stage has become a major research challenge as the field postulates that early biomarker guided customized interventions may offer the best chance of therapeutic success. Clarification and practical operationalization is needed for comprehensive dissection and classification of interacting and converging disease mechanisms, description of genomic and epigenetic drivers, natural history trajectories through space and time, surrogate biomarkers and indicators of risk and progression, as well as considerations about the regulatory, ethical, political and societal consequences of early detection at asymptomatic stages. In this scenario, the integrated roles of genome sequencing, investigations of comprehensive fluid-based biomarkers and multimodal neuroimaging will be of key importance for the identification of distinct molecular mechanisms and signaling pathways in subsets of asymptomatic people at greatest risk for progression to clinical milestones due to those specific pathways. The precision medicine strategy facilitates a paradigm shift in Neuroscience and AD research and development away from the classical “one-size-fits-all” approach in drug discovery towards biomarker guided “molecularly” tailored therapy for truly effective treatment and prevention options. After the long and winding decade of failed therapy trials progress towards the holistic systems-based strategy of precision medicine may finally turn into the new age of scientific and medical success curbing the global AD epidemic.

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Section: The Role Of Genetics In Precision Medicine For Ad – From Gensupporting

confidence: 65%

Precision Medicine - The Golden Gate for Detection, Treatment and Prevention of Alzheimer’s Disease

Hampel¹,

O’Bryant

Castrillo

et al. 2016

J Prev Alz Dis

View full text Add to dashboard Cite

show abstract

“…This demonstrates the increased power that can be realized using pathologically confirmed tissue in comparison to clinically defined samples. In a more recent study, Escott-Price et al (2017a) used a modified approach to calculate the maximum possible predictive power (AUC max ) thereby improving the AUC produced previously from a value of 78.2% to 82%. More recently, Escott-Price et al (2017b) have performed PRS analysis on pathologically confirmed samples and found improved scores compared with the previous study on clinically diagnosed cases (Escott-Price et al (2015)).…”

Section: Discussionmentioning

confidence: 99%

Polygenic risk score in postmortem diagnosed sporadic early-onset Alzheimer's disease

Chaudhury

Patel

Barber

et al. 2018

Neurobiology of Aging

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Sporadic early-onset Alzheimer’s disease (sEOAD) exhibits the symptoms of late-onset Alzheimer’s disease but lacks the familial aspect of the early-onset familial form. The genetics of Alzheimer’s disease (AD) identifies APOE ε4 to be the greatest risk factor; however, it is a complex disease involving both environmental risk factors and multiple genetic loci. Polygenic risk scores (PRSs) accumulate the total risk of a phenotype in an individual based on variants present in their genome. We determined whether sEOAD cases had a higher PRS compared to controls. A cohort of sEOAD cases was genotyped on the NeuroX array, and PRSs were generated using PRSice. The target data set consisted of 408 sEOAD cases and 436 controls. The base data set was collated by the International Genomics of Alzheimer’s Project consortium, with association data from 17,008 late-onset Alzheimer’s disease cases and 37,154 controls, which can be used for identifying sEOAD cases due to having shared phenotype. PRSs were generated using all common single nucleotide polymorphisms between the base and target data set, PRS were also generated using only single nucleotide polymorphisms within a 500 kb region surrounding the APOE gene. Sex and number of APOE ε2 or ε4 alleles were used as variables for logistic regression and combined with PRS. The results show that PRS is higher on average in sEOAD cases than controls, although there is still overlap among the whole cohort. Predictive ability of identifying cases and controls using PRSice was calculated with 72.9% accuracy, greater than the APOE locus alone (65.2%). Predictive ability was further improved with logistic regression, identifying cases and controls with 75.5% accuracy.

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“…gene-based assays, implementing polygenic risk scoring for assessing AD onset risk, are currently in late stage clinical development. In particular, a 90% maximum prediction accuracy via polygenic risk scoring can be accomplished by predictors of genetic risk based on genomic profiles [76]. …”

Section: The Precision Neurology Paradigm In Alzheimer’s Diseasementioning

confidence: 99%

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

Hampel

Toschi

Babiloni

et al. 2018

JAD

131

113

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The Precision Neurology development process implements systems theory with system biology and neurophysiology in a parallel, bidirectional research path: a combined hypothesis-driven investigation of systems dysfunction within distinct molecular, cellular and large-scale neural network systems in both animal models as well as through tests for the usefulness of these candidate dynamic systems biomarkers in different diseases and subgroups at different stages of pathophysiological progression. This translational research path is paralleled by an “omics”-based, hypothesis-free, exploratory research pathway, which will collect multimodal data from progressing asymptomatic, preclinical and clinical neurodegenerative disease (ND) populations, within the wide continuous biological and clinical spectrum of ND, applying high-throughput and high-content technologies combined with powerful computational and statistical modeling tools, aimed at identifying novel dysfunctional systems and predictive marker signatures associated with ND. The goals are to identify common biological denominators or differentiating classifiers across the continuum of ND during detectable stages of pathophysiological progression, characterize systems-based intermediate endophenotypes, validate multi-modal novel diagnostic systems biomarkers, and advance clinical intervention trial designs by utilizing systems-based intermediate endophenotypes and candidate surrogate markers. Achieving these goals is key to the ultimate development of early and effective individualized treatment of ND, such as Alzheimer’s disease (AD). The Alzheimer Precision Medicine Initiative (APMI) and cohort program (APMI-CP), as well as the Paris based core of the Sorbonne University Clinical Research Group “Alzheimer Precision Medicine” (GRC-APM) were recently launched to facilitate the passageway from conventional clinical diagnostic and drug development towards breakthrough innovation based on the investigation of the comprehensive biological nature of aging individuals. The APMI movement is gaining momentum to systematically apply both systems neurophysiology and systems biology in exploratory translational neuroscience research on ND.

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Polygenic score prediction captures nearly all common genetic risk for Alzheimer's disease

Cited by 156 publications

References 24 publications

Precision Medicine - The Golden Gate for Detection, Treatment and Prevention of Alzheimer’s Disease

Precision Medicine - The Golden Gate for Detection, Treatment and Prevention of Alzheimer’s Disease

Polygenic risk score in postmortem diagnosed sporadic early-onset Alzheimer's disease

Revolution of Alzheimer Precision Neurology. Passageway of Systems Biology and Neurophysiology

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