Polygenic Risk Scoring is an Effective Approach to Predict Those Individuals Most Likely to Decline Cognitively Due to Alzheimer’s Disease

BACKGROUND: There is a clear need for simple and effective tests to identify individuals who are most likely to develop Alzheimer’s Disease (AD) both for the purposes of clinical trial recruitment but also for improved management of patients who may be experiencing early pre-clinical symptoms or who have clinical concerns. OBJECTIVES: To predict individuals at greatest risk of progression of cognitive impairment due to Alzheimer’s Disease in individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) using a polygenic risk scoring algorithm. To compare the performance of a PRS algorithm in predicting cognitive decline against that of using the pTau/Aß1-42 ratio CSF biomarker profile. DESIGN: A longitudinal analysis of data from the Alzheimer’s Disease Neuroimaging Initiative study conducted across over 50 sites in the US and Canada. SETTING: Multi-center genetics study. PARTICPANTS: 515 subjects who upon entry to the study were diagnosed as cognitively normal or with mild cognitive impairment. MEASUREMENTS: Use of genotyping and/or whole genome sequencing data to calculate polygenic risk scores and assess ability to predict subsequent cognitive decline as measured by CDR-SB and ADAS-Cog13 over 4 years RESULTS: The overall performance for predicting those individuals who would decline by at least 15 ADAS-Cog13 points from a baseline mild cognitive impairment in 4 years was 72.8% (CI:67.9-77.7) AUC increasing to 79.1% (CI: 75.6-82.6) when also including cognitively normal participants. Assessing mild cognitive impaired subjects only and using a threshold of greater than 0.6, the high genetic risk participant group declined, on average, by 1.4 points (CDR-SB) more than the low risk group over 4 years. The performance of the PRS algorithm tested was similar to that of the pTau/Aß1-42 ratio CSF biomarker profile in predicting cognitive decline. CONCLUSION: Calculating polygenic risk scores offers a simple and effective way, using DNA extracted from a simple mouth swab, to select mild cognitively impaired patients who are most likely to decline cognitively over the next four years

Polygenic Risk Scoring is an Effective Approach to Predict Those Individuals Most Likely to Decline Cognitively Due to Alzheimer’s Disease

This is the final version. Available on open access from Springer Nature via the DOI in this recordBACKGROUND: There is a clear need for simple and effective tests to identify individuals who are most likely to develop Alzheimer’s Disease (AD) both for the purposes of clinical trial recruitment but also for improved management of patients who may be experiencing early pre-clinical symptoms or who have clinical concerns. OBJECTIVES: To predict individuals at greatest risk of progression of cognitive impairment due to Alzheimer’s Disease in individuals from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) using a polygenic risk scoring algorithm. To compare the performance of a PRS algorithm in predicting cognitive decline against that of using the pTau/Aẞ1-42 ratio CSF biomarker profile. DESIGN: A longitudinal analysis of data from the Alzheimer’s Disease Neuroimaging Initiative study conducted across over 50 sites in the US and Canada SETTING: Multi-center genetics study PARTICPANTS: 515 subjects who upon entry to the study were diagnosed as cognitively normal or with mild cognitive impairment MEASUREMENTS: Use of genotyping and/or whole genome sequencing data to calculate polygenic risk scores and assess ability to predict subsequent cognitive decline as measured by CDR-SB and ADAS-Cog13 over 4 years RESULTS: The overall performance for predicting those individuals who would decline by at least 15 ADAS-Cog13 points from a baseline mild cognitive impairment in 4 years was 72.8% (CI:67.9-77.7) AUC increasing to 79.1% (CI: 75.6-82.6) when also including cognitively normal participants. Assessing mild cognitive impaired subjects only and using a threshold of greater than 0.6, the high genetic risk participant group declined, on average, by 1.4 points (CDR-SB) more than the low risk group over 4 years. The performance of the PRS algorithm tested was similar to that of the pTau/Aẞ1-42 ratio CSF biomarker profile in predicting cognitive decline. CONCLUSION: Calculating polygenic risk scores offers a simple and effective way, using DNA extracted from a simple mouth swab, to select mild cognitively impaired patients who are most likely to decline cognitively over the next four yearsNational Institutes of Health (NIH)Department of DefenseInnovate U

A global perspective on marine photosynthetic picoeukaryote community structure

A central goal in ecology is to understand the factors affecting the temporal dynamics and spatial distribution of microorganisms and the underlying processes causing differences in community structure and composition. However, little is known in this respect for photosynthetic picoeukaryotes (PPEs), algae that are now recognised as major players in marine CO2 fixation. Here, we analysed dot blot hybridisation and cloning–sequencing data, using the plastid-encoded 16S rRNA gene, from seven research cruises that encompassed all four ocean biomes. We provide insights into global abundance, α- and β-diversity distribution and the environmental factors shaping PPE community structure and composition. At the class level, the most commonly encountered PPEs were Prymnesiophyceae and Chrysophyceae. These taxa displayed complementary distribution patterns, with peak abundances of Prymnesiophyceae and Chrysophyceae in waters of high (25:1) or low (12:1) nitrogen:phosphorus (N:P) ratio, respectively. Significant differences in phylogenetic composition of PPEs were demonstrated for higher taxonomic levels between ocean basins, using Unifrac analyses of clone library sequence data. Differences in composition were generally greater between basins (interbasins) than within a basin (intrabasin). These differences were primarily linked to taxonomic variation in the composition of Prymnesiophyceae and Prasinophyceae whereas Chrysophyceae were phylogenetically similar in all libraries. These data provide better knowledge of PPE community structure across the world ocean and are crucial in assessing their evolution and contribution to CO2 fixation, especially in the context of global climate change