Biology subjects

Reynolds, C. A.

Publications and source records attributed to Reynolds, C. A..

24 records · Page 2Linked to original sources

bioRxiv2019

Semantic Fluency Predicts Six-Year Progression to Mild Cognitive Impairment in Middle-Aged Men

ObjectiveTest the hypothesis that individual differences in episodic memory and verbal fluency in cognitively normal middle-aged adults will predict progression to amnestic MCI after 6 years.\n\nMethodThe analysis sample included 842 male twins who were cognitively normal at baseline (M=56 years), completed measures of episodic memory and verbal fluency at baseline and again 6 years later (M=62 years).\n\nResultsPoor episodic memory predicted progression to both amnestic MCI (OR=4.42, 95% CI [2.44, 10.60]) and non-amnestic MCI (OR=1.92, 95% CI [1.32, 3.44]). Poor semantic verbal fluency also independently predicted progression to amnestic MCI (OR=1.86, 95% CI [1.12, 3.52]). In the full sample, a semantic-specific fluency latent variable at wave 1 (which controls for letter fluency) predicted change in episodic memory at wave 2 ({beta}=.13), but not vice-versa ({beta}=.04). Associations between episodic memory and verbal fluency factors were primarily explained by genetic, rather than environmental, correlations.\n\nConclusionsAmong individuals who were cognitively normal at wave 1, episodic memory moderately-to-strongly predicted progression to MCI at average age 62, emphasizing the fact that there is still meaningful variability even among cognitively normal individuals. Episodic memory, which is typically a primary focus for AD risk, declined earlier and more quickly than fluency. However, semantic fluency at average age 56 predicted 6-year change in memory as well as progression to amnestic MCI even after accounting for baseline memory performance. These findings emphasize the utility of memory and fluency measures in early identification of AD risk.

genetics↗

bioRxiv2019

Comparing within- and between-family polygenic score prediction

Polygenic scores are a popular tool for prediction of complex traits. However, prediction estimates in samples of unrelated participants can include effects of population stratification, assortative mating and environmentally mediated parental genetic effects, a form of genotype-environment correlation (rGE). Comparing genome-wide polygenic score (GPS) predictions in unrelated individuals with predictions between siblings in a within-family design is a powerful approach to identify these different sources of prediction. Here, we compared within- to between-family GPS predictions of eight life outcomes (anthropometric, cognitive, personality and health) for eight corresponding GPSs. The outcomes were assessed in up to 2,366 dizygotic (DZ) twin pairs from the Twins Early Development Study from age 12 to age 21. To account for family clustering, we used mixed-effects modelling, simultaneously estimating within- and between-family effects for target- and cross-trait GPS prediction of the outcomes. There were three main findings: (1) DZ twin GPS differences predicted DZ differences in height, BMI, intelligence, educational achievement and ADHD symptoms; (2) target and cross-trait analyses indicated that GPS prediction estimates for cognitive traits (intelligence and educational achievement) were on average 60% greater between families than within families, but this was not the case for non-cognitive traits; and (3) this within- and between-family difference for cognitive traits disappeared after controlling for family socio-economic status (SES), suggesting that SES is a source of between-family prediction through rGE mechanisms. These results provide novel insights into the patterns by which rGE contributes to GPS prediction, while ruling out confounding due to population stratification and assortative mating.

genomics↗

bioRxiv2019

Multiple memory tests in midlife improve prediction of mild cognitive impairment

INTRODUCTIONPredicting risk for Alzheimers disease when most people are likely still biomarker negative would aid earlier identification. We hypothesized that combining multiple memory tests and scores in middle-aged adults would provide useful, and non-invasive, prediction of 6-year progression to MCI.\n\nMETHODSWe examined 849 men who were cognitively normal at baseline (mean age=55.69{+/-}2.45).\n\nRESULTSCalifornia Verbal Learning Test learning trials was the best individual predictor of amnestic MCI (OR=4.75). A latent factor incorporating 7 measures across 3 memory tests provided much stronger prediction (OR=9.88). This compared favorably with biomarker-based prediction in a study of much older adults.\n\nDISCUSSIONNeuropsychological tests are sensitive and early indicators of Alzheimers disease risk at an age when few individuals are likely to have yet become biomarker positive. Single best measures may appear time- and cost-effective, but 30 additional minutes of testing, and use of multiple scores within tests, provides substantially improved prediction

pathology↗

bioRxiv2018

Genetic risk for coronary heart disease alters the influence of Alzheimer’s genetic risk on mild cognitive impairment

BACKGROUNDAlzheimers disease (AD) is under considerable genetic influence. However, known susceptibility loci only explain a modest proportion of variance in disease outcomes. This small proportion could occur if the etiology of AD is heterogeneous. We previously found that an AD polygenic risk score (PRS) was significantly associated with mild cognitive impairment (MCI), an early stage of AD. Poor cardiovascular health is also associated with increased risk for AD and has been found to interact with AD pathology. Conditions such as coronary artery disease (CAD) are also heritable, and may contribute to heterogeneity if there are interactions of genetic risk for these conditions as there is phenotypically. However, case-control designs based on prevalent cases of a disease with relatively high case-fatality rate such as CAD may be biased toward individuals who have long post-event survival times and may therefore also identify loci with protective effects.\n\nMETHODSWe compared interactions between an AD-PRS and two CAD-PRSs, one based on a GWAS of incident cases and one on prevalent cases, on MCI status in 1,209 individuals.\n\nRESULTSAs expected, the incidence-based CAD-PRS interacts with the AD-PRS to further increase MCI risk. Conversely, higher prevalence-based CAD-PRSs reduced the effect of AD genetic risk on MCI status.\n\nCONCLUSIONSThese results demonstrate: i) the utility of including multiple PRSs and their interaction effects; ii) how genetic risk for one disease may modify the impact of genetic risk for another; and iii) the importance of considering ascertainment procedures of GWAS being used for genetic risk prediction.

genomics↗

bioRxiv2017

GWAS meta-analysis (N=279,930) identifies new genes and functional links to intelligence

Intelligence is highly heritable1 and a major determinant of human health and well-being2. Recent genome-wide meta-analyses have identified 24 genomic loci linked to intelligence3-7, but much about its genetic underpinnings remains to be discovered. Here, we present the largest genetic association study of intelligence to date (N=279,930), identifying 206 genomic loci (191 novel) and implicating 1,041 genes (963 novel) via positional mapping, expression quantitative trait locus (eQTL) mapping, chromatin interaction mapping, and gene-based association analysis. We find enrichment of genetic effects in conserved and coding regions and identify 89 nonsynonymous exonic variants. Associated genes are strongly expressed in the brain and specifically in striatal medium spiny neurons and cortical and hippocampal pyramidal neurons. Gene-set analyses implicate pathways related to neurogenesis, neuron differentiation and synaptic structure. We confirm previous strong genetic correlations with several neuropsychiatric disorders, and Mendelian Randomization results suggest protective effects of intelligence for Alzheimers dementia and ADHD, and bidirectional causation with strong pleiotropy for schizophrenia. These results are a major step forward in understanding the neurobiology of intelligence as well as genetically associated neuropsychiatric traits.

genetics↗

bioRxiv2017

Ninety-nine independent genetic loci influencing general cognitive function include genes associated with brain health and structure (N = 280,360)

General cognitive function is a prominent human trait associated with many important life outcomes1,2, including longevity3. The substantial heritability of general cognitive function is known to be polygenic, but it has had little explication in terms of the contributing genetic variants4,5,6. Here, we combined cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N=280,360; age range = 16 to 102). We found 9,714 genome-wide significant SNPs (P<5 x 10-8) in 99 independent loci. Most showed clear evidence of functional importance. Among many novel genes associated with general cognitive function were SGCZ, ATXN1, MAPT, AUTS2, and P2RY6. Within the novel genetic loci were variants associated with neurodegenerative disorders, neurodevelopmental disorders, physical and psychiatric illnesses, brain structure, and BMI. Gene-based analyses found 536 genes significantly associated with general cognitive function; many were highly expressed in the brain, and associated with neurogenesis and dendrite gene sets. Genetic association results predicted up to 4% of general cognitive function variance in independent samples. There was significant genetic overlap between general cognitive function and information processing speed, as well as many health variables including longevity.

genetics↗