Biology subjects

Fan, C. C.

Publications and source records attributed to Fan, C. C..

7 recordsLinked to original sources

bioRxiv2018

Lipid associated polygenic enrichment in Alzheimer’s disease

Cardiovascular (CV) and lifestyle associated risk factors (RFs) are increasingly recognized as important for Alzheimers disease (AD) pathogenesis. Beyond the [isin]4 allele of apolipoprotein E (APOE), comparatively little is known about whether CV associated genes also increase risk for AD (genetic pleiotropy). Using large genome-wide association studies (GWASs) (total n > 500,000 cases and controls) and validated tools to quantify genetic pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with AD and one or more CV RFs, namely body mass index (BMI), type 2 diabetes (T2D), coronary artery disease (CAD), waist hip ratio (WHR), total cholesterol (TC), low-density (LDL) and high-density lipoprotein (HDL). In fold enrichment plots, we observed robust genetic enrichment in AD as a function of plasma lipids (TC, LDL, and HDL); we found minimal AD genetic enrichment conditional on BMI, T2D, CAD, and WHR. Beyond APOE, at conjunction FDR < 0.05 we identified 57 SNPs on 19 different chromosomes that were jointly associated with AD and CV outcomes including APOA4, ABCA1, ABCG5, LIPG, and MTCH2/SPI1. We found that common genetic variants influencing AD are associated with multiple CV RFs, at times with a different directionality of effect. Expression of these AD/CV pleiotropic genes was enriched for lipid metabolism processes, over-represented within astrocytes and vascular structures, highly co-expressed, and differentially altered within AD brains. Beyond APOE, we show that the polygenic component of AD is enriched for lipid associated RFs. Rather than a single causal link between genetic loci, RF and the outcome, we found that common genetic variants influencing AD are associated with multiple CV RFs. Our collective findings suggest that a network of genes involved in lipid biology also influence Alzheimers risk.

genetics↗

bioRxiv2018

Spatial gene-by-environment mapping for schizophrenia reveals locale of upbringing effects beyond urban-rural differences

Identification of mechanisms underlying the incidence of psychiatric disorders has been hampered by the difficulty in discovering highly-predictive environmental risk factors. For example, prior efforts have failed to establish environmental effects predicting geospatial clustering of schizophrenia incidence beyond urban-rural differences. Here, we employ a novel statistical framework for decomposing the geospatial risk for schizophrenia based on locale of upbringing (place of residence, ages 0-7 years) and its synergistic effects with genetic liabilities (polygenic risk for schizophrenia). We use this statistical framework to analyze unprecedented geolocation and genotyping data in a case-cohort study of n=24,028 subjects, drawn from the 1.47 million Danish persons born between 1981 and 2005. Using this framework we estimate the effects of upbringing locale (E) and gene-by-locale interactions (GxE). After controlling for potential confounding variables, upbringing at high-risk locales increases the risk for schizophrenia on average by 122%, while GxE modulates genetic risk for schizophrenia on average by 78%. Within the boundaries of Copenhagen (the largest and most densely populated city of Denmark) specific locales vary substantially in their E and GxE effects, with hazard ratios ranging from 0.26 to 9.26 for E and from 0.20 to 5.95 for GxE. This study provides insight into the degree of geospatial clustering of schizophrenia risk, and our novel analytic procedure provides a framework for decomposing variation in geospatial risk into G, E, and GxE components.

epidemiology↗

bioRxiv2017

Bivariate Gaussian Mixture Model of GWAS (BGMG)quantifies polygenic overlap between complex traitsbeyond genetic correlation

Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. While current cross-trait analytical methods focus on genetic correlation between traits, we developed a novel statistical tool (MiXeR), which quantifies polygenic overlap independent of genetic correlation, using summary statistics from GWAS. MiXeR results can be presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that more than 9K variants causally influence schizophrenia, 7K influence bipolar disorder, and out of those variants 6.9K are shared between these two disorders, which have high genetic correlation. Further, MiXeR uncovers extensive polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, these traits share more than 9K causal variants, while 3K additional variants only influence educational attainment. By considering the polygenicity, heritability and discoverability of complex phenotypes, MiXeR provides a more complete quantification of shared genetic architecture than offered by other available tools.

genetics↗

bioRxiv2017

Polygenic hazard score: an enrichment marker for Alzheimer’s associated amyloid and tau deposition

BackgroundThere is an urgent need for the early identification of nondemented individuals at the highest risk of progressing to Alzheimers disease (AD) dementia for early therapeutic interventions. Our goal was to evaluate whether a recently validated polygenic hazard score (PHS) can be integrated with known in vivo CSF or PET biomarkers of amyloid or tau pathology to prospectively predict cognitive decline and clinical progression to AD dementia in nondemented older individuals.\n\nMethodsWe evaluated 347 cognitive normal (CN) and 599 mild cognitively impaired (MCI) individuals. We first investigated whether PHS can predict CSF or PET amyloid and tau deposition. We evaluated differences in positive and negative predictive values of biomarker status, as a function of PHS risk. Next, we used linear mixed-effects (LME) to examine if PHS and biomarker status in conjunction, best predict longitudinal cognitive and clinical progression. Lastly, we used survival analysis to investigate whether a combination of PHS and biomarker positivity predicts progression to AD dementia better than using PHS or biomarker positivity alone.\n\nFindingsIn CN and MCI individuals, we found that amyloid and total tau positivity systematically varies as a function of PHS. For individuals in greater than the 50th percentile PHS, the positive predictive value for amyloid approached 100%. Similarly, for individuals in less than the 25th percentile PHS, the negative predictive value for total tau approached 85%. Beyond APOE, high PHS individuals with amyloid and tau pathology showed the fastest rate of longitudinal cognitive decline and time to AD dementia progression. Among the CN subgroup, we similarly found that PHS was strongly associated with amyloid positivity and the combination of PHS and biomarker status significantly predicted longitudinal clinical progression.\n\nInterpretationAmong asymptomatic and mildly symptomatic older individuals, PHS considerably improves the predictive value of CSF or PET amyloid and tau biomarkers. Beyond APOE, PHS may be useful for risk stratification and cohort enrichment for MCI and preclinical AD therapeutic trials.

genetics↗

bioRxiv2017

Immune-related genetic enrichment in frontotemporal dementia

BackgroundConverging evidence suggests that immune-mediated dysfunction plays an important role in the pathogenesis of frontotemporal dementia (FTD). Although genetic studies have shown that immune-associated loci are associated with increased FTD risk, a systematic investigation of genetic overlap between immune-mediated diseases and the spectrum of FTD-related disorders has not been performed.\n\nMethods and findingsUsing large genome-wide association studies (GWAS) (total n = 192,886 cases and controls) and recently developed tools to quantify genetic overlap/pleiotropy, we systematically identified single nucleotide polymorphisms (SNPs) jointly associated with FTD-related disorders namely FTD, corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), and amyotrophic lateral sclerosis (ALS) - and one or more immune-mediated diseases including Crohns disease (CD), ulcerative colitis (UC), rheumatoid arthritis (RA), type 1 diabetes (T1D), celiac disease (CeD), and psoriasis (PSOR). We found up to 270-fold genetic enrichment between FTD and RA and comparable enrichment between FTD and UC, T1D, and CeD. In contrast, we found only modest genetic enrichment between any of the immune-mediated diseases and CBD, PSP or ALS. At a conjunction false discovery rate (FDR) < 0.05, we identified numerous FTD-immune pleiotropic SNPs within the human leukocyte antigen (HLA) region on chromosome 6. By leveraging the immune diseases, we also found novel FTD susceptibility loci within LRRK2 (Leucine Rich Repeat Kinase 2), TBKBP1 (TANK-binding kinase 1 Binding Protein 1), and PGBD5 (PiggyBac Transposable Element Derived 5). Functionally, we found that expression of FTD-immune pleiotropic genes (particularly within the HLA region) is altered in postmortem brain tissue from patients with frontotemporal dementia and is enriched in microglia compared to other central nervous system (CNS) cell types.\n\nConclusionsWe show considerable immune-mediated genetic enrichment specifically in FTD, particularly within the HLA region. Our genetic results suggest that for a subset of patients, immune dysfunction may contribute to risk for FTD. These findings have potential implications for clinical trials targeting immune dysfunction in patients with FTD.

genetics↗

bioRxiv2017

Polygenic hazard scores in preclinical Alzheimer’s disease

Identifying asymptomatic older individuals at elevated risk for developing Alzheimers disease (AD) is of clinical importance. Among 1,081 asymptomatic older adults, a recently validated polygenic hazard score (PHS) significantly predicted time to AD dementia and steeper longitudinal cognitive decline, even after controlling for APOE {varepsilon}4 carrier status. Older individuals in the highest PHS percentiles showed the highest AD incidence rates. PHS predicted longitudinal clinical decline among older individuals with moderate to high CERAD (amyloid) and Braak (tau) scores at autopsy, even among APOE {varepsilon}4 non-carriers. Beyond APOE, PHS may help identify asymptomatic individuals at highest risk for developing Alzheimers neurodegeneration.

genetics↗

bioRxiv2016

A genetic risk score to guide age-specific, personalized prostate cancer screening

BackgroundProstate-specific-antigen (PSA) screening resulted in reduced prostate cancer (PCa) mortality in a large clinical trial, but due to a high false-positive rate, among other concerns, many guidelines do not endorse universal screening and instead recommend an individualized decision based on each patients risk. Genetic risk may provide key information to guide the decisions of whether and at what age to screen an individual man for PCa.\n\nMethodsGenotype, PCa status, and age from 34,444 men of European ancestry from the PRACTICAL consortium database were analyzed to select single-nucleotide polymorphisms (SNPs) associated with prostate cancer diagnosis. These SNPs were then incorporated into a survival analysis to estimate their effects on age at PCa diagnosis. The resulting polygenic hazard score (PHS) is an assessment of individual genetic risk. The final model was validated in an independent dataset comprised of 6,417 men with screening PSA and genotype data. PHS was calculated for these men to test for prediction of PCa-free survival. PHS was also combined with age-specific PCa incidence data from the U.S. population to generate a PCa-Risk (PCaR) age that relates a given mans risk to that of the population average. PHS and PCaR age were evaluated for prediction of positive predictive value (PPV) of PSA screening.\n\nFindingsPHS calculated from 54 SNPs was very highly predictive of age at PCa diagnosis for men in the validation set (p =10-53). PPV of PSA screening varied from 0.18 to 0.52 for men with low and high genetic risk, respectively. PHS modulates PCa-free survival curves by an estimated 20 years between men in the 1st or 99th percentiles of genetic risk.\n\nInterpretationPolygenic hazard scores give personalized genetic risk estimates and can inform the decisions of whether and at what age to screen a man for PCa.\n\nFundingDepartment of Defense #W81XWH-13-1-0391

genetics↗