Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Genome-wide association study identifies 30 loci associated with bipolar disorder

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P < 1 × 10−4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P < 5 × 10−8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

New insights into the genetic etiology of Alzheimer's disease and related dementias.

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

Brain volumetric deficits in MAPT mutation carriers: a multisite study

Objective: MAPT mutations typically cause behavioral variant frontotemporal dementia with or without parkinsonism. Previous studies have shown that symptomatic MAPT mutation carriers have frontotemporal atrophy, yet studies have shown mixed results as to whether presymptomatic carriers have low gray matter volumes. To elucidate whether presymptomatic carriers have lower structural brain volumes within regions atrophied during the symptomatic phase, we studied a large cohort of MAPT mutation carriers using a voxelwise approach. Methods: We studied 22 symptomatic carriers (age 54.7 ± 9.1, 13 female) and 43 presymptomatic carriers (age 39.2 ± 10.4, 21 female). Symptomatic carriers’ clinical syndromes included: behavioral variant frontotemporal dementia (18), an amnestic dementia syndrome (2), Parkinson’s disease (1), and mild cognitive impairment (1). We performed voxel-based morphometry on T1 images and assessed brain volumetrics by clinical subgroup, age, and mutation subtype. Results: Symptomatic carriers showed gray matter atrophy in bilateral frontotemporal cortex, insula, and striatum, and white matter atrophy in bilateral corpus callosum and uncinate fasciculus. Approximately 20% of presymptomatic carriers had low gray matter volumes in bilateral hippocampus, amygdala, and lateral temporal cortex. Within these regions, low gray matter volume

Exploration of shared genetic architecture between subcortical brain volumes and anorexia nervosa

In MRI scans of patientswith anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknownwhether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlyingAN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlationsrangedfrom-0.10to0.23(allp > 0.05). Thereweresomesigns ofaninverseconcordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [ 0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune systemrelevant genes, in particularDRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain-and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN.Stress-related psychiatric disorders across the life spa

Uncovering the heterogeneity and temporal complexity of neurodegenerative diseases with Subtype and Stage Inference

The heterogeneity of neurodegenerative diseases is a key confound to disease understanding and treatment development, as study cohorts typically include multiple phenotypes on distinct disease trajectories. Here we introduce a machine-learning technique\u2014Subtype and Stage Inference (SuStaIn)\u2014able to uncover data-driven disease phenotypes with distinct temporal progression patterns, from widely available cross-sectional patient studies. Results from imaging studies in two neurodegenerative diseases reveal subgroups and their distinct trajectories of regional neurodegeneration. In genetic frontotemporal dementia, SuStaIn identifies genotypes from imaging alone, validating its ability to identify subtypes; further the technique reveals within-genotype heterogeneity. In Alzheimer\u2019s disease, SuStaIn uncovers three subtypes, uniquely characterising their temporal complexity. SuStaIn provides fine-grained patient stratification, which substantially enhances the ability to predict conversion between diagnostic categories over standard models that ignore subtype (p = 7.18 7 10 124 ) or temporal stage (p = 3.96 7 10 125 ). SuStaIn offers new promise for enabling disease subtype discovery and precision medicine

Oculomotor control in asymptomatic and recently diagnosed individuals with the genetic marker for Huntington’s disease

AbstractWe compared oculomotor control among individuals in the early stages of Huntington’s disease (HD), with that of individuals who are presymptomatic HD gene carriers (PSGC) and nongene carriers (NGC). The oculomotor testing paradigm included both traditional tests and a novel experimental procedure to assess visual scanning. Traditional tests elicited saccades, pursuit and optokinetic nystagmus (OKN). HD patients demonstrated marked delay in the initiation of volitional saccades (anti-saccade and memory-guided saccades), a reduced number of correct volitional saccades, reduced velocity of saccades, and a decreased OKN gain. We also studied visual scanning while the participants completed the Digit Symbol Subscale of the Wechsler Adult Intelligence Survey-Revised (WAIS-R). The HD participants demonstrated an abnormal gaze strategy, which may be associated with attention and/or planning deficits.Differences between the PSGC and NGC groups were only observed for two measures: PSGC had a decreased number of memory-guided saccades and a subtle delay in the initiation of volitional saccades. Our results suggest that oculomotor measures are a sensitive biomarker in the early stage of HD and demonstrate that the combination of more traditional oculomotor tests with visual scanning tests is useful in the evaluation of visual performance

Supplementary Material for: <b><i>Fibroblast Growth Factor 23</i></b> Genotype and Cardiovascular Disease in Patients Undergoing Hemodialysis

Background: Elevated serum concentrations of fibroblast growth factor 23 (FGF23) are associated with cardiovascular mortality in patients with chronic kidney disease and those undergoing dialysis. Objectives: We tested the hypotheses that polymorphisms in FGF23, its co-receptor alpha-klotho (KL), and/or FGF23 receptors (FGFR) are associated with cardiovascular events and/or mortality. Methods: We used 1,494 DNA samples collected at baseline from the Evaluation of Cinacalcet HCl Therapy to Lower Cardiovascular Events Trial, in which patients were randomized to the calcimimetic cinacalcet or placebo for the treatment of secondary hyperparathyroidism. We analyzed European and African Ancestry samples separately and then combined summary statistics to perform a meta-analysis. We evaluated single-nucleotide polymorphisms (SNPs) in FGF23, KL, and FGFR4 as the key exposures of interest in proportional hazards (Cox) regression models using adjudicated endpoints (all-cause and cardiovascular mortality, sudden cardiac death, and heart failure [HF]) as the outcomes of interest. Results: rs11063112 in FGF23 was associated with cardiovascular mortality (risk allele = A, hazard ratio [HR] 1.32, meta-p value = 0.004) and HF (HR 1.40, meta-p value = 0.007). No statistically significant associations were observed between FGF23 rs13312789 and SNPs in FGFR4 or KL genes and the outcomes of interest. Conclusions: rs11063112 was associated with HF and cardiovascular mortality in patients receiving dialysis with moderate to severe secondary hyperparathyroidism