Pathway-specific Polygenic Risk Scores Research Articles

Pathway-Specific Polygenic Risk Scores Correlate with Clinical Status and Alzheimer's Disease-Related Biomarkers.

APOE is the largest genetic risk factor for Alzheimer's disease (AD), but there is a substantial polygenic component. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk across molecular processes and pathways that contribute to heterogeneity of disease presentation. We examined polygenic risk impacting specific AD-associated pathways and its relationship with clinical status and biomarkers of amyloid, tau, and neurodegeneration (A/T/N). We analyzed data from 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied pathway analysis and clustering to identify AD-associated "pathway clusters" and construct pathway-specific PRSs (excluding the APOE region). We tested associations with diagnostic status, abnormal levels of amyloid and ptau, and hippocampal volume. Thirteen pathway clusters were identified, and eight pathway-specific PRSs were significantly associated with AD diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau-positivity was also associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs. Pathway PRS may contribute to understanding separable disease processes, but do not add significant power for predictive purposes. These findings demonstrate that AD-phenotypes may be preferentially associated with risk in specific pathways, and defining genetic risk along multiple dimensions may clarify etiological heterogeneity in AD. This approach to delineate pathway-specific PRS can be used to study other complex diseases.

Effect of Pathway-Specific Polygenic Risk Scores for Alzheimer's Disease (AD) on Rate of Change in Cognitive Function and AD-Related Biomarkers Among Asymptomatic Individuals.

Genetic scores for late-onset Alzheimer's disease (LOAD) have been associated with preclinical cognitive decline and biomarker variations. Compared with an overall polygenic risk score (PRS), a pathway-specific PRS (p-PRS) may be more appropriate in predicting a specific biomarker or cognitive component underlying LOAD pathology earlier in the lifespan. In this study, we leveraged longitudinal data from the Wisconsin Registry for Alzheimer's Prevention and explored changing patterns in cognition and biomarkers at various age points along six biological pathways. PRS and p-PRSs with and without APOE were constructed separately based on the significant SNPs associated with LOAD in a recent genome-wide association study meta-analysis and compared to APOE alone. We used a linear mixed-effects model to assess the association between PRS/p-PRSs and cognitive trajectories among 1,175 individuals. We also applied the model to the outcomes of cerebrospinal fluid biomarkers in a subset. Replication analyses were performed in an independent sample. We found p-PRSs and the overall PRS can predict preclinical changes in cognition and biomarkers. The effects of PRS/p-PRSs on rate of change in cognition, amyloid-β, and tau outcomes are dependent on age and appear earlier in the lifespan when APOE is included in these risk scores compared to when APOE is excluded. In addition to APOE, the p-PRSs can predict age-dependent changes in amyloid-β, tau, and cognition. Once validated, they could be used to identify individuals with an elevated genetic risk of accumulating amyloid-β and tau, long before the onset of clinical symptoms.

Effect of polygenic risk for schizophrenia on cardiac structure and function: a UK Biobank observational study

Cardiovascular disease is a major cause of excess mortality in people with schizophrenia. Several factors are responsible, including lifestyle and metabolic effects of antipsychotics. However, variations in cardiac structure and function are seen in people with schizophrenia in the absence of cardiovascular disease risk factors and after accounting for lifestyle and medication. Therefore, we aimed to explore whether shared genetic causes contribute to these cardiac variations. For this observational study, we used data from the UK Biobank and included White British or Irish individuals without diagnosed schizophrenia with variable polygenic risk scores for the condition. To test the association between polygenic risk score for schizophrenia and cardiac phenotype, we used principal component analysis and regression. Robust regression was then used to explore the association between the polygenic risk score for schizophrenia and individual cardiac phenotypes. We repeated analyses with fibro-inflammatory pathway-specific polygenic risk scores for schizophrenia. Last, we investigated genome-wide sharing of common variants between schizophrenia and cardiac phenotypes using linkage disequilibrium score regression. The primary outcome was principal component regression. Of 33 353 individuals recruited, 32 279 participants had complete cardiac MRI data and were included in the analysis, of whom 16 625 (51·5%) were female and 15 654 (48·5%) were male. 1074 participants were excluded on the basis of incomplete cardiac MRI data (for all phenotypes). A model regressing polygenic risk scores for schizophrenia onto the first five cardiac principal components of the principal components analysis was significant (F=5·09; p=0·00012). Principal component 1 captured a pattern of increased cardiac volumes, increased absolute peak diastolic strain rates, and reduced ejection fractions; polygenic risk scores for schizophrenia and principal component 1 were negatively associated (β=-0·01 [SE 0·003]; p=0·017). Similar to the principal component analysis results, for individual cardiac phenotypes, we observed negative associations between polygenic risk scores for schizophrenia and indexed right ventricular end-systolic volume (β=-0·14 [0·04]; p=0·0013, pFDR=0·015), indexed right ventricular end-diastolic volume (β=-0·17 [0·08]); p=0·025; pFDR=0·082), and absolute longitudinal peak diastolic strain rates (β=-0·01 [0·003]; p=0·0024, pFDR=0·015), and a positive association between polygenic risk scores for schizophrenia and right ventricular ejection fraction (β=0·09 [0·03]; p=0·0041, pFDR=0·015). Models examining the transforming growth factor-β (TGF-β)-specific and acute inflammation-specific polygenic risk scores for schizophrenia found significant associations with the first five principal components (F=2·62, p=0·022; F=2·54, p=0·026). Using linkage disequilibrium score regression, we observed genetic overlap with schizophrenia for right ventricular end-systolic volume and right ventricular ejection fraction (p=0·0090, p=0·0077). High polygenic risk scores for schizophrenia are associated with decreased cardiac volumes, increased ejection fractions, and decreased absolute peak diastolic strain rates. TGF-β and inflammatory pathways might be implicated, and there is evidence of genetic overlap for some cardiac phenotypes. Reduced absolute peak diastolic strain rates indicate increased myocardial stiffness and diastolic dysfunction, which increases risk of cardiac disease. Thus, genetic risk for schizophrenia is associated with cardiac structural changes that can worsen cardiac outcomes. Further work is required to determine whether these associations are specific to schizophrenia or are also seen in other psychiatric conditions. National Institute for Health Research, Maudsley Charity, Wellcome Trust, Medical Research Council, Academy of Medical Sciences, Edmond J Safra Foundation, British Heart Foundation.

Alzheimer’s Disease‐Related Polygenic Risk Score Profiles and Brain Proteinopathies

AbstractBackgroundGenome‐wide association studies (GWAS) have identified more than 70 genetic loci significantly associated with Alzheimer’s disease (AD). AD‐associated genetic variants have been mapped to biological pathways including endocytosis, oxidative stress, immune response, synaptic plasticity, lipid metabolic, apoptotic process, and amyloid‐beta formation. These diverse biological pathways may be differentially responsible for brain pathologies and combinations of proteinopathies. Pathway‐specific polygenic risk scores (PRSs) are useful to estimate an individual’s genetic liability according to well‐characterized biologic pathways. In this study, we investigated differences in AD‐PRSs calculated by biological pathways in different brain proteinopathies.MethodParticipant data comprised autopsied volunteers from the National Alzheimer’s Coordinating Center (NACC) database linked to Alzheimer’s Disease Genetics Consortium (ADGC) genotype data. We obtained Gene Ontology (GO) terms listed for Homo sapiens and mapped genes to each of the GO terms. Of 18,826 GO terms, 7,300 biological processes were extracted among those constructed of 3 or more genes. We also obtained AD‐related GWAS summary statistics from Kunkle et al. (2019; PMID 30820047). We then extracted single nucleotide polymorphisms (SNPs) with p<0.5 that were not located near the APOE loci. We examined the associations between biological pathway‐specific PRSs and proteinopathies using the Kruskal Wallis non‐parametric test.ResultADGC genotype data were available for 1,610 NACC participants. There were 4,866 biological processes that had GWAS summary statistics from at least five SNPs. The distributions of “negative regulation of amyloid‐beta formation” PRSs were significantly different between A scores (Thal phase ratings for Aβ distribution: A0 = Phase 0, A1 = Phase 1 or 2, A2 = Phase 3, and A3 = Phase 4 or 5). The top three biological processes for B score (Braak NFT stage: B0 = Stage 0, B1 = Stage I or II, B2 = Stage III or IV, and B3 = Stage V or VI) were “cell differentiation”, “signal transduction”, and “protein transport”. There was no significant biological pathway associated with TDP‐43 or Lewy body pathologies.ConclusionDistinct brain proteinopatholies are likely caused by disruption of unique, albeit correlated, biological pathways. Further studies that integrate genetic information with PRSs may elucidate the mechanisms underlying brain proteinopathies.

Dissecting Polygenic Etiology of Ischemic Stroke in the Era of Precision Medicine.

Ischemic stroke (IS), the leading cause of death and disability worldwide, is caused by many modifiable and non-modifiable risk factors. This complex disease is also known for its multiple etiologies with moderate heritability. Polygenic risk scores (PRSs), which have been used to establish a common genetic basis for IS, may contribute to IS risk stratification for disease/outcome prediction and personalized management. Statistical modeling and machine learning algorithms have contributed significantly to this field. For instance, multiple algorithms have been successfully applied to PRS construction and integration of genetic and non-genetic features for outcome prediction to aid in risk stratification for personalized management and prevention measures. PRS derived from variants with effect size estimated based on the summary statistics of a specific subtype shows a stronger association with the matched subtype. The disruption of the extracellular matrix and amyloidosis account for the pathogenesis of cerebral small vessel disease (CSVD). Pathway-specific PRS analyses confirm known and identify novel etiologies related to IS. Some of these specific PRSs (e.g., derived from endothelial cell apoptosis pathway) individually contribute to post-IS mortality and, together with clinical risk factors, better predict post-IS mortality. In this review, we summarize the genetic basis of IS, emphasizing the application of methodologies and algorithms used to construct PRSs and integrate genetics into risk models.

Pathway-Specific Polygenic Risk Scores Identify Obstructive Sleep Apnea-Related Pathways Differentially Moderating Genetic Susceptibility to Coronary Artery Disease.

Obstructive sleep apnea (OSA) and its features, such as chronic intermittent hypoxia, may differentially affect specific molecular pathways and processes in the pathogenesis of coronary artery disease (CAD) and influence the subsequent risk and severity of CAD events. In particular, competing adverse (eg, inflammatory) and protective (eg, increased coronary collateral blood flow) mechanisms may operate, but remain poorly understood. We hypothesize that common genetic variation in selected molecular pathways influences the likelihood of CAD events differently in individuals with and without OSA, in a pathway-dependent manner. We selected a cross-sectional sample of 471 877 participants from the UK Biobank, with 4974 ascertained to have OSA, 25 988 to have CAD, and 711 to have both. We calculated pathway-specific polygenic risk scores for CAD, based on 6.6 million common variants evaluated in the CARDIoGRAMplusC4D genome-wide association study (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics), annotated to specific genes and pathways using functional genomics databases. Based on prior evidence of involvement with intermittent hypoxia and CAD, we tested pathway-specific polygenic risk scores for the HIF1 (hypoxia-inducible factor 1), VEGF (vascular endothelial growth factor), NFκB (nuclear factor kappa-light-chain-enhancer of activated B cells) and TNF (tumor necrosis factor) signaling pathways. In a multivariable-adjusted logistic generalized additive model, elevated pathway-specific polygenic risk scores for the Kyoto Encyclopedia of Genes and Genomes VEGF pathway (39 genes) associated with protection for CAD in OSA (interaction odds ratio 0.86, P=6×10-4). By contrast, the genome-wide CAD PRS did not show evidence of statistical interaction with OSA. We find evidence that pathway-specific genetic risk of CAD differs between individuals with and without OSA in a qualitatively pathway-dependent manner. These results provide evidence that gene-by-environment interaction influences CAD risk in certain pathways among people with OSA, an effect that is not well-captured by the genome-wide PRS. This invites further study of how OSA interacts with genetic risk at the molecular level and suggests eventual personalization of OSA treatment to reduce CAD risk according to individual pathway-specific genetic risk profiles.

Gene set enrichment analysis of pathophysiological pathways highlights oxidative stress in psychosis

Polygenic risk prediction remains an important aim of genetic association studies. Currently, the predictive power of schizophrenia polygenic risk scores (PRSs) is not large enough to allow highly accurate discrimination between cases and controls and thus is not adequate for clinical integration. Since PRSs are rarely used to reveal biological functions or to validate candidate pathways, to fill this gap, we investigated whether their predictive ability could be improved by building genome-wide (GW-PRSs) and pathway-specific PRSs, using distance- or expression quantitative trait loci (eQTLs)- based mapping between genetic variants and genes. We focused on five pathways (glutamate, oxidative stress, GABA/interneurons, neuroimmune/neuroinflammation and myelin) which belong to a critical hub of schizophrenia pathophysiology, centred on redox dysregulation/oxidative stress. Analyses were first performed in the Lausanne Treatment and Early Intervention in Psychosis Program (TIPP) study (n = 340, cases/controls: 208/132), a sample of first-episode of psychosis patients and matched controls, and then validated in an independent study, the epidemiological and longitudinal intervention program of First-Episode Psychosis in Cantabria (PAFIP) (n = 352, 224/128). Our results highlighted two main findings. First, GW-PRSs for schizophrenia were significantly associated with early psychosis status. Second, oxidative stress was the only significantly associated pathway that showed an enrichment in both the TIPP (p = 0.03) and PAFIP samples (p = 0.002), and exclusively when gene-variant linking was done using eQTLs. The results suggest that the predictive accuracy of polygenic risk scores could be improved with the inclusion of information from functional annotations, and through a focus on specific pathways, emphasizing the need to build and study functionally informed risk scores.

A Pathway-Specific Polygenic Risk Score Is Associated with Tau Pathology and Cognitive Decline.

Tauopathy is a primary neuropathological hallmark of Alzheimer's disease with a strong relationship to cognitive impairment. In the brain, tau aggregation is associated with the regulation of tau kinases and the binding ability of tau to microtubules. To explore the potential for using specific polygenic risk scores (PRSs), combining the genetic influences involved in tau-protein kinases and the tau-protein binding pathway, as predictors of tau pathology and cognitive decline in non-demented individuals. We computed a pathway-specific PRS using summary statistics from previous large-scale genome-wide association studies of dementia. We examined whether PRS is related to tau uptake in positron emission tomography (PET), tau levels, and the rate of tau level changes in cerebrospinal fluid (CSF). We further assessed whether PRS is associated with memory impairment mediated by CSF tau levels. A higher PRS was related to elevated CSF tau levels and tau-PET uptake at baseline, as well as greater rates of change in CSF tau levels. Moreover, PRS was associated with memory impairment, mediated by increased CSF tau levels. The association between PRS and tau pathology was significant when APOE was excluded, even among females. However, the effect of PRS on cognitive decline appeared to be driven by the inclusion of APOE. The influence of genetic risk in a specific tau-related biological pathway may make an individual more susceptible to tau pathology, resulting in cognitive dysfunction in an early preclinical phase of the disease.

Pathway-specific polygenic risk score of AD-associated genetic variants associated with AD risk, resilience against AD, and progression to AD.

Several collaborative genome-wide-association studies (GWAS) have characterized the genetic landscape of Alzheimer's disease (AD), which now counts >70 single-nucleotide polymorphisms (SNPs) associated with AD-risk. We linked these SNPs to their affected biological pathways, and combined the effect of multiple SNPs into pathway-specific polygenic-risk-scores (PRS). Using a genetically homogeneous dataset of 2,458 AD-patients (age=70.2±10.4), 3,848 healthy controls (age=61.1±14.8), 343 cognitively healthy centenarians (age=101.1±1.8) and 705 individuals with mild-cognitive-impairment (MCI, age=69.1±8.9), we studied the association between pathway-PRS and AD-risk, MCI-to-AD conversion, and resilience against AD. With an integrative strategy, we linked 72 AD-associated SNPs to 5 clusters of biological pathways: beta-amyloid cluster, immune cluster, vascular cluster, endocytosis cluster and a trafficking cluster (Figure 1). A PRS comprising all 72 SNPs (excluding APOE-SNPs) was significantly associated with AD-risk (OR=1.53, p<2e-16), progression of MCI to AD dementia (OR=1.45, p=5.5e-4), and, albeit in the opposite direction, resilience against AD in healthy centenarians (OR=0.82, p=6.4e-4) (Figure 2, Figure 3). At the pathway level, all pathway-PRS significantly associated with increased AD-risk while specifically the vascular-, endocytosis- and trafficking-PRS associated with resilience against AD (p<0.05) (Figure 4). Interestingly, the beta-amyloid-, endocytosis and trafficking-PRSs were significantly associated with MCI-to-AD progression (p<0.05), with a higher-PRS leading up to 1.5-year shorter conversion time. Our results add on the efficacy of pathway-specific PRSs to identify individuals at highest or the lowest risk for the development of AD. Further, our results suggest that specific biological pathways are more important at different stages of the disease or in fact, associate with the escape of disease. AD diagnostic procedures may benefit from the identification of individual, pathway-specific vulnerabilities. In the future, pathway-specific PRSs may contribute to the selection of patients who may benefit most from pathway-specific treatment strategies.

Risk factors for melanoma by anatomical site: an evaluation of aetiological heterogeneity.

Melanoma aetiology has been proposed to have two pathways, which are determined by naevi and type of sun exposure and related to the anatomical site where melanoma develops. We examined associations with melanoma by anatomical site for a comprehensive set of risk factors including pigmentary and naevus phenotypes, ultraviolet radiation exposure and polygenic risk. We analysed harmonized data from 2617 people with incident first invasive melanoma and 975 healthy controls recruited through two population-based case-control studies in Australia and the UK. Questionnaire data were collected by interview using a single protocol, and pathway-specific polygenic risk scores were derived from DNA samples. We estimated adjusted odds ratios using unconditional logistic regression that compared melanoma cases at each anatomical site with all controls. When cases were compared with control participants, there were stronger associations for many naevi vs. no naevi for melanomas on the trunk, and upper and lower limbs than on the head and neck (P-heterogeneity<0·001). Very fair skin (vs. olive/brown skin) was more weakly related to melanoma on the trunk than to melanomas at other sites (P-heterogeneity=0·04). There was no significant difference by anatomical site for polygenic risk. Increased weekday sun exposure was positively associated with melanoma on the head and neck but not on other sites. We found evidence of aetiological heterogeneity for melanoma, supporting the dual pathway hypothesis. These findings enhance understanding of risk factors for melanoma and can guide prevention and skin examination education and practices.

The Differential Influence of Immune, Endocytotic, and Lipid Metabolism Genes on Amyloid Deposition and Neurodegeneration in Subjects at Risk of Alzheimer's Disease.

Over 20 single-nucleotide polymorphisms (SNPs) are associated with increased risk of Alzheimer's disease (AD). We categorized these loci into immunity, lipid metabolism, and endocytosis pathways, and associated the polygenic risk scores (PRS) calculated, with AD biomarkers in mild cognitive impairment (MCI) subjects. The aim of this study was to identify associations between pathway-specific PRS and AD biomarkers in patients with MCI and healthy controls. AD biomarkers ([18F]Florbetapir-PET SUVR, FDG-PET SUVR, hippocampal volume, CSF tau and amyloid-β levels) and neurocognitive tests scores were obtained in 258 healthy controls and 451 MCI subjects from the ADNI dataset at baseline and at 24-month follow up. Pathway-related (immunity, lipid metabolism, and endocytosis) and total polygenic risk scores were calculated from 20 SNPs. Multiple linear regression analysis was used to test predictive value of the polygenic risk scores over longitudinal biomarker and cognitive changes. Higher immune risk score was associated with worse cognitive measures and reduced glucose metabolism. Higher lipid risk score was associated with increased amyloid deposition and cortical hypometabolism. Total, immune, and lipid scores were associated with significant changes in cognitive measures, amyloid deposition, and brain metabolism. Polygenic risk scores highlights the influence of specific genes on amyloid-dependent and independent pathways; and these pathways could be differentially influenced by lipid and immune scores respectively.

Immune response and endocytosis pathways are associated with the resilience against Alzheimer\u2019s disease

Developing Alzheimer’s disease (AD) is influenced by multiple genetic variants that are involved in five major AD-pathways. Per individual, these pathways may differentially contribute to the modification of the AD-risk. The pathways involved in the resilience against AD have thus far been poorly addressed. Here, we investigated to what extent each molecular mechanism associates with (i) the increased risk of AD and (ii) the resilience against AD until extreme old age, by comparing pathway-specific polygenic risk scores (pathway-PRS). We used 29 genetic variants associated with AD to develop pathway-PRS for five major pathways involved in AD. We developed an integrative framework that allows multiple genes to associate with a variant, and multiple pathways to associate with a gene. We studied pathway-PRS in the Amsterdam Dementia Cohort of well-phenotyped AD patients (N = 1895), Dutch population controls from the Longitudinal Aging Study Amsterdam (N = 1654) and our unique 100-plus Study cohort of cognitively healthy centenarians who avoided AD (N = 293). Last, we estimated the contribution of each pathway to the genetic risk of AD in the general population. All pathway-PRS significantly associated with increased AD-risk and (in the opposite direction) with resilience against AD (except for angiogenesis, p < 0.05). The pathway that contributed most to the overall modulation of AD-risk was β-amyloid metabolism (29.6%), which was driven mainly by APOE-variants. After excluding APOE variants, all pathway-PRS associated with increased AD-risk (except for angiogenesis, p < 0.05), while specifically immune response (p = 0.003) and endocytosis (p = 0.0003) associated with resilience against AD. Indeed, the variants in these latter two pathways became the main contributors to the overall modulation of genetic risk of AD (45.5% and 19.2%, respectively). The genetic variants associated with the resilience against AD indicate which pathways are involved with maintained cognitive functioning until extreme ages. Our work suggests that a favorable immune response and a maintained endocytosis pathway might be involved in general neuro-protection, which highlight the need to investigate these pathways, next to β-amyloid metabolism.

Identification of biological pathways to Alzheimer's disease using polygenic scores

IntroductionSingle nucleotide polymorphisms (SNPs) contribute small increases in risk for late-onset Alzheimer's disease (LOAD). LOAD SNPs cluster around genes with similar biological functions (pathways). Polygenic risk scores (PRS) aggregate the effect of SNPs genome-wide. However, this approach has not been widely used for SNPs within specific pathways.ObjectivesWe investigated whether pathway-specific PRS were significant predictors of LOAD case/control status.MethodsWe mapped SNPs to genes within 8 pathways implicated in LOAD. For our polygenic analysis, the discovery sample comprised 13,831 LOAD cases and 29,877 controls. LOAD risk alleles for SNPs in our 8 pathways were identified at a P-value threshold of 0.5. Pathway-specific PRS were calculated in a target sample of 3332 cases and 9832 controls. The genetic data were pruned with R2 &gt; 0.2 while retaining the SNPs most significantly associated with AD. We tested whether pathway-specific PRS were associated with LOAD using logistic regression, adjusting for age, sex, country, and principal components. We report the proportion of variance in liability explained by each pathway.ResultsThe most strongly associated pathways were the immune response (NSNPs = 9304, = 5.63 × 10−19, R2 = 0.04) and hemostasis (NSNPs = 7832, P = 5.47 × 10−7, R2 = 0.015). Regulation of endocytosis, hematopoietic cell lineage, cholesterol transport, clathrin and protein folding were also significantly associated but accounted for less than 1% of the variance. With APOE excluded, all pathways remained significant except proteasome-ubiquitin activity and protein folding.ConclusionsGenetic risk for LOAD can be split into contributions from different biological pathways. These offer a means to explore disease mechanisms and to stratify patients.Disclosure of interestThe authors have not supplied their declaration of competing interest.

CLINICAL AND GENETIC PREDICTION OF ONSET AND COURSE OF ILLNESS IN SUBJECTS AT RISK FOR BIPOLAR DISORDER

As part of a five-site collaborative study, we are following 300 adolescents/young adults at high risk for bipolar disorder and related conditions (because they are close relatives of a bipolar proband), along with 150 age-matched controls. A new follow-up protocol is beginning over the next several months. The risk for major mood disorder is ~35% for high risk offspring and ~7% for controls. An additional reference sample, available for studies of course of illness is the BiGS sample, including > 600 families with multiple cases of bipolar disorder and >4000 unrelated bipolar cases. Using these three samples (high risk, familial BP, case BP) we describe the development of a clinical subtyping scheme and its potential use in predicting risk and course of illness. We have now obtained complete, newly imputed, genotype data from the PGC on all of our cases and ethnically matched controls, as well as the high risk sample. These data are being used to develop polygenic risk scores for use in prediction of illness (as part of the research, not for clinical purposes currently). We are also using the genotype data in conjunction with our published work on bipolar pathways (Nurnberger et al, JAMA Psychiatry, 2014) in order to derive pathway-specific polygenic risk scores. These will be applied to BPI cases in general and to the specific subtypes we have described (Monahan et al, Psychological Medicine, 2015): 1) pure BPI, 2) BPI plus internalizing disorder, 3) BPI plus externalizing disorder, and 4) BPI plus externalizing and internalizing disorder.

Pathway-Specific Polygenic Risk Scores as Predictors of Amyloid-β Deposition and Cognitive Function in a Sample at Increased Risk for Alzheimer's Disease.

Polygenic risk scores (PRSs) have been used to combine the effects of variants with small effects identified by genome-wide association studies. We explore the potential for using pathway-specific PRSs as predictors of early changes in Alzheimer's disease (AD)-related biomarkers and cognitive function. Participants were from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults who were cognitively asymptomatic at enrollment and enriched for a parental history of AD. Using genes associated with AD in the International Genomics of Alzheimer's Project's meta-analysis, we identified clusters of genes that grouped into pathways involved in amyloid-β (Aβ) deposition and neurodegeneration: Aβ clearance, cholesterol metabolism, and immune response. Weighted pathway-specific and overall PRSs were developed and compared to APOE alone. Mixed models were used to assess whether each PRS was associated with cognition in 1,200 individuals, cerebral Aβ deposition measured using amyloid ligand (Pittsburgh compound B) positron emission imaging in 168 individuals, and cerebrospinal fluid Aβ deposition, neurodegeneration, and tau pathology in 111 individuals, with replication performed in an independent sample. We found that PRSs including APOE appeared to be driven by the inclusion of APOE, suggesting that the pathway-specific PRSs used here were not more predictive than an overall PRS or APOE alone. However, pathway-specific PRSs could prove to be useful as more knowledge is gained on the genetic variants involved in specific biological pathways of AD.