A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networks.

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

Uncovering Unrecognized Heart Failure With Preserved Ejection Fraction Among Individuals With Obesity and Dyspnea.

BACKGROUND: Although heart failure with preserved ejection fraction (HFpEF) has become the predominant heart failure subtype, it remains clinically under-recognized. HFpEF diagnosis is particularly challenging in the setting of obesity given the limitations of natriuretic peptides and resting echocardiography. We examined invasive and noninvasive HFpEF diagnostic criteria among individuals with obesity and dyspnea without known cardiovascular disease to determine the prevalence of hemodynamic HFpEF in the community. METHODS: Research volunteers with dyspnea and obesity underwent resting echocardiography; participants with possible pulmonary hypertension qualified for invasive cardiopulmonary exercise testing. HFpEF was defined using rest or exercise pulmonary capillary wedge pressure criteria (≥15 mm Hg or Δpulmonary capillary wedge pressure/Δcardiac output slope, >2.0 mm Hg·L-1·min-1). RESULTS: Among n=78 participants (age, 53±13 years; 65% women; body mass index, 37.3±6.8 kg/m2), 40 (51%) met echocardiographic criteria to undergo invasive cardiopulmonary exercise testing. In total, 24 participants (60% among the cardiopulmonary exercise testing group, 31% among the total sample) were diagnosed with HFpEF by rest or exercise pulmonary capillary wedge pressure (n=12) or exercise criteria (n=12). There were no differences in NT-proBNP (N-terminal pro-B-type natriuretic peptide; 79 [62-104] versus 73 [57-121] pg/mL) or resting echocardiography (mitral E/e' ratio, 9.1±3.1 versus 8.0±2.7) among those with versus without HFpEF (P>0.05 for all). Distributions of HFpEF diagnostic scores were similar, with the majority classified as intermediate risk (100% versus 93.75% [H2FPEF] and 87.5% versus 68.75% [HFA-PEFF (Heart Failure Association Pretest assessment, echocardiography and natriuretic peptide, functional testing, and final etiology)] in those with versus without HFpEF). CONCLUSIONS: Among adults with obesity and dyspnea without known cardiovascular disease, at least a third had clinically unrecognized HFpEF uncovered on invasive cardiopulmonary exercise testing. Clinical, biomarker, resting echocardiography, and diagnostic scores were similar among those with and without HFpEF. These results suggest clinical underdiagnosis of HFpEF among individuals with obesity and dyspnea and highlight limitations of noninvasive testing in the identification of HFpEF.

A plasma protein-based risk score to predict hip fractures.

As there are effective treatments to reduce hip fractures, identification of patients at high risk of hip fracture is important to inform efficient intervention strategies. To obtain a new tool for hip fracture prediction, we developed a protein-based risk score in the Cardiovascular Health Study using an aptamer-based proteomic platform. The proteomic risk score predicted incident hip fractures and improved hip fracture discrimination in two Trøndelag Health Study validation cohorts using the same aptamer-based platform. When transferred to an antibody-based proteomic platform in a UK Biobank validation cohort, the proteomic risk score was strongly associated with hip fractures (hazard ratio per s.d. increase, 1.64; 95% confidence interval 1.53-1.77). The proteomic risk score, but not available polygenic risk scores for fractures or bone mineral density, improved the C-index beyond the fracture risk assessment tool (FRAX), which integrates information from clinical risk factors (C-index, FRAX 0.735 versus FRAX + proteomic risk score 0.776). The developed proteomic risk score constitutes a new tool for stratifying patients according to hip fracture risk; however, its improvement in hip fracture discrimination is modest and its clinical utility beyond FRAX with information on femoral neck bone mineral density remains to be determined.

Proteomics, Human Environmental Exposure, and Cardiometabolic Risk.

BACKGROUND: The biological mechanisms linking environmental exposures with cardiovascular disease pathobiology are incompletely understood. We sought to identify circulating proteomic signatures of environmental exposures and examine their associations with cardiometabolic and respiratory disease in observational cohort studies. METHODS: We tested the relations of >6500 circulating proteins with 29 environmental exposures across the built environment, green space, air pollution, temperature, and social vulnerability indicators in ≈3000 participants of the CARDIA study (Coronary Artery Risk Development in Young Adults) across 4 centers using penalized and ordinary linear regression. In >3500 participants from FHS (Framingham Heart Study) and JHS (Jackson Heart Study), we evaluated the prospective relations of proteomic signatures of the envirome with cardiovascular disease and mortality using Cox models. RESULTS: Proteomic signatures of the envirome identified novel/established cardiovascular disease-relevant pathways including DNA damage, fibrosis, inflammation, and mitochondrial function. The proteomic signatures of the envirome were broadly related to cardiometabolic disease and respiratory phenotypes (eg, body mass index, lipids, and left ventricular mass) in CARDIA, with replication in FHS/JHS. A proteomic signature of social vulnerability was associated with a composite of cardiovascular disease/mortality (1428 events; FHS: hazard ratio, 1.16 [95% CI, 1.08-1.24]; P=1.77×10-5; JHS: hazard ratio, 1.25 [95% CI, 1.13-1.38]; P=6.38×10-6; hazard ratioexpressed as per 1 SD increase in proteomic signature), robust to adjustment for known clinical risk factors. CONCLUSIONS: Environmental exposures are related to an inflammatory-metabolic proteome, which identifies individuals with cardiometabolic disease and respiratory phenotypes and outcomes. Future work examining the dynamic impact of the environment on human cardiometabolic health is warranted.

BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis.

Brown adipose tissue (BAT) is best known for thermogenesis. Rodent studies demonstrated that enhanced BAT thermogenesis is tightly associated with increased energy expenditure, reduced body weight, and improved glucose homeostasis. However, human BAT is protective against type 2 diabetes, independent of body weight. The mechanism underlying this dissociation remains unclear. Here, we report that impaired mitochondrial catabolism of branched-chain amino acids (BCAAs) in BAT, by deleting mitochondrial BCAA carriers (MBCs), caused systemic insulin resistance without affecting energy expenditure and body weight. Brown adipocytes catabolized BCAA in the mitochondria as nitrogen donors for the biosynthesis of non-essential amino acids and glutathione. Impaired mitochondrial BCAA-nitrogen flux in BAT resulted in increased oxidative stress, decreased hepatic insulin signaling, and decreased circulating BCAA-derived metabolites. A high-fat diet attenuated BCAA-nitrogen flux and metabolite synthesis in BAT, whereas cold-activated BAT enhanced the synthesis. This work uncovers a metabolite-mediated pathway through which BAT controls metabolic health beyond thermogenesis.

Analysis of plasma metabolomes from 11 309 subjects in five population-based cohorts.

Plasma metabolomics holds potential for precision medicine, but limited information is available to compare the performance of such methods across multiple cohorts. We compared plasma metabolite profiles after an overnight fast in 11,309 participants of five population-based Swedish cohorts (50-80 years, 52% women). Metabolite profiles were uniformly generated at a core laboratory (Metabolon Inc.) with untargeted liquid chromatography mass spectrometry and a comprehensive reference library. Analysis of a second sample obtained one year later was conducted in a subset. Of 1629 detected metabolites, 1074 (66%) were detected in all cohorts while only 10% were unique to one cohort, most of which were xenobiotics or uncharacterized. The major classes were lipids (28%), xenobiotics (22%), amino acids (14%), and uncharacterized (19%). The most abundant plasma metabolome components were the major dietary fatty acids and amino acids, glucose, lactate and creatinine. Most metabolites displayed a log-normal distribution. Temporal variability was generally similar to clinical chemistry analytes but more pronounced for xenobiotics. Extensive metabolite-metabolite correlations were observed but mainly restricted to within each class. Metabolites were broadly associated with clinical factors, particularly body mass index, sex and renal function. Collectively, our findings inform the conduct and interpretation of metabolite association and precision medicine studies.

Metabolite signatures associated with microRNA miR-143-3p serve as drivers of poor lung function trajectories in childhood asthma.

BACKGROUND: Lung function trajectories (LFTs) have been shown to be an important measure of long-term health in asthma. While there is a growing body of metabolomic studies on asthma status and other phenotypes, there are no prospective studies of the relationship between metabolomics and LFTs or their genomic determinants. METHODS: We utilized ordinal logistic regression to identify plasma metabolite principal components associated with four previously-published LFTs in children from the Childhood Asthma Management Program (CAMP) (n = 660). The top significant metabolite principal component (PCLF) was evaluated in an independent cross-sectional child cohort, the Genetic Epidemiology of Asthma in Costa Rica Study (GACRS) (n = 1151) and evaluated for association with spirometric measures. Using meta-analysis of CAMP and GACRS, we identified associations between PCLF and microRNA, and SNPs in their target genes. Statistical significance was determined using an false discovery rate-adjusted Q-value. FINDINGS: The top metabolite principal component, PCLF, was significantly associated with better LFTs after multiple-testing correction (Q-value = 0.03). PCLF is composed of the urea cycle, caffeine, corticosteroid, carnitine, and potential microbial (secondary bile acid, tryptophan, linoleate, histidine metabolism) metabolites. Higher levels of PCLF were also associated with increases in lung function measures and decreased circulating neutrophil percentage in both CAMP and GACRS. PCLF was also significantly associated with microRNA miR-143-3p, and SNPs in three miR-143-3p target genes; CCZ1 (P-value = 2.6 × 10-5), SLC8A1 (P-value = 3.9 × 10-5); and TENM4 (P-value = 4.9 × 10-5). INTERPRETATION: This study reveals associations between metabolites, miR-143-3p and LFTs in children with asthma, offering insights into asthma physiology and possible interventions to enhance lung function and long-term health. FUNDING: Molecular data for CAMP and GACRS via the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung, and Blood Institute (NHLBI).

Lac-Phe mediates the effects of metformin on food intake and body weight.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. There is ongoing debate about the mechanisms that mediate metformin's effects on energy balance. Here, we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite N-lactoyl-phenylalanine (Lac-Phe) in cells, in mice and two independent human cohorts. Metformin drives Lac-Phe biosynthesis through the inhibition of complex I, increased glycolytic flux and intracellular lactate mass action. Intestinal epithelial CNDP2+ cells, not macrophages, are the principal in vivo source of basal and metformin-inducible Lac-Phe. Genetic ablation of Lac-Phe biosynthesis in male mice renders animals resistant to the effects of metformin on food intake and body weight. Lastly, mediation analyses support a role for Lac-Phe as a downstream effector of metformin's effects on body mass index in participants of a large population-based observational cohort, the Multi-Ethnic Study of Atherosclerosis. Together, these data establish Lac-Phe as a critical mediator of the body weight-lowering effects of metformin.

Large-scale circulating proteome association study (CPAS) meta-analysis identifies circulating proteins and pathways predicting incident hip fractures.

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. In an exploratory search of the underlying biology as reflected through the circulating proteome, we performed a comprehensive Circulating Proteome Association Study (CPAS) meta-analysis for incident hip fractures. Analyses included 6430 subjects from two prospective cohort studies (Cardiovascular Health Study and Trøndelag Health Study) with circulating proteomics data (aptamer-based 5 K SomaScan version 4.0 assay; 4979 aptamers). Associations between circulating protein levels and incident hip fractures were estimated for each cohort using age and sex-adjusted Cox regression models. Participants experienced 643 incident hip fractures. Compared with the individual studies, inverse-variance weighted meta-analyses yielded more statistically significant associations, identifying 23 aptamers associated with incident hip fractures (conservative Bonferroni correction 0.05/4979, P < 1.0 × 10-5). The aptamers most strongly associated with hip fracture risk corresponded to two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR. High levels of several inflammation-related proteins (CD14, CXCL12, MMP12, ITIH3) were also associated with increased hip fracture risk. Ingenuity pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. These analyses identified several circulating proteins and pathways consistently associated with incident hip fractures. These findings underscore the usefulness of the meta-analytic approach for comprehensive CPAS in a similar manner as has previously been observed for large-scale human genetic studies. Future studies should investigate the underlying biology of these potential novel drug targets.

Hip fractures are associated with significant disability, high cost, and mortality. However, the exact biological mechanisms underlying susceptibility to hip fractures remain incompletely understood. To increase the understanding of the underlying mechanisms, we performed a meta-analysis of the associations between 4860 circulating proteins and risk of fractures using two large cohorts, including 6430 participants with 643 incident hip fractures. We identified 23 proteins/aptamers associated with incident hip fractures. Two proteins of the growth hormone/insulin growth factor system (GHR and IGFBP2), as well as GDF15 and EGFR were most strongly associated with hip fracture risk. High levels of several inflammation-related proteins were also associated with increased hip fracture risk. Pathway analysis identified reduced LXR/RXR activation and increased acute phase response signaling to be overrepresented among those proteins associated with increased hip fracture risk. Future mechanistic studies should investigate the underlying biology of these novel protein biomarkers which may be potential drug targets.

Plasma proteomic signature of human longevity.

The identification of protein targets that exhibit anti-aging clinical potential could inform interventions to lengthen the human health span. Most previous proteomics research has been focused on chronological age instead of longevity. We leveraged two large population-based prospective cohorts with long follow-ups to evaluate the proteomic signature of longevity defined by survival to 90 years of age. Plasma proteomics was measured using a SOMAscan assay in 3067 participants from the Cardiovascular Health Study (discovery cohort) and 4690 participants from the Age Gene/Environment Susceptibility-Reykjavik Study (replication cohort). Logistic regression identified 211 significant proteins in the CHS cohort using a Bonferroni-adjusted threshold, of which 168 were available in the replication cohort and 105 were replicated (corrected p value <0.05). The most significant proteins were GDF-15 and N-terminal pro-BNP in both cohorts. A parsimonious protein-based prediction model was built using 33 proteins selected by LASSO with 10-fold cross-validation and validated using 27 available proteins in the validation cohort. This protein model outperformed a basic model using traditional factors (demographics, height, weight, and smoking) by improving the AUC from 0.658 to 0.748 in the discovery cohort and from 0.755 to 0.802 in the validation cohort. We also found that the associations of 169 out of 211 proteins were partially mediated by physical and/or cognitive function. These findings could contribute to the identification of biomarkers and pathways of aging and potential therapeutic targets to delay aging and age-related diseases.

Proteomic Signature of HIV-Associated Subclinical Left Atrial Remodeling and Incident Heart Failure.

Background: People living with HIV (PLWH) are at higher risk of heart failure (HF) and preceding subclinical cardiac abnormalities, including left atrial dilation, compared to people without HIV (PWOH). Hypothesized mechanisms include premature aging linked to chronic immune activation. We leveraged plasma proteomics to identify potential novel contributors to HIV-associated differences in indexed left atrial volume (LAVi) among PLWH and PWOH and externally validated identified proteomic signatures with incident HF among a cohort of older PWOH. Methods: We performed proteomics (Olink Explore 3072) on plasma obtained concurrently with cardiac magnetic resonance imaging among PLWH and PWOH in the United States. Proteins were analyzed individually and as agnostically defined clusters. Cross-sectional associations with HIV and LAVi were estimated using multivariable regression with robust variance. Among an independent general population cohort, we estimated associations between identified signatures and LAVi using linear regression and incident HF using Cox regression. Results: Among 352 participants (age 55±6 years; 25% female), 61% were PLWH (88% on ART; 73% with undetectable HIV RNA) and mean LAVi was 29±9 mL/m 2 . Of 2594 analyzed proteins, 439 were associated with HIV serostatus, independent of demographics, hepatitis C virus infection, renal function, and substance use (FDR<0.05). We identified 73 of these proteins as candidate contributors to the independent association between positive HIV serostatus and higher LAVi, enriched in tumor necrosis factor (TNF) signaling and immune checkpoint proteins regulating T cell, B cell, and NK cell activation. We identified one protein cluster associated with LAVi and HIV regardless of HIV viral suppression status, which comprised 42 proteins enriched in TNF signaling, ephrin signaling, and extracellular matrix (ECM) organization. This protein cluster and 30 of 73 individual proteins were associated with incident HF among 2273 older PWOH (age 68±9 years; 52% female; 8.5±1.4 years of follow-up). Conclusion: Proteomic signatures that may contribute to HIV-associated LA remodeling were enriched in immune checkpoint proteins, cytokine signaling, and ECM organization. These signatures were also associated with incident HF among older PWOH, suggesting specific markers of chronic immune activation, systemic inflammation, and fibrosis may identify shared pathways in HIV and aging that contribute to risk of HF.

Mitochondrial choline import regulates purine nucleotide pools via SLC25A48.

Choline is an essential nutrient for cellular metabolism, including the biosynthesis of phospholipids, neurotransmitters, and one-carbon metabolism. A critical step of choline catabolism is the mitochondrial import and synthesis of chorine-derived methyl donors, such as betaine. However, the underlying mechanisms and the biological significance of mitochondrial choline catabolism remain insufficiently understood. Here, we report that a mitochondrial inner-membrane protein SLC25A48 controls mitochondrial choline transport and catabolism in vivo. We demonstrate that SLC25A48 is highly expressed in brown adipose tissue and required for whole-body cold tolerance, thermogenesis, and mitochondrial respiration. Mechanistically, choline uptake into the mitochondrial matrix via SLC25A48 facilitates betaine synthesis and one-carbon metabolism. Importantly, cells lacking SLC25A48 exhibited reduced synthesis of purine nucleotides and failed to initiate the G1-to-S phase transition, thereby leading to cell death. Taken together, the present study identified SLC25A48 as a mitochondrial carrier that mediates choline import and plays a critical role in mitochondrial respiratory capacity, purine nucleotide synthesis, and cell survival.

Effects of exercise training on ANGPTL3/8 and ANGPTL4/8 and their associations with cardiometabolic traits.

Angiopoietin-like protein (ANGPTL) complexes 3/8 and 4/8 are established inhibitors of LPL and novel therapeutic targets for dyslipidemia. However, the effects of regular exercise on ANGPTL3/8 and ANGPTL4/8 are unknown. We characterized ANGPTL3/8 and ANGPTL4/8 and their relationship with in vivo measurements of lipase activities and cardiometabolic traits before and after a 5-month endurance exercise training intervention in 642 adults from the HERITAGE (HEalth, RIsk factors, exercise Training And GEnetics) Family Study. At baseline, higher levels of both ANGPTL3/8 and ANGPTL4/8 were associated with a worse lipid, lipoprotein, and cardiometabolic profile, with only ANGPTL3/8 associated with postheparin LPL and HL activities. ANGPTL3/8 significantly decreased with exercise training, which corresponded with increases in LPL activity and decreases in HL activity, plasma triglycerides, apoB, visceral fat, and fasting insulin (all P < 5.1 × 10-4). Exercise-induced changes in ANGPTL4/8 were directly correlated to concomitant changes in total cholesterol, LDL-C, apoB, and HDL-triglycerides and inversely related to change in insulin sensitivity index (all P < 7.0 × 10-4). In conclusion, exercise-induced decreases in ANGPTL3/8 and ANGPTL4/8 were related to concomitant improvements in lipase activity, lipid profile, and cardiometabolic risk factors. These findings reveal the ANGPTL3-4-8 model as a potential molecular mechanism contributing to adaptations in lipid metabolism in response to exercise training.

Proteome Network Analysis Identifies Potential Biomarkers for Brain Aging.

BACKGROUND: Alzheimer's disease and related dementias (ADRD) involve biological processes that begin years to decades before onset of clinical symptoms. The plasma proteome can offer insight into brain aging and risk of incident dementia among cognitively healthy adults. OBJECTIVE: To identify biomarkers and biological pathways associated with neuroimaging measures and incident dementia in two large community-based cohorts by applying a correlation-based network analysis to the plasma proteome. METHODS: Weighted co-expression network analysis of 1,305 plasma proteins identified four modules of co-expressed proteins, which were related to MRI brain volumes and risk of incident dementia over a median 20-year follow-up in Framingham Heart Study (FHS) Offspring cohort participants (n = 1,861). Analyses were replicated in the Cardiovascular Health Study (CHS) (n = 2,117, mean 6-year follow-up). RESULTS: Two proteomic modules, one related to protein clearance and synaptic maintenance (M2) and a second to inflammation (M4), were associated with total brain volume in FHS (M2: p = 0.014; M4: p = 4.2×10-5). These modules were not significantly associated with hippocampal volume, white matter hyperintensities, or incident all-cause or AD dementia. Associations with TCBV did not replicate in CHS, an older cohort with a greater burden of comorbidities. CONCLUSIONS: Proteome networks implicate an early role for biological pathways involving inflammation and synaptic function in preclinical brain atrophy, with implications for clinical dementia.

Lac-Phe mediates the anti-obesity effect of metformin.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. The mechanisms that mediate metformin's effects on energy balance remain incompletely defined. Here we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite Lac-Phe in mice as well as in two independent human cohorts. In cell culture, metformin drives Lac-Phe biosynthesis via inhibition of complex I, increased glycolytic flux, and intracellular lactate mass action. Other biguanides and structurally distinct inhibitors of oxidative phosphorylation also increase Lac-Phe levels in vitro. Genetic ablation of CNDP2, the principal biosynthetic enzyme for Lac-Phe, in mice renders animals resistant to metformin's anorexigenic and anti-obesity effects. Mediation analyses also support a role for Lac-Phe in metformin's effect on body mass index in humans. These data establish the CNDP2/Lac-Phe pathway as a critical mediator of the effects of metformin on energy balance.

A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically-determined protein-protein networks.

Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.

Identification of circulating proteins associated with general cognitive function among middle-aged and older adults.

Identifying circulating proteins associated with cognitive function may point to biomarkers and molecular process of cognitive impairment. Few studies have investigated the association between circulating proteins and cognitive function. We identify 246 protein measures quantified by the SomaScan assay as associated with cognitive function (p < 4.9E-5, n up to 7289). Of these, 45 were replicated using SomaScan data, and three were replicated using Olink data at Bonferroni-corrected significance. Enrichment analysis linked the proteins associated with general cognitive function to cell signaling pathways and synapse architecture. Mendelian randomization analysis implicated higher levels of NECTIN2, a protein mediating viral entry into neuronal cells, with higher Alzheimer's disease (AD) risk (p = 2.5E-26). Levels of 14 other protein measures were implicated as consequences of AD susceptibility (p < 2.0E-4). Proteins implicated as causes or consequences of AD susceptibility may provide new insight into the potential relationship between immunity and AD susceptibility as well as potential therapeutic targets.

The functional impact of rare variation across the regulatory cascade.

Each human genome has tens of thousands of rare genetic variants; however, identifying impactful rare variants remains a major challenge. We demonstrate how use of personal multi-omics can enable identification of impactful rare variants by using the Multi-Ethnic Study of Atherosclerosis, which included several hundred individuals, with whole-genome sequencing, transcriptomes, methylomes, and proteomes collected across two time points, 10 years apart. We evaluated each multi-omics phenotype's ability to separately and jointly inform functional rare variation. By combining expression and protein data, we observed rare stop variants 62 times and rare frameshift variants 216 times as frequently as controls, compared to 13-27 times as frequently for expression or protein effects alone. We extended a Bayesian hierarchical model, "Watershed," to prioritize specific rare variants underlying multi-omics signals across the regulatory cascade. With this approach, we identified rare variants that exhibited large effect sizes on multiple complex traits including height, schizophrenia, and Alzheimer's disease.