Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation:discovering causal pathways

Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (β = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP.</p

Analysis of individual families implicates noncoding DNA variation and multiple biological pathways in Alzheimer’s disease risk

Background Late‐onset Alzheimer’s disease (AD) is a complex disorder with multiple genetic risk factors. Linkage and association analysis have mapped dozens of loci in pooled analysis of many pedigrees or large numbers of unrelated cases and controls. Identification of the underlying DNA risk variants in the regions of interest (ROIs) has been complicated by both the genetic heterogeneity and the cost, until recently, of comprehensive DNA sequencing in ROIs. The known loci also leave much heritability unexplained. Method We used the families in the AD Sequencing Project (ADSP) discovery family sample to identify variants of interest from whole genome sequences (WGS), and through the variants, genes implicated in risk. We used SNP‐based multipoint linkage analysis to identify ROIs with rare VOIs, carrying out analysis without trimming pedigrees. We pursued all ROIs with family‐specific lodmax scores >1.9, reducing the variants of interest by several filters. We carried out pedigree‐based genotype imputation from the available WGS data, followed by family‐based association analysis, filtered for low population minor allele frequency. We prioritized genes with a low false‐discovery rate for association of single‐cell transcription in brain with AD disease state (PMID:31209304), and genes with high expression in bulk brain (PMID: 24309898). Result We obtained 46 distinct ROIs representing lodmax1.9‐3.5 per ROI in each of 26 of the 110 ADSP discovery families analyzed. 29 ROIs further investigated in 16 of the families yielded 59 prioritized genes, with 1‐11 genes/ROI. Only 4 out of 321 variants that passed all filters in these genes were in exons, with minimal overlap with genes identified in AD GWASs. Only one ROI occurred in two families, with evidence for a shared‐haplotype between these families, implicating FBXO2 and FBXO44. Both genes are implicated in ubiquitination, while FBXO2 interacts with BACE1. Multiple pathways, both known and new, are implicated, including the ubiquitin‐proteasome system, neural development and maintenance, and mitochondrial functions. Conclusion This analysis underscores the evidence for extensive genetic heterogeneity and rare variants underlying AD risk, along with multiple potential mechanisms. The preponderance of prioritize non‐coding variants suggests alterations in gene regulation and/or expression as an aspect of AD genetic risk

Association of mitochondrial DNA copy number with brain MRI and cognitive function in the TOPMed Program

BackgroundMitochondria are the main energy source for normal neuronal functions. Mitochondrial DNA (mtDNA) copy number (CN), a measure of mtDNA levels in the cell, correlates with cellular energy generating capacity and metabolic status. Previous studies have observed a significant decrease of circulating cell‐free mtDNA content in the cerebrospinal fluid of patients with Alzheimer’s disease (AD). However, it is unknown whether mtDNA CN circulating in the blood is related to AD endophenotypes. We aimed to investigate the cross‐sectional association of mtDNA CN with MRI markers of abnormal brain aging and cognitive function.MethodWe included dementia‐free, multiethnic participants from seven population‐based cohorts with whole‐genome sequencing as part of the Trans‐Omics for Precision Medicine (TOPMed) program. The average mtDNA CN in whole blood was estimated as twice the ratio of the average coverage of mtDNA to the average coverage of the nuclear DNA using fastMitoCalc from mitoAnalyzer. Brain MRI markers included total brain volume, hippocampal volume, and white matter hyperintensities. General cognitive function was derived from at least three distinct cognitive domains using principal component analysis. We related mtDNA CN to AD endophenotypes assessed within 5 years of blood draw per cohort and further performed random‐effects or sample size‐weighted meta‐analyses. Models were adjusted for demographics and vascular risk factors.ResultHigher mtDNA CN was significantly associated with better general cognitive function (P‐values<0.05) in four cohorts after adjusting for age, sex, batch effect, self‐reported race/ethnicity, the time between blood draw and MRI/Cognitive evaluation, cohort‐specific variables, and education (Figure 1). Meta‐analysis across all cohorts confirmed and strengthened the significant association between mtDNA CN and general cognitive function (n=11,021, Beta=0.046, SE=0.01, P‐value=0.0002). Additional adjustment for diabetes, hypertension, hyperlipidemia, and obesity led to similar results (Beta=0.043, SE=0.01, P‐value=0.002). We observed no significant associations between mtDNA CN and brain MRI markers.ConclusionThis study suggests that higher mtDNA CN is cross‐sectionally associated with better general cognitive function in a large sample from diverse communities across the US, providing novel findings that support the role of mtDNA in healthy brain aging. Additional analyses are underway to relate mtDNA CN to AD endophenotypes prospectively and to incident dementia.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/171549/1/alz056243.pd

Genome‐wide meta‐analysis of late‐onset Alzheimer’s disease using rare variant imputation in 65,602 subjects identifies risk loci with roles in memory, neurodevelopment, and cardiometabolic traits: The international genomics of Alzheimer’s project (IGAP)

Background Recent meta‐analyses of genome‐wide association studies (GWAS) have identified ∼30 susceptibility LOAD loci in addition to APOE, however the majority are common variants (minor allele frequency (MAF)>0.02). We used the dense, high‐resolution Haplotype Reference Consortium (HRC) r1.1 reference panel (64,976 haplotypes/39,235,157 SNPs), which allows imputation of rare variants (MAF>0.0008), to impute 44 GWAS datasets of the IGAP consortia to identify novel rare variant, gene, and pathway associations. Method We imputed 25,192 cases and 40,410 controls to the HRC r1.1 panel using Minimac3 on the Michigan Imputation Server. Converting imputed genotype probabilities to minor allele dosage, we ran logistic regression using SNPTEST on individual variants with MAF > 0.01 (and using generalized linear mixed models in R with family‐based datasets), and performed a fixed‐effects, inverse‐variance‐weighted meta‐analysis using METAL. Variants with MAF ≤ 0.01 were meta‐analyzed using score‐based tests via SeqMeta/R. Both analyses adjusted for age‐at‐onset(cases)/age‐at‐exam(controls), sex, and principal components for population substructure. Gene‐based associations were done with SKAT‐O and burden testing, while pathway associations were examined using VEGAS2. Result Discovery analyses of ∼39.2M genotyped or imputed SNVs confirmed single variant associations in 26 of 30 known IGAP LOAD loci at suggestive levels of significance (P 0.01) in or near homologs of known AD loci, EPHA5 (rs17086136, OR[95% CI] = 1.23 [1.13,1.33], P = 6.36 × 10−7) and ADAM28 (rs10096379, OR[95% CI] = 0.86 [0.81,0.92], P = 3.02 × 10−6); in/near neuronal development genes including DAB1 (neuronal migration; 1:57700874:T:G, OR[95% CI] = 0.71 [0.62, 0.81], P = 6.94 × 10−7) and DCC (axon guidance; rs2054289, OR[95% CI] = 0.71 [0.62, 0.83], P = 6.69 × 10−6); and in/near genes involved in cardiometabolic traits including THADA (type 2 diabetes; rs77101426, OR[95% CI] = 0.89 [0.85, 0.95], P = 2.37 × 10−6). Several known AD loci demonstrated novel rare variant associations with genome‐wide significance, including CR1, PICALM, and the MS4A region (Figure 2), and novel rare variant associations were observed in or near genes involved in memory and cognitive function, including HS3ST4 and DBX1. Independent replication in external datasets including the UK Biobank is on‐going. Conclusion Several novel LOAD candidate loci, including those with prior associations with neurodevelopment and cardiometabolic traits, were identified using high‐quality imputation of rare and low‐frequency variants in IGAP

A meta-analysis of genome-wide association studies identifies new genetic loci associated with all-cause and vascular dementia

BACKGROUND: Dementia is multifactorial with Alzheimer (AD) and vascular (VaD) pathologies making the largest contributions. There have been over 40 genetic loci associated with AD but genome-wide associations (GWA) underlying VaD remain incompletely identified. The proportion of VaD differs across studies based on study-specific definitions. We hypothesize that common forms of dementia (AD, VaD) will share genetic risk factors. We conducted the largest GWAS to date of VaD and examined the genetic overlap with "all-cause dementia" (ACD). METHOD: A total of 293,544 participants from 9 population-based CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) cohorts, 2 national case-control consortia (ADGC, MEMENTO) and the UKBB contributed 23,986 and 2,935 cases of ACD and VaD, respectively. We ran study-specific analyses adjusting for age, sex, and population structure and meta-analyzed summary statistics using the sample size weighted method implemented in METAL, followed by conditional analyses, fine-mapping and bioinformatic exploration of loci. RESULT: Genome-wide associations with VaD were identified at the APOE locus and at 5 additional loci. One locus has been previously associated with hippocampal volume, verbal memory and CSF amyloid levels (ASTN2); others were near genes associated with hypertension, diabetes and hyperlipidemia (Figures 1 and 2). In addition to previously identified AD loci, we identified novel variants associated with ACD. VaD-related loci also showed sub-threshold associations with ACD that were congruent in direction of effect, thus suggesting additional biological targets underlying ACD. We will additionally present results of an ongoing multiethnic GWAS and insights from pathway analyses and bioinformatic parsing of the identified loci. CONCLUSION: Although VaD is the second most common cause of dementia, the identification of associated genetic loci has been hindered by the heterogeneity of its definition, which necessitates a large sample size to reach genome-wide significance. The newly identified loci could provide novel insights into the pathophysiological mechanisms of dementia and point to new prevention and treatment strategies

Understanding the complex genetic architecture connecting rheumatoid arthritis, osteoporosis and inflammation: discovering causal pathways

Rheumatoid arthritis (RA) and osteoporosis (OP) are two comorbid complex inflammatory conditions with evidence of shared genetic background and causal relationships. We aimed to clarify the genetic architecture underlying RA and various OP phenotypes while additionally considering an inflammatory component, C-reactive protein (CRP). Genome-wide association study summary statistics were acquired from the GEnetic Factors for OSteoporosis Consortium, Cohorts for Heart and Aging Research Consortium and UK Biobank. Mendelian randomization (MR) was used to detect the presence of causal relationships. Colocalization analysis was performed to determine shared genetic variants between CRP and OP phenotypes. Analysis of pleiotropy between traits owing to shared causal single nucleotide polymorphisms (SNPs) was performed using PL eiotropic A nalysis under CO mposite null hypothesis (PLACO). MR analysis was suggestive of horizontal pleiotropy between RA and OP traits. RA was a significant causal risk factor for CRP (β = 0.027, 95% confidence interval = 0.016-0.038). There was no evidence of CRP→OP causal relationship, but horizontal pleiotropy was apparent. Colocalization established shared genomic regions between CRP and OP, including GCKR and SERPINA1 genes. Pleiotropy arising from shared causal SNPs revealed through the colocalization analysis was all confirmed by PLACO. These genes were found to be involved in the same molecular function 'protein binding' (GO:0005515) associated with RA, OP and CRP. We identified three major components explaining the epidemiological relationship among RA, OP and inflammation: (1) Pleiotropy explains a portion of the shared genetic relationship between RA and OP, albeit polygenically; (2) RA contributes to CRP elevation and (3) CRP, which is influenced by RA, demonstrated pleiotropy with OP

Novel Loci Associated With PR Interval in a Genome-Wide Association Study of 10 African American Cohorts

Background-The PR interval, as measured by the resting, standard 12-lead ECG, reflects the duration of atrial/atrioventricular nodal depolarization. Substantial evidence exists for a genetic contribution to PR, including genome-wide association studies that have identified common genetic variants at 9 loci influencing PR in populations of European and Asian descent. However, few studies have examined loci associated with PR in African Americans. Methods and Results-We present results from the largest genome-wide association study to date of PR in 13 415 adults of African descent from 10 cohorts. We tested for association between PR (ms) and approximate to 2.8 million genotyped and imputed single-nucleotide polymorphisms. Imputation was performed using HapMap 2 YRI and CEU panels. Study-specific results, adjusted for global ancestry and clinical correlates of PR, were meta-analyzed using the inverse variance method. Variation in genome-wide test statistic distributions was noted within studies (lambda range: 0.9-1.1), although not after genomic control correction was applied to the overall meta-analysis (lambda: 1.008). In addition to generalizing previously reported associations with MEIS1, SCN5A, ARHGAP24, CAV1, and TBX5 to African American populations at the genome-wide significance level (P<5.0x10(-8)), we also identified a novel locus: ITGA9, located in a region previously implicated in SCN5A expression. The 3p21 region harboring SCN5A also contained 2 additional independent secondary signals influencing PR (P<5.0x10-8). Conclusions-This study demonstrates the ability to map novel loci in African Americans as well as the generalizability of loci associated with PR across populations of African, European, and Asian descent. (Circ Cardiovasc Genet. 2012;5:639-646.