Minor Allele Count Research Articles

Characterization of fine geographic scale population genetics in sugar kelp (Saccharina latissima) using genome-wide markers

BackgroundKelps are not only ecologically important, being primary producers and habitat forming species, they also hold substantial economic potential. Expansion of the kelp cultivation industry raises the interest for genetic improvement of kelp for cultivation, as well as concerns about genetic introgression from cultivated to wild populations. Thus, increased understanding of population genetics in natural kelp populations is crucial. Genotyping-by-sequencing (GBS) is a powerful tool for studying population genetics. Here, using Saccharina latissima (sugar kelp) as our study species, we characterize the population genetics at a fine geographic scale, while also investigating the influence of marker type (biallelic SNPs versus multi-allelic short read-backed haplotypes) and minor allele count (MAC) thresholds on estimated population genetic metrics.ResultsWe examined 150 sporophytes from 10 locations within a small area in Mid-Norway. Employing GBS, we detected 20,710 bi-allelic SNPs and 42,264 haplotype alleles at 20,297 high quality GBS loci. We used both marker types as well as two MAC filtering thresholds (3 and 15) in the analyses. Overall, higher genetic diversity, more outbreeding and stronger substructure was estimated using haplotypes compared to SNPs, and with MAC 15 compared to MAC 3. The population displayed high genetic diversity (HE ranging from 0.18–0.37) and significant outbreeding (FIS ≤ − 0.076). Construction of a genomic relationship matrix, however, revealed a few close relatives within sampling locations. The connectivity between sampling locations was high (FST ≤ 0.09), but subtle, yet significant, genetic substructure was detected, even between sampling locations separated by less than 2 km. Isolation-by-distance was significant and explained 15% of the genetic variation, while incorporation of predicted currents in an “isolation-by-oceanography” model explained a larger proportion (~ 27%).ConclusionThe studied population is diverse, significantly outbred and exhibits high connectivity, partly due to local currents. The use of genome-wide markers combined with permutation testing provides high statistical power to detect subtle population substructure and inbreeding or outbreeding. Short haplotypes extracted from GBS data and removal of rare alleles enhances the resolution. Careful consideration of marker type and filtering thresholds is crucial when comparing independent studies, as they profoundly influence numerical estimates of population genetic metrics.

Combining evidence from human genetic and functional screens to identify pathways altering obesity and fat distribution.

Overall adiposity and body fat distribution are heritable traits associated with altered risk of cardiometabolic disease and mortality. Performing rare variant (minor allele frequency<1%) association testing using exome-sequencing data from 402,375 participants in the UK Biobank (UKB) for nine overall and tissue-specific fat distribution traits, we identified 19 genes where putatively damaging rare variation associated with at least one trait (Bonferroni-adjusted P<1.58×10-7) and 52 additional genes at FDR≤1% (P≤4.37×10-5). These 71 genes exhibited higher (P=3.58×10-18) common variant prioritisation scores than genes not significantly enriched for rare putatively damaging variation, with evidence of monotonic allelic series (dose-response relationships) among ultra-rare variants (minor allele count≤10) in 22 genes. Five of the 71 genes have cognate protein UKB Olink data available; all five associated (P<3.80×10-6) with three or more analysed traits. Combining rare and common variation evidence, allelic series and proteomics, we selected 17 genes for CRISPR knockout in human white adipose tissue cell lines. In three previously uncharacterised target genes, knockout increased (two-sided t-test P<0.05) lipid accumulation, a cellular phenotype relevant for fat mass traits, compared to Cas9-empty negative controls: COL5A3 (fold change [FC]=1.72, P=0.0028), EXOC7 (FC=1.35, P=0.0096), and TRIP10 (FC=1.39, P=0.0157); furthermore, knockout of SLTM resulted in reduced lipid accumulation (FC=0.51, P=1.91×10-4). Integrating across population-based genetic and in vitro functional evidence, we highlight therapeutic avenues for altering obesity and body fat distribution by modulating lipid accumulation.

Abstract 6148: Multiple new Ewing sarcoma susceptibility loci expand knowledge of germline genetic etiology and nominate mechanisms of risk

Abstract Ewing sarcoma (EwS) is a rare and aggressive pediatric cancer with peak incidence in the second decade of life. EwS occurs primarily in children of European ancestry suggesting a genetic component to susceptibility. Prior investigations identified six susceptibility loci associated with EwS, with evidence for additional signals not reaching the commonly accepted threshold for genome-wide significance (i.e., p&amp;lt;5×10−8). At least two of these loci demonstrate evidence of tagging variation in length of nearby GGAA microsatellites, which alter binding of the pathognomonic EWSR1::FLI1 fusion resulting in downstream dysregulation of target genes promoting sarcomagenesis. To identify additional susceptibility loci, we performed the largest genome-wide association study (GWAS) to date consisting of 1,640 EwS cases and 8,457 cancer-free individuals of European ancestry from 8 studies and matched by principal components. Genotype imputation was carried out by study/array using TOPMed data as the reference and each set was analyzed using PLINK 1.9 adjusting for significant principal components. Variants were included in each study if minor allele count was greater than five in each set of cases. Individual study results were combined using fixed effects meta-analysis in Metasoft with variants demonstrating evidence for heterogeneity excluded.For previously reported EwS loci (i.e., 1p36.22, 6p25.1, 10q21.3, 15q15.1, 20p11.22 and 20p11.23), odds ratios (OR) remained high for GWAS (OR=1.5-2.4) and the -log10 p-values grew by several orders of magnitude, providing strong evidence for replication in the additional 907 EwS cases and 7,111 cancer-free controls. Our analysis identified five novel loci reaching genome-wide significance (P-valuemeta&amp;lt; 5×10−8) at 5q32, 7q32.3, 8q24.2, 13q32.3, and 17q23.2. Risk allele frequency of newly identified loci ranged from 0.001 to 0.75with estimated ORs ranging from 1.31-4.30. eQTL analyses nominated nearby biologically plausible candidate genes for future functional investigation including LARS1, a gene implicated in osteosarcoma and skeletal muscle dysgenesis, at the 5q32 locus and COX5BP6, a gene implicated in age at menarche and testosterone levels, at 13q32.3.Our results add to evidence supporting a strong inherited genetic component to EwS risk and particularly a genetic architecture harboring a substantial number of common variants with moderate effect. Ongoing work is focusing on enrichment analyses of GGAA microsatellite repeat sequences in identified risk loci to search for evidence for germline-somatic interactions with EWSR1::FLI1. Citation Format: Aubrey K. Hubbard, Weiyin Zhou, Carrie Boyce, Javed Khan, Melissa M. Hudson, Kirsten K. Ness, Zhaoming Wang, Katherine A. Janeway, Philip J. Lupo, Lindsay M. Morton, Stephen J. Chanock, Thomas G. Grünewald, Olivier Delattre, Mitchell J. Machiela, Ewing Sarcoma Germline Genetics Group. Multiple new Ewing sarcoma susceptibility loci expand knowledge of germline genetic etiology and nominate mechanisms of risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6148.

Detecting Protective Rare Variants for Alzheimer’s Disease from Whole‐Genome Sequencing in the Amish

AbstractBackgroundA shift in focus from risk to resilience for Alzheimer’s disease (AD) encourages efforts to uncover novel AD biological mechanisms. Rare variants identified through whole genome sequencing (WGS) may represent an important and understudied component of complex trait genetics. While population‐based studies are powered to discover associations with common genetic variants, founder populations are better powered for discovery of previously unknown rare alleles that have risen to higher frequency due to genetic drift.MethodWe examined WGS data from the Mid‐Western Amish population in a genome‐wide search for rare coding variants shared only among cognitively‐unimpaired (CU) individuals. The cognitive status of each individual was assigned via consensus review of medical history and neuropsychological testing. Allele frequencies were calculated across all samples and for CU and cognitively‐impaired (CI) groups separately. We defined rare variants as having an allele frequency &lt;0.05 across all samples. Variants with a minor allele count (MAC)&gt;10 in the CU group, and 0 in the CI group were annotated to determine likely loss of function.ResultAfter extensive QC, 1,048 samples were available to estimate overall allele frequency. Allele frequencies of rare variants (n = 11,854,817) within 634 CU (mean age = 81.53±6.10, 60% female) and within 184 CI (mean age = 84.77±6.60, 62% female) individuals were compared and 51,616 variants with MAC &gt;10 were found only in CU. There were 316 unique coding variants (288 missense, 4 inframe_insertion, 6 inframe_deletion, 11 frameshift, 4 stop_gained, 3 splice_donor) and 180 synonymous variants located within 425 unique genes. Among them, 7 missense variants and 7 synonymous variants had MAC &gt;20 and the remaining variants had MAC of 11‐20. The mean allele frequency of the 7 missense variants was 0.0038 in TOPMed compared to 0.0154 in our data. Two synonymous variants were located within proposed AD genes (NYAP1 and ZNF423). Additionally, several untranslated region or nonsense‐mediated decay transcript variants existed within 26 known AD gene regions, among which 8 of them are reported to harbor protective variants for AD.ConclusionNumerous rare variants potentially impacting gene function were found only in CU individuals, providing a rich resource for further investigation of genes that may provide protection from cognitive impairment.

Fast multiple-trait genome-wide association analysis for correlated longitudinal measurements

Large-scale longitudinal biobank data can be leveraged to identify genetic variation contributing to human diseases progression and traits trajectories. While methods for genome-wide association studies (GWAS) of multiple correlated traits have been proposed, an efficient multiple-trait approach to model longitudinal phenotypes is not currently available. We developed GAMUT, a genome-wide association approach for multiple longitudinal traits. GAMUT employs a mixed-effects model to fit longitudinal outcomes where a fast algorithm for inversion by recursive partitioning of the random effects submatrix is introduced. To evaluate performance of the algorithms introduced and assess their statistical power and type I error, stochastic simulation was conducted. Consistent with our expectation, power was greater for cross-sectional (CS) than longitudinal (LT) effects, particularly with a diminishing LT/CS ratio. With a minimum minor allele count of 3 within genotype by time categories, observed type I error was roughly equal to theoretical genome-wide significance. Additionally, 28 blood-based biomarkers measured at 2 time points on participants of the UK Biobank were used to compare GAMUT against single-trait standard and longitudinal GWAS (including rate of change). Across all biomarkers, we observed 539 (CS) and 248 (LT) significant independent variants for the GAMUT method, and 513 (CS) and 30 (LT) for single-trait longitudinal GWAS, respectively. Only 37 variants were identified by modeling rates of change using standard GWAS.

Reference Genome Choice and Filtering Thresholds Jointly Influence Phylogenomic Analyses.

Molecular phylogenies are a cornerstone of modern comparative biology and are commonly employed to investigate a range of biological phenomena, such as diversification rates, patterns in trait evolution, biogeography, and community assembly. Recent work has demonstrated that significant biases may be introduced into downstream phylogenetic analyses from processing genomic data; however, it remains unclear whether there are interactions among bioinformatic parameters or biases introduced through the choice of reference genome for sequence alignment and variant calling. We address these knowledge gaps by employing a combination of simulated and empirical data sets to investigate the extent to which the choice of reference genome in upstream bioinformatic processing of genomic data influences phylogenetic inference, as well as the way that reference genome choice interacts with bioinformatic filtering choices and phylogenetic inference method. We demonstrate that more stringent minor allele filters bias inferred trees away from the true species tree topology, and that these biased trees tend to be more imbalanced and have a higher center of gravity than the true trees. We find the greatest topological accuracy when filtering sites for minor allele count (MAC) >3-4 in our 51-taxa data sets, while tree center of gravity was closest to the true value when filtering for sites with MAC >1-2. In contrast, filtering for missing data increased accuracy in the inferred topologies; however, this effect was small in comparison to the effect of minor allele filters and may be undesirable due to a subsequent mutation spectrum distortion. The bias introduced by these filters differs based on the reference genome used in short read alignment, providing further support that choosing a reference genome for alignment is an important bioinformatic decision with implications for downstream analyses. These results demonstrate that attributes of the study system and dataset (and their interaction) add important nuance for how best to assemble and filter short-read genomic data for phylogenetic inference.

Variants near X‐Chromosome Genes NLGN4X and PTCHD1 are Significantly Associated with Alzheimer’s Disease Risk

AbstractBackgroundGenome‐wide association studies (GWAS) for AD have identified numerous associated loci but have been focused only on the autosomes. We sought to identify novel AD‐associated genes on X‐Chromosome (X‐Chr).MethodWe evaluated the association of AD with X‐Chr variants in GWAS datasets assembled by the Alzheimer Disease Genetics Consortium including 26,322 non‐Hispanic White (NHW) individuals using logistic regression models with covariates for age, sex and principal components of ancestry. The number of independent SNPs in X‐Chr was calculated by linkage disequilibrium pruning yielding a study‐wide significance threshold of P&lt;7.58×10−7. Genes near SNPs surpassing this threshold were further evaluated by expression quantitative trait locus (eQTL) in the BRAINEAC database and differential gene expression analyses using RNA‐seq data obtained from autopsied brains contained (GEO: GSE44772 and GSE33000). We also tested association of AD with missense or splicing variants with minor allele count (MAC)≥10 in the same genes using GENESIS and whole exome sequencing (WES) data obtained by the Alzheimer Disease Sequencing Project (ADSP) for 11,172 NHWs.ResultWe identified novel associations with variants near NLGN4X (rs34056759; minor allele frequency [MAF] = 0.15, OR = 1.15, P = 5.14×10−7) and PTCHD1 (rs5970663; MAF = 0.30, OR = 1.13, P = 8.26×10−7). The rs5970663 risk allele C was significantly associated with increased expression of PTCHD1 in the medulla region, and PTCHD1 expression was significantly higher in AD cases than in controls in the prefrontal cortex (P&lt;2.1×10−8) and visual cortex (P&lt;2.3×10−4). Rs34056759 was not associated with NLGN4X expression, but NLGN4X expression was significantly lower in AD cases compared to controls in the prefrontal cortex (P&lt;8.7×10−7). A rare PTCHD1 variant (rs201933353; MAF = 0.001) was nominally associated with AD among 6,318 women (OR = 3.72, P = 0.06).ConclusionWe identified novel associations of AD with X‐Chr variants near NLGN4X and PTCHD1, loci that were previously associated with autism spectrum disorder. We plan to replicate, fine‐map, and annotate the candidate loci identified in this study using large whole genome sequencing ADSP datasets.

Saddlepoint approximations to score test statistics in logistic regression for analyzing genome-wide association studies.

We investigate saddlepoint approximations of tail probabilities of the score test statistic in logistic regression for genome-wide association studies. The inaccuracy in the normal approximation of the score test statistic increases with increasing imbalance in the response and with decreasing minor allele counts. Applying saddlepoint approximation methods greatly improve the accuracy, even far out in the tails of the distribution. By using exact results for a simple logistic regression model, as well as simulations for models with nuisance parameters, we compare double saddlepoint methods for computing two-sided -values and mid- -values. These methods are also compared to a recent single saddlepoint procedure. We investigate the methods further on data from UK Biobank with skin and soft tissue infections as phenotype, using both common and rare variants.

MEGA-ANALYSIS OF A CONSORTIUM OF FOUR CENTENARIAN STUDIES IDENTIFIES NOVEL EXTREME LONGEVITY VARIANTS

Abstract The meta-analysis of extreme longevity (EL) conducted in 2017 using a consortium of four longevity studies—the New England Centenarian Study (NECS), the Long Life Family Study (LLFS), the Southern Italian Centenarian Study (SICS), and the Longevity Gene Project (LGP)—confirmed previous associations with APOE alleles and identified additional candidate genes. The current study builds upon this work. Using an aggregated set of the four studies (mega-analysis), we sought to identify additional longevity variants. The current study includes 234 additional cases with a total of 2304 cases (median age=103, age range=[96, 119]), defined as living past the age at which less than 1% individuals from the 1900 - 1920 birth year cohorts survived and approximately 6,000 controls. Approximately 10 million genotyped and imputed SNPs that passed imputation quality score threshold of 0.7 and that had a minor allele count of 3 or greater were analyzed. We ran a mixed effects logistic model for EL adjusting for sex, top principal components, indicator for living in Denmark, indicator for living in Italy, and the genetic relationship matrix. The analysis identified 21 novel loci that are genome-wide significant, both common and rare, and these loci were not previously published. The genome-wide significant loci include genes such as ADGRL2 (p=6.46-15), HLA-DPA1 (p=1.06-8), GRK5 (p=2.01-8), TECTB (p=3.38-8), KCNQ1 (p=7.53-10), TEAD2 (p=9.53-10), and several intergenic regions. We are currently in the process of seeking replication of the top results in independent cohorts.

Whole genome sequence association analysis of Brain MRI measures

AbstractBackgroundGenome‐wide association studies (GWAS) of brain volumes have identified common genetic variants with modest effect sizes that lie mainly in non‐coding regions. We sought to identify low frequency and rare variants influencing brain volumes by performing association analyses using whole‐genome sequence data from the Trans‐Omics for Precision Medicine (TOPMed) Program.MethodWe analyzed up to 7,607 participants (57% women; 62% European ancestry, 21% African‐Americans, 15% Hispanic/Latino, 2% Chinese‐American), mean age of 60.5 (16.2), from eight TOPMed population‐ or family‐based studies (FHS, GENESTAR, CHS, GENOA, ARIC, CARDIA, MESA, and SAFS). We excluded participants with dementia, stroke, presence of large brain infarcts, tumor or low‐quality scans. We tested the association of hippocampal (HV), total brain (TBV), lateral ventricular (LVV) and intracranial (ICV) volumes to individual genetic variants with minor allele counts ≥ 15 using mixed‐effect linear regression models adjusted for age, age2, sex, study and the first 10 principal components. Models for HV, TBV and log(LVV) were adjusted for ICV. We accounted for relatedness using an empirical kinship matrix and trait variance variability by using a random effect for study.ResultWe detected one novel region with low frequency variants associated with HV (13q14, P = 5.8×10−9). The top 13q14 variant for HV (rs115674829) minor allele frequency (MAF) was 2% in our pooled sample but was more common in the pan‐African 1000 Genomes population (MAF = 14%). This variant lies in LINC00598 at 237kb from FOXO1, a member of the forkhead family of transcription factors that has been linked to Alzheimer’s Disease. Additionally, we detected new suggestive associations (P≤10−7) for TBV (16p11) and LVV (1q25, 2q22, 3q13, 5q14, and 10q23), including common variants. Finally, we confirmed the association of common variants in GWAS loci for all traits.ConclusionOur whole genome sequence analyses revealed intriguing new loci of low‐frequency and common variants, and replicated loci previously associated with brain volumes. Future work will include ancestry‐specific and conditional analyses, as well as gene‐based and scan tests.Supported by: AG058589, AG052409, AG054076, NO1‐HC‐25195, HHSN268201500001I and 75N92019D00031, R01HL131136, P30 AG066546, and K99AG066849.

Identification of Genetic Variants and Serum Metabolites Associated with Blood‐derived Mitochondrial DNA Copy Number

AbstractBackgroundMitochondrial DNA Copy Number (mtDNA‐CN) can be used to estimate mitochondrial function and it varies across tissues and cell types. Blood‐derived mtDNA‐CN has been studied in aging‐related diseases including Alzheimer’s Disease (AD). However, little is known about the genetic contribution to variation of blood‐derived mtDNA‐CN and how this variation affects the level of serum metabolites.MethodWe developed a fast computational pipeline to accurately estimate mtDNA‐CN using whole genome sequence data from blood samples from European ancestry (EA, 2,885 AD cases and 2,777 controls), African American (AA, 1,118 AD cases and 1,725 controls), and Caribbean Hispanic (CH, 1,022 AD cases and 1,949 controls) participants of the Alzheimer’s Disease Sequencing Project (ADSP). In the combined sample and within each population group. We tested association of blood‐derived mtDNA‐CN with 17,569,705 variants (minor allele count≥20) genome‐wide using a linear mixed effect model including covariates for age, sex, sequencing center, PCR, AD status, polygenic risk score of blood cell count, and principal components of ancestry. We also tested the associations of mtDNA‐CN and levels of 175 serum metabolites in 1,521 subjects from Alzheimer’s Disease Neuroimaging Initiative.ResultIn the total sample, we identified genome‐wide significant (GWS) associations with variants from 24 independent loci. The top‐ranked SNP (rs1455130415 in NDUFS8, (p=3.25x10‐42) was also GWS in EAs (p=3.96x10‐28) and AAs (p=2.20x10‐27). SNP rs997412864 (p=5.13x10‐9) in GCAT was found associated with mtDNA‐CN in EAs, but not in other groups. Association of SNP rs1237233197 (p=1.40x10‐8) in NDUFS7 was specific to AAs. Measurements of two long‐chain acylcarnitine, C14:2‐OH (p=4.91x10‐7) and C18:2 (p=1.81x10‐5), were negatively associated with mtDNA‐CN after Bonferroni correction (P&lt;2.9x10‐4). Ornithine, a non‐proteinogenic amino acid, was also negatively associated with mtDNA‐CN (p=2.32x10‐4).ConclusionWe identified GWS association of blood‐derived mtDNA‐CN with a variant in a nuclear‐encoded mitochondrial gene, NDUFS8, which encodes a subunit of Complex I. In addition, mtDNA‐CN was significantly associated with two acylcarnitine metabolites and ornithine whose levels were previously reported to be decreased in blood of AD patients. These results provide more insight about the role of mitochondrial function in AD pathogenesis and suggest that blood‐derived mtDNA‐CN may be a useful biomarker for AD.

Gene‐based polygenic score analysis identifies novel immune genes with deleterious variants that associate with Alzheimer’s disease

AbstractBackgroundIn the Alzheimer’s disease sequencing project (ADSP) whole exome dataset, only the well‐known TREM2.pR47H variant shows genome‐wide significance by conventional single variant analysis. To identify novel AD genes related to TREM2, we used gene‐based polygenic score analysis (PGSA) to evaluate an immune, temporal cortical co‐expression network with 229 genes including TREM2.MethodThe most recent whole exome variant call files from the ADSP (NG00067.v7) were subjected to stringent quality control. Post‐QC samples were divided into discovery (4174 samples sequenced at Broad), test (3299 samples sequenced at WashU), and follow‐up (2273 samples sequenced at Baylor) sets. The pruned variants (r2 &lt; 0.2) with a minor allele count over 20 in each gene were analyzed by Broad/WashU PGSA thereby obtaining P‐values (gPbr.wa) for each gene in WashU samples. To assess significance in independent Baylor samples, cumulative Broad/Baylor PGSA was performed using a novel approach in which variants were stratified by both gene (gPbr.wa) and variant (Broad.P).ResultAfter excluding TREM2, the five variants with gPbr.wa ≤ 0.08 and Broad.P ≤ 0.03 showed significant association in Broad/Baylor PGSA. One of these variants showed no evidence of association with AD in the combined dataset. Polygenic scores for the other four variants, which were in three genes, showed significant association in Baylor samples, and significant, essentially identical association in WashU samples. Polygenic scores for nine additional variants in these genes (0.03&gt; Broad.P ≤ 0.13) also showed significant, essentially identical association in Baylor and WashU samples. The association of these 13 variants with AD was driven primarily by six deleterious, protein‐altering variants with minor allele frequencies less than 1%, but the other 7 variants also contributed.ConclusionUsing gene‐based polygenic score analysis to analyze an immune co‐expression network, we identify three novel immune genes with actionable nonsynonymous and stopgain variants that show significant, replicable association with AD in the most recent release of the ADSP whole exome dataset.

Functional Annotations‐Informed Whole Genome Sequence Analysis Identifies Novel Rare Variants for AD in the Alzheimer’s Disease Sequencing Project

AbstractBackgroundIncorporating functional annotations improves power to identify rare variants (RV) in the analysis of whole genome sequencing (WGS) association studies. We incorporated Alzheimer’s Disease (AD)‐specific annotations based on partitioning heritability into the variant‐Set Test for Association using Annotation information (STAAR‐O) framework to identify RVs associated with AD in the diverse sample of the Alzheimer’s Disease Sequencing Project (ADSP).MethodWe performed WGS association analyses in a sample of 4,074 individuals (1,668 AD cases; 2,406 controls) sequenced as part of the ADSP Discovery Extension Phase. We first estimated heritability of all single nucleotide variants in functional annotation categories using the GCTA tool embedded in FunSPU. For each annotation category, a global weight was derived based on the partitioned AD heritability. Among weighted functional scores, we selected the top 12 to leverage the most informative functional annotations for incorporation into the STAAR‐O test.2 We performed agnostic region‐based association analysis using sliding windows, defined as 2kb in length with a skip length of 1kb. Association tests were performed with RV (minor allele frequency &lt;1%), adjusting for sex, sequencing center, platform, study, 4 principal components, and a genetic relatedness matrix. Replication of significant associations was carried out in an independent sample of 10,083 individuals (5,717 AD cases, 4,366 controls) sequenced as part of the ADSP Follow‐Up Study and using the same analytical models.ResultOut of 2.65 million 2‐kb overlapping windows with a total minor allele count &gt;10, two non‐consecutive windows on chromosome 17 were associated with AD (P&lt;5×10−8) (Figures). Both windows associations were replicated in the independent sample (P = 0.003 and 0.016). The top variant of one significant window was rs534148850 (MAF = 0.0005, P = 5.55×10−9) located downstream of PLEKHM1P1, a pseudogene, and MIR4315‐2, a microRNA with predicted targets enriched in apoptosis pathways. The top variant of the other window was rs532055552 (MAF = 0.005, P = 6.20×10−9) located downstream of CEP112, a coiled domain‐containing protein involved in the regulation of gamma‐aminobutyric acid A receptor surface expression.ConclusionIncorporating AD‐relevant functional annotations to a powerful RV association framework, we discovered and replicated two novel genetic regions harboring RV associated with AD.

Genome-wide discovery for diabetes-dependent triglycerides-associated loci.

We aimed to discover loci associated with triglyceride (TG) levels in the context of type 2 diabetes (T2D). We conducted a genome-wide association study (GWAS) in 424,120 genotyped participants of the UK Biobank (UKB) with T2D status and TG levels. We stratified the cohort based on T2D status and conducted association analyses of TG levels for genetic variants with minor allele count (MAC) at least 20 in each stratum. Effect differences of genetic variants by T2D status were determined by Cochran's Q-test and we validated the significantly associated variants in the Mass General Brigham Biobank (MGBB). Among 21,176 T2D and 402,944 non-T2D samples from UKB, stratified GWAS identified 19 and 315 genomic risk loci significantly associated with TG levels, respectively. Only chr6p21.32 exhibited genome-wide significant heterogeneity (I2 = 98.4%; pheterogeneity = 2.1x10-15), with log(TG) effect estimates of -0.066 (95%CI: -0.082, -0.050) and 0.002 (95%CI: -0.002, 0.006) for T2D and non-T2D, respectively. The lead variant rs9274619:A (allele frequency 0.095) is located 2Kb upstream of the HLA-DQB1 gene, between HLA-DQB1 and HLA-DQA2 genes. We replicated this finding among 25,137 participants (6,951 T2D cases) of MGBB (pheterogeneity = 9.5x10-3). Phenome-wide interaction association analyses showed that the lead variant was strongly associated with a concomitant diagnosis of type 1 diabetes (T1D) as well as diabetes-associated complications. In conclusion, we identified an intergenic variant near HLA-DQB1/DQA2 significantly associates with decreased triglycerides only among those with T2D and highlights an immune overlap with T1D.

Efficient and accurate frailty model approach for genome-wide survival association analysis in large-scale biobanks

With decades of electronic health records linked to genetic data, large biobanks provide unprecedented opportunities for systematically understanding the genetics of the natural history of complex diseases. Genome-wide survival association analysis can identify genetic variants associated with ages of onset, disease progression and lifespan. We propose an efficient and accurate frailty model approach for genome-wide survival association analysis of censored time-to-event (TTE) phenotypes by accounting for both population structure and relatedness. Our method utilizes state-of-the-art optimization strategies to reduce the computational cost. The saddlepoint approximation is used to allow for analysis of heavily censored phenotypes (>90%) and low frequency variants (down to minor allele count 20). We demonstrate the performance of our method through extensive simulation studies and analysis of five TTE phenotypes, including lifespan, with heavy censoring rates (90.9% to 99.8%) on ~400,000 UK Biobank participants with white British ancestry and ~180,000 individuals in FinnGen. We further analyzed 871 TTE phenotypes in the UK Biobank and presented the genome-wide scale phenome-wide association results with the PheWeb browser.

Association of protein function-altering variants with cardiometabolic traits: the strong heart study

Clinical and biomarker phenotypic associations for carriers of protein function-altering variants may help to elucidate gene function and health effects in populations. We genotyped 1127 Strong Heart Family Study participants for protein function-altering single nucleotide variants (SNV) and indels selected from a low coverage whole exome sequencing of American Indians. We tested the association of each SNV/indel with 35 cardiometabolic traits. Among 1206 variants (average minor allele count = 20, range of 1 to 1064), ~ 43% were not present in publicly available repositories. We identified seven SNV-trait significant associations including a missense SNV at ABCA10 (rs779392624, p = 8 × 10–9) associated with fasting triglycerides, which gene product is involved in macrophage lipid homeostasis. Among non-diabetic individuals, missense SNVs at four genes were associated with fasting insulin adjusted for BMI (PHIL, chr6:79,650,711, p = 2.1 × 10–6; TRPM3, rs760461668, p = 5 × 10–8; SPTY2D1, rs756851199, p = 1.6 × 10–8; and TSPO, rs566547284, p = 2.4 × 10–6). PHIL encoded protein is involved in pancreatic β-cell proliferation and survival, and TRPM3 protein mediates calcium signaling in pancreatic β-cells in response to glucose. A genetic risk score combining increasing insulin risk alleles of these four genes was associated with 53% (95% confidence interval 1.09, 2.15) increased odds of incident diabetes and 83% (95% confidence interval 1.35, 2.48) increased odds of impaired fasting glucose at follow-up. Our study uncovered novel gene-trait associations through the study of protein-coding variants and demonstrates the advantages of association screenings targeting diverse and high-risk populations to study variants absent in publicly available repositories.

Whole Exome Sequence Study of Mild Cognitive Impairment in African and European Americans; the Atherosclerosis Risk in Communities‐Neurocognitive Study

AbstractBackgroundMild cognitive impairment (MCI) encompasses cognitive deficits beyond normal aging that minimally impact daily functioning. Uncovering the genetic architecture of MCI, which can progress to Alzheimer’s disease in some individuals, may facilitate the development of lifestyle and pharmacologic interventions to minimize cognitive impairment or prevent dementia. We conducted a whole exome sequence study of MCI in 1,144 African American (AA) and 3,358 European American (EA) participants aged 67‐90 years from the Atherosclerosis Risk in Communities‐Neurocognitive Study.MethodsFor both single‐variant and gene‐based tests, we employed seqMeta to perform race‐stratified analyses of functional (nonsynonymous, splicing, stopgain, stoploss, or frameshift) variants in each sex alone and both sexes combined. Models were adjusted for age, sex (except sex‐stratified models), field center, and population substructure (the first ten principal components). Logistic regression models were fit on autosomal single‐variants with minor allele frequency (MAF) ≥0.01 while SKAT‐O, T1 burden, and SKAT (beta weights and MAF ≤ 0.05) gene‐based tests were conducted. The significance and suggestive p‐value thresholds were 1.13E‐06 and 2.27E‐05 for single‐variant tests and 2.81E‐06 and 5.63E‐05 for gene‐based tests, respectively, after Bonferroni correction.ResultsThe analysis sample contained 993 MCI cases and 3,509 cognitively normal participants; Table 1 contains the count for each race and sex subgroup. One significant (p‐value=1.06E‐7) single‐variant association (chr6:51712759:T:C in PKHD1) was detected in AA males (Figure 1). This variant had MAF=0.025 in AA males but was monomorphic in EA males. Four significant gene‐based associations with minor allele counts (MAC) ≥ 10 were discovered: CDC27 in AA females (SKAT‐O p‐value=6.63E‐07), C19orf18 in AA males (SKAT‐O p‐value=1.26E‐07), SLC16A10 in EA males and females combined (SKAT p‐value=1.90E‐06), and ZNF804A in EA females (T1 p‐value=2.69E‐07). Twenty‐three suggestive single‐variant and gene‐based associations with MAC ≥ 10 were identified (Figure 2).ConclusionsMCI‐associated genes have diverse biological functions including cell division, sodium‐independent transportation of amino acids, and zinc finger binding. Our findings imply that the genetic underpinnings of MCI may differ by race and sex. External replication of our findings, as well as investigations using large samples in consortia, will provide insight into the pervasiveness of sex‐specific genetic effects in dementia‐related traits.

Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease.

Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants. Proteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics). We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure. Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.

Abstract 10660: Genome-Wide Scan Identifies Variants Increasing Triglycerides Only Among Diabetics

Introduction: Increased triglycerides (TG) frequently accompanies type 2 diabetes (T2D) mellitus and poor glycemic control. The extent to which genetics influences triglycerides differently in individuals with T2D is not well understood. Methods: We conducted a genome-wide association study (GWAS) of log(TG) stratified by T2D using imputed UKB genotypes with minor allele count&gt;20. We used linear regression model with a leave-one-out cross-validation using REGENIE adjusted for PC1-10, age, age 2 , gender, array-type, and race. We assessed the heterogeneity (I 2 ) between the effects of TG in T2D and non-T2D individuals. We sought replication in the Mass General Brigham Biobank (MGBB). Results: Among 21,176 T2D and 402,944 non-T2D samples, stratified GWAS identified 17 and 45 loci significantly associated with TG levels, respectively. Only one loci exhibited significant genome-wide heterogeneity (I 2 =98.4%; p heterogeneity =2x10 -15 ). The most significantly heterogenous variant was an intronic variant of the HLA-DQB1 gene, where the major allele (frequency 91.3%) was associated with increased TGs among those with T2D but not non-T2D (T2D group: beta=0.066, p-value=3.9x10 -15 ; non-T2D group: beta=-0.002, p-value=0.21). Among 25,136 participants (6,951 T2D cases) of MGBB, we replicated this finding (p heterogeneity =0.01). Conclusions: An intronic variant at HLA-DQB1 significantly associates with increased TGs only in those with T2D.

Abstract 9897: Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults

Introduction: Plasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Hypothesis: Whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry will increase power to identify novel genetic determinants. Methods: Proteomic profiling of 1,301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan®). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥ 5. Results were validated using an alternative, antibody-based, proteomic platform (Olink®) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study. Results: We identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8 х 10 -11 . These associations include 134 novel locus-protein relationships and an additional 205 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β = 0.61±0.05, p-value = 3.27 х 10 -30 ) and MMP-3 (β = -0.60±0.05, p = 1.67 х 10 -32 ), as well as a completely novel pleiotropic locus at the HPX gene, associated with nine proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1 associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β = 0.34±0.04, p = 1.34 х 10 -17 ) as well as an association between ATTR amyloidosis and RBP4 levels in community dwelling individuals without heart failure. Discussion: Taken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation and myocardial function.