Distinct Genetic Architecture Research Articles

The interplay of sex and genotype in disease associations: a comprehensive network analysis in the UK Biobank

BackgroundDisease comorbidities and longer-term complications, arising from biologically related associations across phenotypes, can lead to increased risk of severe health outcomes. Given that many diseases exhibit sex-specific differences in their genetics, our objective was to determine whether genotype-by-sex (GxS) interactions similarly influence cross-phenotype associations. Through comparison of sex-stratified disease-disease networks (DDNs)—where nodes represent diseases and edges represent their relationships—we investigate sex differences in patterns of polygenicity and pleiotropy between diseases.ResultsUsing UK Biobank summary statistics, we built male- and female-specific DDNs for 103 diseases. This revealed that male and female diseasomes have similar topology and central diseases (e.g., hypertensive, chronic respiratory, and thyroid-based disorders), yet some phenotypes exhibit sex-specific influence in cross-phenotype associations. Multiple sclerosis and osteoarthritis are central only in the female DDN, while cardiometabolic diseases and skin cancer are more prominent in the male DDN. Edge comparison indicated similar shared genetics between the two graphs relative to a random model of disease association, though notable discrepancies in embedding distances and clustering patterns imply a more expansive genetic influence on multimorbidity risk for females than males. Analysis of pleiotropic contributions of two sexually-dimorphic single-nucleotide polymorphisms related to thyroid disorders further validated a distinct genetic architecture across sexes that influences associations, confirmed through examination of corresponding gene expression profiles from the GTEx Portal.ConclusionsOur analysis affirms the presence of GxS interactions in cross-phenotype associations, emphasizing the need to investigate the role of sex in disease onset and its importance in biomedical discovery and precision medicine research.

Common and Distinct Genetic Architecture of Blood Pressure in Relation to Coronary Artery and Abdominal Aortic Calcium.

Common and Distinct Genetic Architecture of Blood Pressure in Relation to Coronary Artery and Abdominal Aortic Calcium.

Recent Advances in Stroke Genetics-Unraveling the Complexity of Cerebral Infarction: A Brief Review.

Recent advances in stroke genetics have substantially enhanced our understanding of the complex genetic architecture underlying cerebral infarction and other stroke subtypes. As knowledge in this field expands, healthcare providers must remain informed about these latest developments. This review aims to provide a comprehensive overview of recent advances in stroke genetics, with a focus on cerebral infarction, and discuss their potential impact on patient care and future research directions. We reviewed recent literature about advances in stroke genetics, focusing on cerebral infarction, and discussed their potential impact on patient care and future research directions. Key developments include the identification of monogenic stroke syndromes, such as cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy, and cerebral autosomal recessive arteriopathy with subcortical infarcts and leukoencephalopathy caused by mutations in the NOTCH3 and HTRA1 genes, respectively. In addition, the role of RNF213 in moyamoya disease and other cerebrovascular disorders, particularly in East Asian populations, has been elucidated. The development of polygenic risk scores for assessing genetic predisposition to stroke has demonstrated the potential to improve risk prediction beyond traditional factors. Genetic studies have also elucidated the distinct genetic architecture of stroke subtypes, including large artery atherosclerosis, small vessel disease, and cardioembolic stroke. Furthermore, the investigation of epigenetic modifications influencing stroke risk and its outcomes has revealed new research avenues, while advancements in pharmacogenomics highlight the potential for personalized stroke treatment based on individual genetic profiles. These genetic discoveries have important clinical implications, including improved risk stratification, targeted prevention strategies, and the development of novel therapeutic approaches.

Genome-wide association study reveals shared and distinct genetic architecture of fatty acids and oxylipins in the Hispanic Community Health Study/Study of Latinos.

Bioactive fatty acid-derived oxylipin molecules play key roles mediating inflammation and oxidative stress. Circulating levels of fatty acids and oxylipins are influenced by environmental and genetic factors; characterizing the genetic architecture of bioactive lipids could yield new insights into underlying biology. We performed a genome-wide association study (GWAS) of 81 fatty acids and oxylipins in 11,584 Hispanic Community Health Study/Study of Latinos (HCHS/SOL) participants with genetic and lipidomic data measured at study baseline (58.6% female, mean age= 46.1 years (standard deviation 13.8)). Additionally, given the effects of central obesity on inflammation, we examined interactions with waist circumference using two-degree-of-freedom joint tests. Thirty-three of the 81 oxylipins and fatty acids were significantly heritable (heritability range: 0-32.7%). Forty (49.4%) oxylipins and fatty acids had at least one genome-wide significant (p<6.94E-11) variant resulting in 19 independent genetic loci. Six loci (lead variant minor allele frequency [MAF] range: 0.08-0.50), including desaturase-encoding FADS and OATP1B1 transporter protein-encoding SLCO1B1, exhibited associations with two or more fatty acids and oxylipins. At several of these loci, there was evidence of colocalization of the top variant across fatty acids and oxylipins. The remaining loci were only associated with one oxylipin or fatty acid and included several CYP loci. We also identified an additional rare variant (MAF= 0.002) near CARS2 in two-degree-of-freedom tests. Our analyses revealed shared and distinct genetic architecture underlying fatty acids and oxylipins, providing insights into genetic factors and motivating work to characterize these compounds and elucidate their roles in disease.

Systematic comparison of phenome-wide admixture mapping and genome-wide association in a diverse biobank.

Biobank-scale association studies that include Hispanic/Latino(a) (HL) and African American (AA) populations remain underrepresented, limiting the discovery of disease associated genetic factors in these groups. We present here a systematic comparison of phenome-wide admixture mapping (AM) and genome-wide association (GWAS) using data from the diverse Bio Me biobank in New York City. Our analysis highlights 77 genome-wide significant AM signals, 48 of which were not detected by GWAS, emphasizing the complementary nature of these two approaches. AM-tagged variants show significantly higher minor allele frequency and population differentiation (Fst) while GWAS demonstrated higher odds ratios, underscoring the distinct genetic architecture identified by each method. This study offers a comprehensive phenome-wide AM resource, demonstrating its utility in uncovering novel genetic associations in underrepresented populations, particularly for variants missed by traditional GWAS approaches.

Genomic structural equation modeling reveals latent phenotypes in the human cortex with distinct genetic architecture

Genetic contributions to human cortical structure manifest pervasive pleiotropy. This pleiotropy may be harnessed to identify unique genetically-informed parcellations of the cortex that are neurobiologically distinct from functional, cytoarchitectural, or other cortical parcellation schemes. We investigated genetic pleiotropy by applying genomic structural equation modeling (SEM) to map the genetic architecture of cortical surface area (SA) and cortical thickness (CT) for 34 brain regions recently reported in the ENIGMA cortical GWAS. Genomic SEM uses the empirical genetic covariance estimated from GWAS summary statistics with LD score regression (LDSC) to discover factors underlying genetic covariance, which we are denoting genetically informed brain networks (GIBNs). Genomic SEM can fit a multivariate GWAS from summary statistics for each of the GIBNs, which can subsequently be used for LD score regression (LDSC). We found the best-fitting model of cortical SA identified 6 GIBNs and CT identified 4 GIBNs, although sensitivity analyses indicated that other structures were plausible. The multivariate GWASs of the GIBNs identified 74 genome-wide significant (GWS) loci (p < 5 × 10−8), including many previously implicated in neuroimaging phenotypes, behavioral traits, and psychiatric conditions. LDSC of GIBN GWASs found that SA-derived GIBNs had a positive genetic correlation with bipolar disorder (BPD), and cannabis use disorder, indicating genetic predisposition to a larger SA in the specific GIBN is associated with greater genetic risk of these disorders. A negative genetic correlation was observed between attention deficit hyperactivity disorder (ADHD) and major depressive disorder (MDD). CT GIBNs displayed a negative genetic correlation with alcohol dependence. Even though we observed model instability in our application of genomic SEM to high-dimensional data, jointly modeling the genetic architecture of complex traits and investigating multivariate genetic links across neuroimaging phenotypes offers new insights into the genetics of cortical structure and relationships to psychopathology.

Cognitive processing speed and accuracy are intrinsically different in genetic architecture and brain phenotypes

Since the birth of cognitive science, researchers have used reaction time and accuracy to measure cognitive ability. Although recognition of these two measures is often based on empirical observations, the underlying consensus is that most cognitive behaviors may be along two fundamental dimensions: cognitive processing speed (CPS) and cognitive processing accuracy (CPA). In this study, we used genomic-wide association studies (GWAS) data from 14 cognitive traits to show the presence of those two factors and revealed the specific neurobiological basis underlying them. We identified that CPS and CPA had distinct brain phenotypes (e.g. white matter microstructure), neurobiological bases (e.g. postsynaptic membrane), and developmental periods (i.e. late infancy). Moreover, those two factors showed differential associations with other health-related traits such as screen exposure and sleep status, and a significant causal relationship with psychiatric disorders such as major depressive disorder and schizophrenia. Utilizing an independent cohort from the Adolescent Brain Cognitive Development (ABCD) study, we also uncovered the distinct contributions of those two factors on the cognitive development of young adolescents. These findings reveal two fundamental factors underlying various cognitive abilities, elucidate the distinct brain structural fingerprint and genetic architecture of CPS and CPA, and hint at the complex interrelationship between cognitive ability, lifestyle, and mental health.

Genomic insights into the shared and distinct genetic architecture of cognitive function and schizophrenia

Cognitive impairment is a major determinant of functional outcomes in schizophrenia, however, understanding of the biological mechanisms underpinning cognitive dysfunction in the disorder remains incomplete. Here, we apply Genomic Structural Equation Modelling to identify latent cognitive factors capturing genetic liabilities to 12 cognitive traits measured in the UK Biobank. We identified three broad factors that underly the genetic correlations between the cognitive tests. We explore the overlap between latent cognitive factors, schizophrenia, and schizophrenia symptom dimensions using a complementary set of statistical approaches, applied to data from the latest schizophrenia genome-wide association study (Ncase = 53,386, Ncontrol = 77,258) and the Thematically Organised Psychosis study (Ncase = 306, Ncontrol = 1060). Global genetic correlations showed a significant moderate negative genetic correlation between each cognitive factor and schizophrenia. Local genetic correlations implicated unique genomic regions underlying the overlap between schizophrenia and each cognitive factor. We found substantial polygenic overlap between each cognitive factor and schizophrenia and biological annotation of the shared loci implicated gene-sets related to neurodevelopment and neuronal function. Lastly, we show that the common genetic determinants of the latent cognitive factors are not predictive of schizophrenia symptoms in the Norwegian Thematically Organized Psychosis cohort. Overall, these findings inform our understanding of cognitive function in schizophrenia by demonstrating important differences in the shared genetic architecture of schizophrenia and cognitive abilities.

Genome-wide association study reveals shared and distinct genetic architecture underlying fatty acid and bioactive oxylipin metabolites in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).

Bioactive fatty acid-derived oxylipin molecules play key roles in mediating inflammation and oxidative stress, which underlie many chronic diseases. Circulating levels of fatty acids and oxylipins are influenced by both environmental and genetic factors; characterizing the genetic architecture of bioactive lipids could yield new insights into underlying biological pathways. Thus, we performed a genome wide association study (GWAS) of n=81 fatty acids and oxylipins in n=11,584 Hispanic Community Health Study/Study of Latinos (HCHS/SOL) participants with genetic and lipidomic data measured at study baseline (58.6% female, mean age = 46.1 years, standard deviation = 13.8 years). Additionally, given the effects of central obesity on inflammation, we examined interactions with waist circumference using two-degree-of-freedom joint tests. Heritability estimates ranged from 0% to 47.9%, and 48 of the 81oxylipins and fatty acids were significantly heritable. Moreover, 40 (49.4%) of the 81 oxylipins and fatty acids had at least one genome-wide significant (p< 6.94E-11) variant resulting in 19 independent genetic loci involved in fatty acid and oxylipin synthesis, as well as downstream pathways. Four loci (lead variant minor allele frequency [MAF] range: 0.08-0.50), including the desaturase-encoding FADS and the OATP1B1 transporter protein-encoding SLCO1B1, exhibited associations with four or more fatty acids and oxylipins. The majority of the 15 remaining loci (87.5%) (lead variant MAF range = 0.03-0.45, mean = 0.23) were only associated with one oxylipin or fatty acid, demonstrating evidence of distinct genetic effects. Finally, while most loci identified in two-degree-of-freedom tests were previously identified in our main effects analyses, we also identified an additional rare variant (MAF = 0.002) near CARS2, a locus previously implicated in inflammation. Our analyses revealed shared and distinct genetic architecture underlying fatty acids and oxylipins, providing insights into genetic factors and motivating future multi-omics work to characterize these compounds and elucidate their roles in disease pathways.

An early-onset specific polygenic risk score optimizes age-based risk estimate and stratification of prostate cancer: population-based cohort study

BackgroundEarly-onset prostate cancer (EOPC, ≤ 55 years) has a unique clinical entity harboring high genetic risk, but the majority of EOPC patients still substantial opportunity to be early-detected thus suffering an unfavorable prognosis. A refined understanding of age-based polygenic risk score (PRS) for prostate cancer (PCa) would be essential for personalized risk stratification.MethodsWe included 167,517 male participants [4882 cases including 205 EOPC and 4677 late-onset PCa (LOPC)] from UK Biobank. A General-, an EOPC- and an LOPC-PRS were derived from age-specific genome-wide association studies. Weighted Cox proportional hazard models were applied to estimate the risk of PCa associated with PRSs. The discriminatory capability of PRSs were validated using time-dependent receiver operating characteristic (ROC) curves with additional 4238 males from PLCO and TCGA. Phenome-wide association studies underlying Mendelian Randomization were conducted to discover EOPC linking phenotypes.ResultsThe 269-PRS calculated via well-established risk variants was more strongly associated with risk of EOPC [hazard ratio (HR) = 2.35, 95% confidence interval (CI) 1.99–2.78] than LOPC (HR = 1.95, 95% CI 1.89–2.01; I2 = 79%). EOPC-PRS was dramatically related to EOPC risk (HR = 4.70, 95% CI 3.98–5.54) but not to LOPC (HR = 0.98, 95% CI 0.96–1.01), while LOPC-PRS had similar risk estimates for EOPC and LOPC (I2 = 0%). Particularly, EOPC-PRS performed optimal discriminatory capability for EOPC (area under the ROC = 0.613). Among the phenomic factors to PCa deposited in the platform of ProAP (Prostate cancerAge-basedPheWAS; https://mulongdu.shinyapps.io/proap), EOPC was preferentially associated with PCa family history while LOPC was prone to environmental and lifestyles exposures.ConclusionsThis study comprehensively profiled the distinct genetic and phenotypic architecture of EOPC. The EOPC-PRS may optimize risk estimate of PCa in young males, particularly those without family history, thus providing guidance for precision population stratification.

Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population

IntroductionGenetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related...

Genetic architecture distinguishes tinnitus from hearing loss

Tinnitus is a heritable, highly prevalent auditory disorder treated by multiple medical specialties. Previous GWAS indicated high genetic correlations between tinnitus and hearing loss, with little indication of differentiating signals. We present a GWAS meta-analysis, triple previous sample sizes, and expand to non-European ancestries. GWAS in 596,905 Million Veteran Program subjects identified 39 tinnitus loci, and identified genes related to neuronal synapses and cochlear structural support. Applying state-of-the-art analytic tools, we confirm a large number of shared variants, but also a distinct genetic architecture of tinnitus, with higher polygenicity and large proportion of variants not shared with hearing difficulty. Tissue-expression analysis for tinnitus infers broad enrichment across most brain tissues, in contrast to hearing difficulty. Finally, tinnitus is not only correlated with hearing loss, but also with a spectrum of psychiatric disorders, providing potential new avenues for treatment. This study establishes tinnitus as a distinct disorder separate from hearing difficulties.

A genome‐wide association study of LATE‐NC (limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change) reveals a distinct genetic architecture

AbstractBackgroundLimbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) is the third leading cause of late‐life dementia. However, its pathophysiology remains largely unknown, and the relationship of LATE‐NC with Alzheimer’s disease (AD) pathology and frontotemporal lobar degeneration‐TDP (FTLD‐TDP) remains unclear. To address this knowledge gap, we performed a genome‐wide association study (GWAS) of LATE‐NC.MethodDeceased participants of European ancestry from the Religious Orders Study, the Rush Memory and Aging Project (ROSMAP, n = 1,379), and the Adult Changes in Thought study (ACT, n = 459) were included in our study. The primary phenotypes were LATE‐NC burden (a multi‐regional semi‐quantitative TDP‐43 composite, continuous) in ROSMAP, and the presence/absence of LATE‐NC (binary) in ACT, assessed with post‐mortem TDP‐43 immunohistochemistry. Quantitative amyloid‐β (Aβ) and paired helical filament tau (PHFtau) burden were also examined in ROSMAP. GWAS was performed using linear (ROSMAP) or logistic (ACT) additive models. We controlled age, sex, genotyping platforms, and the first three genotype principal components. Sample size‐weighted GWAS meta‐analysis (total n = 1,838) was performed by combining p‐values considering the direction of the association. Confounding and moderating effects of AD pathology on LATE‐NC risk variants were examined in ROSMAP.ResultWe observed two genome‐wide significant risk loci (p&lt;5.0×10−8) in APOE (ε4) and SHANK2 (s146617441G, allele frequency 0.021). In ROSMAP, APOE ε4 was associated with higher LATE‐NC burden after controlling for quantitative Aβ and PHFtau (beta = 0.27, p = 7.3×10−6), and the APOE ε4 – LATE‐NC association was present in the subgroup without detectable Aβ (n = 170, beta = 0.50, p = 0.025). rs146617441G was not directly associated with quantitative Aβ or tau. Instead, rs146617441G×Aβ interaction term was associated with higher LATE‐NC burden (beta = 0.25, p = 0.032), suggesting the synergy between Aβ‐dependent and LATE‐NC‐specific pathways in LATE‐NC pathogenesis. Three additional loci reached a pre‐specified suggestive p‐value threshold (p&lt;1.0×10−6; CMTM7 [rs56284874G], RNF145 [rs111653954T], and CACNA2D3 [rs71303704C]). A previously reported FTLD‐TDP risk locus in TMEM106B (rs1990622A) showed a weaker positive association with LATE‐NC (meta‐analysis p = 9.6×10−4).ConclusionOur GWAS revealed LATE‐NC‐specific risk loci (SHANK2 and other suggestive loci). The unique genetic architecture of LATE‐NC further supports the distinction between LATE‐NC and FTLD‐TDP, and the AD‐independent effect of APOE ε4 on LATE‐NC highlights the pleiotropic role of APOE in neurodegeneration.

OR20-02 Trans-Ethnic Analysis Of PCOS Subtype Genomewide Association Signals Reveals 3 Shared Subtype-Specific Loci

Abstract Disclosure: K. Brewer: None. R. Sisk: None. H. Lee: None. L.M. Moolhuijsen: None. K. van der Ham: None. Y. Louwers: None. J.A. Visser: None. M. Dapas: None. S. Franks: None. J.S. Laven: None. C. Li: None. A.E. Dunaif: None. The phenotypic variation observed in PCOS is suggestive of underlying genetic heterogeneity, but a recent meta-analysis of European ancestry (EA) PCOS cases found that the genetic architecture of PCOS defined by NIH and Rotterdam diagnostic criteria was similar, suggesting that these criteria do not identify biologically distinct disease phenotypes. Using Hierarchical Clustering (HC) in EA NIH PCOS cases, we have identified discrete, stable PCOS subtypes, which we called reproductive and metabolic (Dapas. PLoS Med, 2020); cases that did not cluster were designated as “background”. These subtypes appeared to capture biologically meaningful differences because they were associated with distinct genomewide significant loci. We were unable to replicate 4 of 6 loci since the lead SNPs were neither genotyped nor imputed on the array used for replication, the Metabochip custom array for cardiometabolic traits with additional PCOS-relevant SNPs. Here, we report an updated EA genomewide association study (GWAS) meta-analysis with additional EA NIH PCOS cases, and a trans-ethnic meta-analysis including a Korean ancestry (KA) NIH PCOS cohort (Lee. Hum Reprod, 2015). HC was applied to cases in both cohorts to identify PCOS subtypes. The EA discovery cohort, 620 cases and 2951 controls, was genotyped with the Illumina OmniExpress array. The replication EA cohort, 371 cases and 926 controls, was genotyped with the Metabochip. The KA cohort, 417 cases and 926 controls, was genotyped with the HumanOmni1-Quad v1 array. The imputation of previously reported genotype data was updated using the larger, more deeply sequenced TOPMed (R2) imputation panel. Nine loci were genomewide significant in the EA meta-analysis: 5 novel loci (reproductive subtype); 2 loci (metabolic subtype), including c9orf3; 2 loci (background subtype), including FSHB/ARL14P. Five of 6 other lead SNPs in the original analysis remained nominally significant. Three loci were significant in the trans-ethnic meta-analysis: a novel locus on chr 3, EPHA6, a receptor tyrosine kinase that binds promiscuously GPI-anchored ephrin-A family ligands (rs140766105, p=1.08 x 10-8, reproductive subtype); a previously identified GWAS locus on chr 9, c9orf3 (AOPEP), an aminopeptidase that catalyzes the hydrolysis of amino acid residues from the N-terminus of peptides (rs10761370, p=4.12 x 10-9, metabolic subtype); a previously identified GWAS locus on chr 11, FSHB/ARL14P, FSHB encodes the β-subunit of FSH and is associated with general fertility status, (rs10835649, 1.23 x 10-11, background subtype). We have replicated the 9 distinct subtype loci in the EA meta-analysis providing orthogonal (independent) validation suggesting these subtypes have distinct genetic architecture. For the first time, a trans-ethnic meta-analysis demonstrates that 3 subtype-specific loci play a role in PCOS pathogenesis across diverse populations. Presentation Date: Saturday, June 17, 2023

Artificial selection reveals complex genetic architecture of shoot branching and its response to nitrate supply in Arabidopsis.

Quantitative traits may be controlled by many loci, many alleles at each locus, and subject to genotype-by-environment interactions, making them difficult to map. One example of such a complex trait is shoot branching in the model plant Arabidopsis, and its plasticity in response to nitrate. Here, we use artificial selection under contrasting nitrate supplies to dissect the genetic architecture of this complex trait, where loci identified by association mapping failed to explain heritability estimates. We found a consistent response to selection for high branching, with correlated responses in other traits such as plasticity and flowering time. Genome-wide scans for selection and simulations suggest that at least tens of loci control this trait, with a distinct genetic architecture between low and high nitrate treatments. While signals of selection could be detected in the populations selected for high branching on low nitrate, there was very little overlap in the regions selected in three independent populations. Thus the regulatory network controlling shoot branching can be tuned in different ways to give similar phenotypes.

Genetics of evolved load resistance in the skeletons of unusually large mice from Gough Island.

A primary function of the skeleton is to resist the loads imparted by body weight. Genetic analyses have identified genomic regions that contribute to differences in skeletal load resistance between laboratory strains of mice, but these studies are usually restricted to 1 or 2 bones and leave open the question of how load resistance evolves in natural populations. To address these challenges, we examined the genetics of bone structure using the largest wild house mice on record, which live on Gough Island (GI). We measured structural traits connected to load resistance in the femur, tibia, scapula, humerus, radius, ulna, and mandible of GI mice, a smaller-bodied reference strain from the mainland, and 760 of their F2s. GI mice have bone geometries indicative of greater load resistance abilities but show no increase in bone mineral density compared to the mainland strain. Across traits and bones, we identified a total of 153 quantitative trait loci (QTL) that span all but one of the autosomes. The breadth of QTL detection ranges from a single bone to all 7 bones. Additive effects of QTL are modest. QTL for bone structure show limited overlap with QTL for bone length and width and QTL for body weight mapped in the same cross, suggesting a distinct genetic architecture for load resistance. Our findings provide a rare genetic portrait of the evolution of load resistance in a natural population with extreme body size.

Genetic analysis of a phenotypic loss in the mechanosensory entrainment of a circalunar clock.

Genetic variants underlying traits that become either non-adaptive or selectively neutral are expected to have altered evolutionary trajectories. Uncovering genetic signatures associated with phenotypic loss presents the opportunity to discover the molecular basis for the phenotype in populations where it persists. Here we study circalunar clocks in populations of the marine midge Clunio marinus. The circalunar clock synchronizes development to the lunar phase, and it is set by moonlight and tidal cycles of mechanical agitation. Two out of ten studied populations have lost their sensitivity to mechanical agitation while preserving sensitivity to moonlight. Intriguingly, the F1 offspring of the two insensitive populations regained the sensitivity to mechanical entrainment, implying a genetically independent loss of the phenotype. By combining quantitative trait locus mapping and genome-wide screens, we explored the genetics of this phenotypic loss. QTL analysis suggested an oligogenic origin with one prevalent additive locus in one of the strains. In addition, it confirmed a distinct genetic architecture in the two insensitive populations. Genomic screens further uncovered several candidate genes underlying QTL regions. The strongest signal under the most prominent QTL contains a duplicated STAT1 gene, which has a well-established role in development, and CG022363, an ortholog of the Drosophila melanogaster CG32100 gene, which plays a role in gravitaxis. Our results support the notion that adaptive phenotypes have a complex genetic basis with mutations occurring at several loci. By dissecting the most prevalent signals, we started to reveal the molecular machinery responsible for the entrainment of the circalunar clock.

Race/ethnicity-stratified fine-mapping of the MHC locus reveals genetic variants associated with late-onset asthma.

Introduction: Asthma is a chronic disease of the airways that impairs normal breathing. The etiology of asthma is complex and involves multiple factors, including the environment and genetics, especially the distinct genetic architecture associated with ancestry. Compared to early-onset asthma, little is known about genetic predisposition to late-onset asthma. We investigated the race/ethnicity-specific relationship among genetic variants within the major histocompatibility complex (MHC) region and late-onset asthma in a North Carolina-based multiracial cohort of adults. Methods: We stratified all analyses by self-reported race (i.e., White and Black) and adjusted all regression models for age, sex, and ancestry. We conducted association tests within the MHC region and performed fine-mapping analyses conditioned on the race/ethnicity-specific lead variant using whole-genome sequencing (WGS) data. We applied computational methods to infer human leukocyte antigen (HLA) alleles and residues at amino acid positions. We replicated findings in the UK Biobank. Results: The lead signals, rs9265901 on the 5' end of HLA-B, rs55888430 on HLA-DOB, and rs117953947 on HCG17, were significantly associated with late-onset asthma in all, White, and Black participants, respectively (OR = 1.73, 95%CI: 1.31 to 2.14, p = 3.62 × 10-5; OR = 3.05, 95%CI: 1.86 to 4.98, p = 8.85 × 10-6; OR = 19.5, 95%CI: 4.37 to 87.2, p = 9.97 × 10-5, respectively). For the HLA analysis, HLA-B*40:02 and HLA-DRB1*04:05, HLA-B*40:02, HLA-C*04:01, and HLA-DRB1*04:05, and HLA-DRB1*03:01 and HLA-DQB1 were significantly associated with late-onset asthma in all, White, and Black participants. Conclusion: Multiple genetic variants within the MHC region were significantly associated with late-onset asthma, and the associations were significantly different by race/ethnicity group.

71-OR: The Landscape of Pharmacogenetic Variants Associated with Noninsulin Antidiabetic Drugs in the Indian Population

Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. India’s distinct genetic architecture and its exploding burden of Type 2 Diabetes (T2D) warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. We mined 1029 Indian whole genomes for PGx variants, drug-drug (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to T2D therapy among Indians. We report remarkable inter-ethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared to other global populations. Network analysis of shared PGx genes predicts high DDI risk during co-administration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when co-administered with PPIs. Our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population. Disclosure A.Sivadas: None. A.Mishra: None. A.Mukhopadhyay: None. K.Narayan: None. S.Sivasubbu: None. V.Scaria: None. A.Kurpad: None. S.Sahana: None. B.Jolly: None. R.C.Bhoyar: None. A.Jain: None. D.Sharma: None. M.Imran: None. V.Senthivel: None. M.K.Divakar: None. Funding DBT/Wellcome Trust India Alliance (IA/E/19/1/504945)

Common and Distinct Genetic Architecture of Age at Diagnosis of Diabetes in South Indian and European Populations.

South Asians are diagnosed with type 2 diabetes (T2D) more than a decade earlier in life than seen in European populations. We hypothesized that studying the genomics of age of diagnosis in these populations may give insight into the earlier age diagnosis of T2D among individuals of South Asian descent. We conducted a meta-analysis of genome-wide association studies (GWAS) of age at diagnosis of T2D in 34,001 individuals from four independent cohorts of European and South Asian Indians. We identified two signals near the TCF7L2 and CDKAL1 genes associated with age at the onset of T2D. The strongest genome-wide significant variants at chromosome 10q25.3 in TCF7L2 (rs7903146; P = 2.4 × 10-12, β = -0.436; SE 0.02) and chromosome 6p22.3 in CDKAL1 (rs9368219; P = 2.29 × 10-8; β = -0.053; SE 0.01) were directionally consistent across ethnic groups and present at similar frequencies; however, both loci harbored additional independent signals that were only present in the South Indian cohorts. A genome-wide signal was also obtained at chromosome 10q26.12 in WDR11 (rs3011366; P = 3.255 × 10-8; β = 1.44; SE 0.25), specifically in the South Indian cohorts. Heritability estimates for the age at diagnosis were much stronger in South Indians than Europeans, and a polygenic risk score constructed based on South Indian GWAS explained ∼2% trait variance. Our findings provide a better understanding of ethnic differences in the age at diagnosis and indicate the potential importance of ethnic differences in the genetic architecture underpinning T2D.