Novel Association of HK1 with Glycated Hemoglobin in a Non-Diabetic Population: A Genome-Wide Evaluation of 14,618 Participants in the Women's Genome Health Study

Type 2 diabetes is a leading cause of morbidity and mortality. While genetic variants have been found to influence the risk of type 2 diabetes mellitus, relatively few studies have focused on genes associated with glycated hemoglobin, an index of the mean blood glucose concentration of the preceding 8–12 weeks. Epidemiologic studies and randomized clinical trials have documented the relationship between glycated hemoglobin levels and the development of long-term complications in diabetes; moreover, higher glycated hemoglobin levels in the subdiabetic range have been shown to predict type 2 diabetes risk and cardiovascular disease. To examine the common genetic determinants of glycated hemoglobin levels, we performed a genome-wide association study that evaluated 337,343 SNPs in 14,618 apparently healthy Caucasian women. The results show that glycated hemoglobin levels are associated with genetic variation at the GCK (rs730497; P = 2.8×10−12), SLC30A8 (rs13266634; P = 9.8×10−8), G6PC2 (rs1402837; P = 6.8×10−10), and HK1 (rs7072268; P = 6.4×10−9) loci. While associations at the GCK, SLC30A8, and G6PC2 loci are confirmatory, the findings at HK1 are novel. We were able to replicate this novel association in an independent validation sample of 455 additional non-diabetic men and women. HK1 encodes the enzyme hexokinase, the first step in glycolysis and a likely candidate for the control of glucose metabolism. This observed genetic association between glycated hemoglobin levels and HK1 polymorphisms paves the way for further studies of the role of HK1 in hemoglobin glycation, glucose metabolism, and diabetes

Variation in VKORC1 is associated with vascular dementia

BACKGROUND: The genetic variant rs9923231 (VKORC1) is associated with differences in the coagulation of blood and consequentially with sensitivity to the drug warfarin. Variation in VKORC1 has been linked in a gene-based test to dementia/Alzheimer’s disease in the parents of participants, with suggestive evidence for an association for rs9923231 (p = 1.8×10(–7)), which was included in the genome-wide significant KAT8 locus. OBJECTIVE: Our study aimed to investigate whether the relationship between rs9923231 and dementia persists only for certain dementia sub-types, and if those taking warfarin are at greater risk. METHODS: We used logistic regression and data from 238,195 participants from UK Biobank to examine the relationship between VKORC1, risk of dementia, and the interplay with warfarin use. RESULTS: Parental history of dementia, APOE variant, atrial fibrillation, diabetes, hypertension, and hypercholesterolemia all had strong associations with vascular dementia (p < 4.6×10(–6)). The T-allele in rs9923231 was linked to a lower warfarin dose (β(perT - allele) = –0.29, p < 2×10(–16)) and risk of vascular dementia (OR = 1.17, p = 0.010), but not other dementia sub-types. However, the risk of vascular dementia was not affected by warfarin use in carriers of the T-allele. CONCLUSION: Our study reports for the first time an association between rs9923231 and vascular dementia, but further research is warranted to explore potential mechanisms and specify the relationship between rs9923231 and features of vascular dementia

Novel genetic markers improve measures of atrial fibrillation risk prediction

Aims Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. Methods and results We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684-0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709-0.774); P = 0.001], the category-less net reclassification [0.490 (0.301-0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033-0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1-5, and 5+% [0.041 (−0.044-0.12); P = 0.33]. Conclusion Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categorie

Candidate loci shared among periodontal disease, diabetes and bone density

IntroductionWhile periodontal disease (PD) has been associated with type 2 diabetes (T2D) and osteoporosis, the underlying genetic mechanisms for these associations remain largely unknown. The aim of this study is to apply cross-trait genetic analyses to investigate the potentially shared biology among PD, T2D, and bone mineral density (BMD) by assessing pairwise genetic correlations and searching for shared polymorphisms.MethodsWe applied cross-trait genetic analyses leveraging genome-wide association study (GWAS) summary statistics for: Periodontitis/loose teeth from the UKBB/GLIDE consortium (PerioLT, N=506594), T2D from the DIAGRAM consortium (Neff=228825), and BMD from the GEFOS consortium (N=426824). Among all three, pair-wise genetic correlations were estimated with linkage disequilibrium (LD) score regression. Multi-trait meta-analysis of GWAS (MTAG) and colocalization analyses were performed to discover shared genome-wide significant variants (pMTAG &lt;5x10-8). For replication, we conducted independent genetic analyses in the Women’s Genome Health Study (WGHS), a prospective cohort study of middle-aged women of whom 14711 provided self-reported periodontal disease diagnosis, oral health measures, and periodontal risk factor data including incident T2D.ResultsSignificant genetic correlations were identified between PerioLT/T2D (Rg=0.23; SE=0.04; p=7.4e-09) and T2D/BMD (Rg=0.09; SE=0.02; p=9.8e-06). Twenty-one independent pleiotropic variants were identified via MTAG (pMTAG&lt;5x10-8 across all traits). Of these variants, genetic signals for PerioLT and T2D colocalized at one candidate variant (rs17522122; ProbH4 = 0.58), a 3’UTR variant of AKAP6. Colocalization between T2D/BMD and the original PerioLT GWAS p-values suggested 14 additional loci. In the independent WGHS sample, which includes responses to a validated oral health questionnaire for PD surveillance, the primary shared candidate (rs17522122) was associated with less frequent dental flossing [OR(95%CI)= 0.92 (0.87-0.98), p=0.007], a response that is correlated with worse PD status. Moreover, 4 additional candidate variants were indirectly supported by associations with less frequent dental flossing [rs75933965, 1.17(1.04-1.31), p=0.008], less frequent dental visits [rs77464186, 0.82(0.75-0.91), p=0.0002], less frequent dental prophylaxis [rs67111375, 0.91(0.83-0.99), p=0.03; rs77464186, 0.80(0.72-0.89), p=3.8e-05], or having bone loss around teeth [rs8047395, 1.09(1.03-1.15), p=0.005].DiscussionThis integrative approach identified one colocalized locus and 14 additional candidate loci that are shared between T2D and PD/oral health by comparing effects across PD, T2D and BMD. Future research is needed to independently validate our findings

Novel genetic markers improve measures of atrial fibrillation risk prediction

Aims Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. Methods and results We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684–0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709–0.774); P = 0.001], the category-less net reclassification [0.490 (0.301–0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033–0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1–5, and 5+% [0.041 (−0.044–0.12); P = 0.33]. Conclusion: Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categories

A Kinesin Family Member 6 Variant Is Associated With Coronary Heart Disease in the Women’s Health Study

ObjectivesWe asked if carriers of the 719Arg allele of kinesin family member 6 (KIF6) have increased risk of coronary heart disease (CHD) in a cohort of initially healthy Caucasian American women.BackgroundThe 719Arg allele of KIF6 (rs20455) has been reported to be associated with increased risk of CHD in a large population-based prospective study, ARIC (Atherosclerosis Risk in Communities), and in the placebo arms of 2 statin trials, CARE (Cholesterol and Recurrent Events) and WOSCOPS (West of Scotland Coronary Prevention Study). However, this KIF6 variant was not specifically investigated in the female subgroup in the ARIC study, and the CARE and WOSCOPS trials included only a small number of female patients.MethodsGenotypes of the rs20455 single nucleotide polymorphism (SNP) were determined among 25,283 initially healthy Caucasian women, age 45 years and older, participating in the WHS (Women’s Health Study) who were prospectively followed over a 12-year period for incident cardiovascular events. The risk associated with the 719Arg allele of KIF6 was estimated using Cox proportional hazards models that adjusted for age and traditional risk factors.ResultsDuring follow-up, 953 women suffered a first-ever CHD event (myocardial infarction, coronary revascularization, or cardiovascular death) or first-ever ischemic stroke. Compared with noncarriers, carriers of the 719Arg allele had an increased risk of CHD (hazard ratio [HR] = 1.24 [95% confidence interval (CI) 1.04 to 1.46, p = 0.013]) and myocardial infarction (HR = 1.34 [95% CI 1.02 to 1.75, p = 0.034]) but not ischemic stroke.ConclusionsConfirming and extending previous reports, carriers of the 719Arg allele of KIF6 have 34% higher risk of myocardial infarction and 24% higher risk of CHD compared with noncarriers among 25,283 women from the WHS

Genetics, Ancestry, and Hypertension: Implications for Targeted Antihypertensive Therapies

Hypertension is the most common chronic condition seen by physicians in ambulatory care and a condition for which life-long medications are commonly prescribed. There is evidence for genetic factors influencing blood pressure variation in populations and response to medications. This review summarizes recent genetic discoveries that surround blood pressure, hypertension, and antihypertensive drug response from genome-wide association studies, while highlighting ancestry-specific findings and any potential implication for drug therapy targets. Genome-wide association studies have identified several novel loci for inter-individual variation of blood pressure and hypertension risk in the general population. Evidence from pharmacogenetic studies suggests that genes influence the blood pressure response to antihypertensive drugs, although results are somewhat inconsistent across studies. There is still much work that remains to be done to identify genes both for efficacy and adverse events of antihypertensive medications

A genome-wide cross-phenotype meta-analysis of the association of blood pressure with migraine

Blood pressure (BP) was inconsistently associated with migraine and the mechanisms of BP-lowering medications in migraine prophylaxis are unknown. Leveraging large-scale summary statistics for migraine (N-cases/N-controls = 59,674/316,078) and BP (N = 757,601), we find positive genetic correlations of migraine with diastolic BP (DBP, r(g) = 0.11, P = 3.56 x 10(-06)) and systolic BP (SBP, r(g) = 0.06, P = 0.01), but not pulse pressure (PP, r(g) = -0.01, P = 0.75). Cross-trait meta-analysis reveals 14 shared loci (P <= 5 x 10(-08)), nine of which replicate (P < 0.05) in the UK Biobank. Five shared loci (ITGB5, SMG6, ADRA2B, ANKDD1B, and KIAA0040) are reinforced in gene-level analysis and highlight potential mechanisms involving vascular development, endothelial function and calcium homeostasis. Mendelian randomization reveals stronger instrumental estimates of DBP (OR [95% CI] = 1.20 [1.15-1.25]/10 mmHg; P = 5.57 x 10(-25)) on migraine than SBP (1.05 [1.03-1.07]/10 mmHg; P = 2.60 x 10(-07)) and a corresponding opposite effect for PP (0.92 [0.88-0.95]/10 mmHg; P = 3.65 x 10(-07)). These findings support a critical role of DBP in migraine susceptibility and shared biology underlying BP and migraine

Migraine genetics : from genome-wide association studies to translational insights

Understanding the molecular mechanisms that precede and give rise to a migraine attack is key to developing new therapeutic strategies. Advances towards this goal have recently been made through genome-wide association studies, which have identified new genetic components of migraine that highlight vascular etiologies and underline the polygenic nature of this disorder.Non peer reviewe