Lp(a) is a genetically determined lipoprotein targeted by emerging therapies. In a UK Biobank analysis (1,026 abdominal aortic aneurysm [AAA] cases, 469,989 controls), elevated Lp(a) was associated with increased risk of AAA, including at clinically relevant thresholds while controlling for traditional risk factors, including ApoB. Multivariable Mendelian randomization confirmed a causal relationship between lipoprotein(a) [Lp(a)] and AAA independent of apolipoprotein B. These findings support Lp(a) as a modifiable risk factor and potential therapeutic target for AAA, a condition with limited medical treatment options. AAA should be considered as an outcome in future clinical trials of Lp(a)-lowering therapies.

OBJECTIVE:Recent evidence suggests an association between air pollution exposure and abdominal aortic aneurysm (AAA) rupture. It is unclear whether environmental factors also influence the rate at which AAAs grow. This study aimed to determine how environmental factors contribute to aneurysm growth using a prospective cohort study design. METHODS:This study used data from the UK Aneurysm Growth Study (UKAGS), a national cohort of men with AAA representative of the UK population in AAA surveillance. Participant records were linked with environmental exposure data from a validated land use regression model, including nitrogen dioxide (NO2) concentrations (μg/m3), particles with an aerodynamic diameter < 2.5 μm (PM2.5) concentrations (μg/m3), satellite measures of greenness (normalised difference vegetation index, enhanced vegetation index, and tree cover density), Ordnance Survey derived greenspace, and noise pollution exposure (dB) from three sources (aircraft, railway, and road), over a ten year period (2010 - 2019) with a 25 × 25 m grid cell resolution. Linear mixed effect growth modelling was used to explore the association with AAA growth. RESULTS:Environmental data were available for 3 360 (86.0%) participants. Mean follow up ± standard deviation was 5.64 ± 2.47 years. There were no statistically significant associations between NO2, PM2.5, and transport noise pollution with AAA growth in adjusted models, whereas relationships with greenspace measures were inconsistent. CONCLUSION:The link between environmental factors and AAA growth remains unclear. Potential issues include use of those participating in a screening programme (who may be healthier than the general population and less susceptible to environmental influences). Managing traditional risk factors, especially smoking, remains key to clinical care.

Introduction: Lipoprotein(a) (Lp(a)) is an apolipoprotein B (ApoB) containing particle that is causally associated with atherosclerotic vascular disease and the target of emerging therapeutics. Recent work has highlighted the role of circulating lipoproteins in abdominal aortic aneurysm (AAA). We sought to triangulate human observational and genetic evidence to evaluate the role of Lp(a) in AAA. Methods: We tested the association between levels of Lp(a) and clinically diagnosed aortic aneurysms while controlling for traditional AAA risk factors and levels of ApoB using logistic regression among 798 individuals with and 384,499 individuals without AAA in the UK biobank (UKB). Multivariable Mendelian randomization (MVMR) was used to test for putatively casual associations between Lp(a) and AAA controlling for ApoB. Genetic instruments for Lp(a) and ApoB were created from genome-wide association studies (GWAS) of Lp(a) and ApoB comprising 335,796 and 418,505 UKB participants, respectively. The instruments were tested against AAA using data from a GWAS of 39,221 individuals with and 1,086,107 without AAA. Results: Elevated Lp(a) levels were associated with an increased risk of AAA (OR 1.04 per 10 nmol/L Lp(a); 95%CI 1.02-1.05; P<0.01). Clinically elevated Lp(a) levels (>150nmol/L) were likewise associated with an increased risk of AAA (OR 1.50; 95%CI 1.17-1.91; P<0.01) when compared to individuals with Lp(a) levels <150nmol/L. MVMR confirmed a significant association between genetically proxied increased Lp(a) and increased genetic liability to AAA (OR 1.13 per SD increased in Lp(a); 95%CI 1.02-1.24; P<0.02). Conclusion: Both observational and genetic casual inference analyses support an association between increased Lp(a) and AAA risk that is independent of ApoB. Mendelian randomization analyses posit a causal relationship. These findings suggest that Lp(a) may be a therapeutic target for AAA and drive the inclusion of AAA as an outcome in clinical trials of Lp(a) antagonists.

Abdominal aortic aneurysm (AAA) is a common disease with substantial heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 141 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis explained AAA risk beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in AAA pathogenesis. These genes also indicate overlap between the development of AAA and other monogenic aortopathies, particularly via transforming growth factor β signaling. Motivated by the strong evidence for the role of lipid metabolism in AAA, we used Mendelian randomization to establish the central role of nonhigh-density lipoprotein cholesterol in AAA and identified the opportunity for repurposing of proprotein convertase, subtilisin/kexin-type 9 (PCSK9) inhibitors. This was supported by a study demonstrating that PCSK9 loss of function prevented the development of AAA in a preclinical mouse model.

Rupture or dissection of the aorta is often fatal. Tcheandjieu and colleagues now identify key pathways underlying aortic dilatation, a common prelude to acute aortic events, and assess the utility of a polygenic risk score to identify those at highest risk of aortic death in whom prophylactic surgical repair may be beneficial.

SummaryAbdominal aortic aneurysm (AAA) is a common disease with significant heritability. In this study, we performed a genome-wide association meta-analysis from 14 discovery cohorts and uncovered 144 independent associations, including 97 previously unreported loci. A polygenic risk score derived from meta-analysis was able to explain AAA beyond clinical risk factors. Genes at AAA risk loci indicate involvement of lipid metabolism, vascular development and remodeling, extracellular matrix dysregulation and inflammation as key mechanisms in the pathogenesis of AAA. We further integrated functional data to elucidate expression of genes associated with AAA. These genes also indicate crossover between the development of AAA and other monogenic aortopathies, particularly via TGF-β signaling pathways. Motivated by the strong evidence for the role of lipid levels in AAA by PheWAS, we identified therapeutic opportunities using Mendelian Randomization and, in pre-clinical studies, we demonstrated thatPCSK9inhibition in mice prevented the development of AAA.

At face value, questions about the sex ratio have always seemed to have straightforward answers, which on closer inspection turn out to be fiendishly complex. The familial distribution of male and female births is no exception.

Throughout the world, there is a male-bias in the sex ratio at birth (SRB). It is not known whether this phenomenon has a genetic basis, though there is tentative evidence from genealogical and genomic studies that it may have. It has been proposed that the higher rate of male childhood mortality in humans is linked to the male-bias in SRB through parental investment, but this may only apply to facultative not genetic sex ratio adjustment. In previous population genetic models, elevated mortality in one sex (prior to breeding) has been shown not to affect the SRB, but these models did not consider the role of replacement births (i.e. births that only occur because a sibling died prematurely). In a set of population genetic modelling simulations, in which sex ratio is controlled by an autosomal gene expressed in the male line, this study shows that when there is replacement of dead offspring, this leads to a sustained bias in the SRB in the direction of the sex suffering the highest mortality. In the example of higher male mortality, this occurs, because replacement offspring are disproportionately drawn from fathers who were genetically predisposed to have initially had sons (because sons were more likely to die prematurely), and more likely to pass on male-biasing alleles to replacement offspring. To test the empirical basis for replacement births, an analysis of birth data from the Demographic and Health Survey program was conducted, which shows that parents do indeed tend to replace children who die prematurely.

Background It is recognized that factors beyond aortic size are important in predicting outcome in abdominal aortic aneurysm (AAA) disease. AAA is characterized by the breakdown of elastin within the aortic tunica media, leading to aortic dilatation and rupture. The aim of this study was to investigate the association of plasma desmosine (pDES), an elastin‐specific degradation product, with disease severity and clinical outcome in patients with AAA. Methods and Results We measured pDES and serum biomarker concentrations in 507 patients with AAAs (94% men; mean age, 72.4±6.1 years; mean AAA diameter, 48±8 mm) and 162 control subjects (100% men; mean age, 71.5±4.4 years) from 2 observational cohort studies. In the longitudinal cohort study (n=239), we explored the incremental prognostic value of pDES on AAA events. pDES was higher in patients with AAA compared with control subjects (mean±SD: 0.46±0.22 versus 0.33±0.16 ng/mL; P<0.001) and had the strongest correlation with AAA diameter (r=0.39; P<0.0001) of any serum biomarker. After adjustment for baseline AAA diameter, pDES was associated with an AAA event (hazard ratio, 2.03 per SD increase [95% CI, 1.02–4.02]; P=0.044). In addition to AAA diameter, pDES provided incremental improvement in risk stratification (continuous net reclassification improvement, 34.4% [95% CI, −10.8% to 57.5%; P=0.09]; integrated discrimination improvement, 0.04 [95% CI, 0.00–0.15; P=0.050]). Conclusions pDES concentrations predict disease severity and clinical outcomes in patients with AAA. Clinical Trial Registration http://www.isrctn.com. Unique identifier: ISRCTN76413758.

Abdominal aortic aneurysm (AAA) is the thirteenth leading cause of death and occurs in 5% of men between the ages of 65 and 74 years. Currently, patients at risk for AAA are offered ultrasound screening and surveillance, and when appropriate (size >55 mm or expansion rate >10 mm/year), elective AAA repair. Despite this surveillance, prediction of patients likely to have AAA rupture is difficult, with many AAAs rupturing before reaching 55 mm or having unpredictable expansion rates. A serum biomarker that could predict AAA events would be extremely valuable. Desmosine is an amino acid cross-link that is released into the bloodstream when there is elastin breakdown. We hypothesised that plasma desmosine (pDES) might be associated with events in patients with AAA. Methods We evaluated pDES levels in 239 patients with AAA recruited to the MA3RS study (NCT01749280). Patients had 6 monthly visits with abdominal ultrasound performed at each visit. A panel of biomarkers related to vascular integrity was also obtained. Patients were followed up for clinical events including AAA rupture, repair and mortality. Results The cohort was predominantly male (87.4%). Mean AAA diameter was 50.6±8.0 mm. pDES was significantly correlated with ultrasound AAA diameter (r=0.27, p<0.0001). In total 13 patients had an emergency AAA event and 20 had MACE (AAA event +CV mortality). pDES was a major predictor of both AAA events (HR 4.97, 95% CI 1.05–23.64, p=0.044) and MACE (HR 5.92, 95% CI 1.73–20.26, p=0.005) independent of AAA diameter, with patients with the highest tertiles of pDES having the worst outcome. pDES was significantly more associated with AAA events than the next best biomarker, MMP-9 (AUC 0.70 vs 0.60, p<0.001). pDES was associated with improvement in risk prediction when added to AAA diameter with a significant improvement in both net reclassification index (p=0.013) and integrative discrimination increment (p<0.001). Conclusion pDES was an independent predictor of adverse outcome in patients with AAA and may be the first non-invasive serum biomarker to predict events in this group of patients.

In this paper, we investigate what late timing of marriage combined with neo-locality in early modern Western Europe actually implied for the likelihood of upward intergenerational support. In our analysis of genealogical data from the Netherlands (1650-1899) we show that due to high marriage ages and small spousal age gaps, life cycles of children and their parents were going through difficult periods at the same time, with the elderly as potential victims. To some extent, the risk of 'hardship' was compensated for by relatively small geographical distances between the parental and children's households, allowing for exchange of support. We discuss our outcomes in the broader context of alternative options and elderly care arrangements that were developed from the early modern period onwards.

The features of historical marriage patterns have been linked to debates in social and economic history about economic growth and female agency. However, there is a lack of empirical evidence on the demographics of marriage prior to the nineteenth century. Here, we study trends in sex-specific ages at first marriage, regional variation and the impact of migration on marital timing in the Netherlands in the period 1650-1900. We make use of two new large historical datasets, namely an aggregation of Dutch genealogies and the transcribed marriage banns of Amsterdam. This allows us to understand the features and developments of marriage ages from a long-term perspective in what is known as one of the core-areas of the so-called European Marriage Pattern. Our results show high marriage ages for both sexes from the beginning of our study period, increasing until the mid-19th century. A closer look at regional variation reveals clear differences between the provinces and between urban and rural settings with those in the western part of the country and in urban centers marrying earlier. Migrating individuals married on average later than non-migrating individuals both compared to men and women in the receiving community, as to the ‘stayers’ in the location of origin. As later marriage implies a reduction of the window of fertility, especially for women, our results suggest that migration and increasing regional mobility might have been an important driver of the demographic shift toward higher marriage ages and lower fertility in Europe between the 17th and 19th centuries.

There are broadly two explanations for why human longevity appears to be extended by marriage. First, there is the social explanation, whereby the companionship, division of labour and the economic support that marriage offers is thought to extend life. Second, there is a selective explanation, whereby those individuals with high potential longevity are more attractive to the opposite sex and therefore more likely to get married. Here we analyse the “TRA” dataset from 19th century France, using an evolutionary approach to address the question of why marriage is linked to longevity, focussing particularly on sex differences. The dataset is based on death and marriage records from all of France between 1798 and 1901 and includes information on age at death, marriage and wealth for individuals whose surnames began with the letters TRA. We find that marriage is positively associated with longevity, particularly for men. In part, this is related to the higher rate of deaths for single males during marriageable age, as compared to a higher rate of deaths for females during marriage. There is a positive association between wealth (at death) and longevity for individuals who were single or married at death, with a stronger effect for singles. Analysis of the effect of spousal age gap on duration of survival after first marriage indicates that men who were married to younger women lived longer, whereas the longevity of women was not associated with the spousal age gap. We put forward an evolutionary perspective on marriage and longevity, hypothesizing that there is an important role for sexual selection in the association between marriage and longevity, with women selecting on characteristics associated with longevity, whilst men select on characteristics associated with reproductive potential.

Background The Indian sex ratio has become highly male-biased in recent decades. This may be attributed to prenatal sex selection (PSS) and excess female infant mortality. However, the question of whether these factors are related has not been adequately studied. Here we examine whether increased use of PSS may offset excess female infant mortality, by reducing the number of ‘unwanted’ daughters being born. Methods We analyse the National Family Health Survey (NHFS) data sets for India, which contain nationally representative samples of birth histories for women aged 15–49, interviewed in 1992–1993, 1998–1999 and 2005–2006. We test for missing female births at the second and third birth order, by analysis of the frequencies of sibling sex combinations, and examine the mortality differential between male and female infants, controlling for household wealth and sex(es) of older siblings. Results PSS was used most in wealthier households at the second and third birth order, when the firstborn, or firstborn and second-born, siblings were female. Having preceding female siblings was a significant risk factor for female infant mortality, but was not correlated with household wealth. Conclusions PSS and female infant mortality increase with the presence of older female siblings, yet we find no evidence that increasing use of PSS prevents female infant mortality, because PSS and the proportion of female infant mortality attributable to having older sisters increased over the study period. Increased pressure on higher birth order females caused by the trend towards smaller family sizes may explain this.

A data set of first marriages (including marriage location and ages of spouses at marriage) and lifespans of spouses (including year and location of births and deaths, where known), for marriages conducted between 1600 and 1899 in the Netherlands, Belgium and Germany. Also included is a binary indicator for whether the marriage, birth or death locations were urban or rural between 1600 and 1800, according to the coding system used by Bosker et al. 2013 [Rev. Econ. Stat., 95(4), 1418-1437 doi:10.1162/REST_a_00284]. The data set is derived from a genealogical database, which was constructed from family tree (GEDCOM) files contributed by users of www.genealogieonline.nl. The genealogical data from contributed files was error-checked before being combined into a single database using the TreeChecker application. From the initial pool of >1600 f iles contributed by the users of www.genealogieonline.nl, 924 files were included in the database after an assessment of the percentage of errors in each file, hence the database is known as the GO 924 set.Duplicate marriages were identified by the year of marriage and the first 7 letters of each spouse surname, whereupon a random duplicate was selected for inclusion in the data set. Note that names of individuals and exact dates of marria ges, births and deaths are excluded from this data set to prevent identification of individuals, as the genealogical data was provided to our research group on the basis that it would only be published in an aggregated or anonymised format. Access to the un-anonymised data may be granted subject to confidentiality agreements, please contact the authors for further information. Marriages were only included where the place of marriage had been checked and geocoded with latitude and longitude coordinates, where (as far as we could ascertain) it was the first marriage of the spouse, age at marriage was > 13 for both spouses, all lifespans were < 111 and no estimated dates were used to calculate spouse lifespan.The dataset is in a long format, in which there is a separate record for each spouse. It can be determined whether the spouse is the husba nd or wife (and conversely whether the other is the wife or husband) by the `spouse_sex` variable. A description of each variable is included in the text file accompanying the csv data file.

This article has been accepted for publication in Journal of Epidemiology and Community Health following peer review. The definitive copyedited, typeset version Gellatly C, Petrie M. Pre-natal sex selection and female infant mortality are more common in India after firstborn and second-born daughters. Journal of Epidemiology and Community Health 2016 is available online at: http://dx.doi.org/10.1136/jech-2016207489