Genomic ancestry and cancer among Latin Americans

Latin American populations, characterized by intricate admixture patterns resulting from the intermingling of ancestries from European, Native American (NA) Asian, and African ancestries which result in a vast and complex genetic landscape, harboring unique combinations of novel variants. This genetic diversity not only poses challenges in traditional population genetics methods but also opens avenues for a deeper understanding of its implications in health. In cancer, the interplay between genetic ancestry, lifestyle factors, and healthcare disparities adds a layer of complexity to the varying incidence and mortality rates observed across different Latin American subpopulations. This complex interdependence has been unveiled through numerous studies, whether conducted on Latin American patients residing on the continent or abroad, revealing discernible differences in germline composition that influence divergent disease phenotypes such as higher incidence of Luminal B and Her2 breast tumors, EGFR and KRAS mutated lung adenocarcinomas in addition to an enrichment in BRCA1/2 pathogenic variants and a higher than expected prevalence of variants in colorectal cancer associated genes such as APC and MLH1. In prostate cancer novel risk variants have also been solely identified in Latin American populations. Due to the complexity of genetic divergence, inputs from each individual ancestry seem to carry independent contributions that interplay in the development of these complex disease phenotypes. By understanding these unique population characteristics, genomic ancestries hold a promising avenue for tailoring prognostic assessments and optimizing responses to oncological interventions.

Patients with periodontitis might increase the risk of urologic cancers: a bidirectional two-sample Mendelian randomization study

BACKGROUND

Numerous observational epidemiological studies have reported a bidirectional relationship between periodontitis and urological cancers. However, the causal link between these two phenotypes remains uncertain. This study aimed to examine the bidirectional causal association between periodontitis and four types of urological tumors, specifically kidney cancer (KC), prostate cancer (PC), bladder cancer (BC), and testis cancer (TC).

METHODS

Based on large-scale genome-wide association study (GWAS) data, we utilized the two-sample Mendelian randomization (MR) approach to evaluate causal relationships between periodontitis and urological cancers. Several MR methods covering various consistency assumptions were applied in this study, including contamination mixture and Robust Adjusted Profile Score to obtain robust results. Summary-level data of individuals with European ancestry were extracted from the UK Biobank, the Kaiser GERA cohorts, and the FinnGen consortium.

RESULTS

Our findings revealed significant positive genetic correlations between periodontitis and kidney cancer (OR 1.287; 95% CI 1.04, 1.594; P = 0.020). We did not find a significant association of periodontitis on prostate cancer, bladder cancer, and testis cancer. In reverse MR, no significant results were observed supporting the effect of urologic cancers on periodontitis (all P > 0.05).

CONCLUSION

Our study provides the evidence of a potential causal relationship between periodontitis and kidney cancer. However, large-scale studies are warranted to confirm and elucidate the underlying mechanisms of this association.

Causal relationship between diabetes mellitus, glycemic traits and Parkinson's disease: a multivariable mendelian randomization analysis

BACKGROUND

Observational studies have indicated an association between diabetes mellitus (DM), glycemic traits, and the occurrence of Parkinson's disease (PD). However, the complex interactions between these factors and the presence of a causal relationship remain unclear. Therefore, we aim to systematically assess the causal relationship between diabetes, glycemic traits, and PD onset, risk, and progression.

METHOD

We used two-sample Mendelian randomization (MR) to investigate potential associations between diabetes, glycemic traits, and PD. We used summary statistics from genome-wide association studies (GWAS). In addition, we employed multivariable Mendelian randomization to evaluate the mediating effects of anti-diabetic medications on the relationship between diabetes, glycemic traits, and PD. To ensure the robustness of our findings, we performed a series of sensitivity analyses.

RESULTS

In our univariable Mendelian randomization (MR) analysis, we found evidence of a causal relationship between genetic susceptibility to type 1 diabetes (T1DM) and a reduced risk of PD (OR = 0.9708; 95% CI: 0.9466, 0.9956; P = 0.0214). In our multivariable MR analysis, after considering the conditions of anti-diabetic drug use, this correlation disappeared with adjustment for potential mediators, including anti-diabetic medications, insulin use, and metformin use.

CONCLUSION

Our MR study confirms a potential protective causal relationship between genetically predicted type 1 diabetes and reduced risk of PD, which may be mediated by factors related to anti-diabetic medications.

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

BACKGROUND

Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored.

METHODS

Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold.

RESULTS

Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12-3.50, P-value = 4.13 × 10-15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99-2.49, P-value = 5.70 × 10-46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72-0.74).

CONCLUSIONS

Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS.

Association between circulating inflammatory markers and adult cancer risk: a Mendelian randomization analysis

BACKGROUND

Tumour-promoting inflammation is a "hallmark" of cancer and conventional epidemiological studies have reported links between various inflammatory markers and cancer risk. The causal nature of these relationships and, thus, the suitability of these markers as intervention targets for cancer prevention is unclear.

METHODS

We meta-analysed 6 genome-wide association studies of circulating inflammatory markers comprising 59,969 participants of European ancestry. We then used combined cis-Mendelian randomization and colocalisation analysis to evaluate the causal role of 66 circulating inflammatory markers in risk of 30 adult cancers in 338,294 cancer cases and up to 1,238,345 controls. Genetic instruments for inflammatory markers were constructed using genome-wide significant (P < 5.0 × 10-8) cis-acting SNPs (i.e., in or ±250 kb from the gene encoding the relevant protein) in weak linkage disequilibrium (LD, r2 < 0.10). Effect estimates were generated using inverse-variance weighted random-effects models and standard errors were inflated to account for weak LD between variants with reference to the 1000 Genomes Phase 3 CEU panel. A false discovery rate (FDR)-corrected P-value ("q-value") <0.05 was used as a threshold to define "strong evidence" to support associations and 0.05 ≤ q-value < 0.20 to define "suggestive evidence". A colocalisation posterior probability (PPH4) >70% was employed to indicate support for shared causal variants across inflammatory markers and cancer outcomes. Findings were replicated in the FinnGen study and then pooled using meta-analysis.

FINDINGS

We found strong evidence to support an association of genetically-proxied circulating pro-adrenomedullin concentrations with increased breast cancer risk (OR: 1.19, 95% CI: 1.10-1.29, q-value = 0.033, PPH4 = 84.3%) and suggestive evidence to support associations of interleukin-23 receptor concentrations with increased pancreatic cancer risk (OR: 1.42, 95% CI: 1.20-1.69, q-value = 0.055, PPH4 = 73.9%), prothrombin concentrations with decreased basal cell carcinoma risk (OR: 0.66, 95% CI: 0.53-0.81, q-value = 0.067, PPH4 = 81.8%), and interleukin-1 receptor-like 1 concentrations with decreased triple-negative breast cancer risk (OR: 0.92, 95% CI: 0.88-0.97, q-value = 0.15, PPH4 = 85.6%). These findings were replicated in pooled analyses with the FinnGen study. Though suggestive evidence was found to support an association of macrophage migration inhibitory factor concentrations with increased bladder cancer risk (OR: 2.46, 95% CI: 1.48-4.10, q-value = 0.072, PPH4 = 76.1%), this finding was not replicated when pooled with the FinnGen study. For 22 of 30 cancer outcomes examined, there was little evidence (q-value ≥0.20) that any of the 66 circulating inflammatory markers examined were associated with cancer risk.

INTERPRETATION

Our comprehensive joint Mendelian randomization and colocalisation analysis of the role of circulating inflammatory markers in cancer risk identified potential roles for 4 circulating inflammatory markers in risk of 4 site-specific cancers. Contrary to reports from some prior conventional epidemiological studies, we found little evidence of association of circulating inflammatory markers with the majority of site-specific cancers evaluated.

FUNDING

Cancer Research UK (C68933/A28534, C18281/A29019, PPRCPJT∖100005), World Cancer Research Fund (IIG_FULL_2020_022), National Institute for Health Research (NIHR202411, BRC-1215-20011), Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4), Academy of Finland Project 326291, European Union's Horizon 2020 grant agreement no. 848158 (EarlyCause), French National Cancer Institute (INCa SHSESP20, 2020-076), Versus Arthritis (21173, 21754, 21755), National Institutes of Health (U19 CA203654), National Cancer Institute (U19CA203654).

Prevalence, associated factors, and gene polymorphisms of obesity in Tibetan adults in Qinghai, China

OBJECTIVES

To explore the prevalence and associated factors of obesity in Tibetan adults in Qinghai, China, and to determine the association between the FTO (rs1121980 and rs17817449) and MC4R gene (rs17782313 and rs12970134) polymorphisms with obesity.

METHODS

A cross-sectional survey was conducted in 2015 in Qinghai to selected Tibetan adults aged 20 to 80 years. Prevalence of obesity (BMI ≥ 28 kg/m2) and overweight (BMI 24 ~ 27.9 kg/m2) were evaluated. Multivariable logistic models were used to determine the associated factors. Pair-matched subjects of obesity cases and normal-weight controls were selected for the gene polymorphism analyses. Conditional logistic models were used to assess the association between gene polymorphisms with obesity. Additive and multiplicative gene-environment interactions were tested.

RESULTS

A total of 1741 Tibetan adults were enrolled. The age- and sex- standardized prevalence of obesity and overweight was 18.09% and 31.71%, respectively. Male sex, older age, heavy level of leisure-time exercise, current smoke, and heavy level of occupational physical activity were associated with both obesity and overweight. MC4R gene polymorphisms were associated with obesity in Tibetan adults. No significant gene-environment interaction was detected.

CONCLUSION

The prevalence of obesity and overweight in Tibetan adults was high. Both environmental and genetic factors contributed to the obesity prevalent.

Selection of genetic instruments in Mendelian randomisation studies of sleep traits

This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.

Genetic evidence for the causal association between type 1 diabetes and the risk of polycystic ovary syndrome

BACKGROUND

Accumulating observational studies have identified associations between type 1 diabetes (T1D) and polycystic ovary syndrome (PCOS). Still, the evidence about the causal effect of this association is uncertain.

METHODS

We performed a two-sample Mendelian randomization (MR) analysis to test for the causal association between T1D and PCOS using data from a large-scale biopsy-confirmed genome-wide association study (GWAS) in European ancestries. We innovatively divided T1D into nine subgroups to be analyzed separately, including: type1 diabetes wide definition, type1 diabetes early onset, type 1 diabetes with coma, type 1 diabetes with ketoacidosis, type 1 diabetes with neurological complications, type 1 diabetes with ophthalmic complications, type 1 diabetes with peripheral circulatory complications, type 1 diabetes with renal complications, and type 1 diabetes with other specified/multiple/unspecified complications. GWAS data for PCOS were obtained from a large-scale GWAS (10,074 cases and 103,164 controls) for primary analysis and the IEU consortium for replication and meta-analysis. Sensitivity analyses were conducted to evaluate heterogeneity and pleiotropy.

RESULTS

Following rigorous instrument selection steps, the number of SNPs finally used for T1D nine subgroups varying from 6 to 36 was retained in MR estimation. However, we did not observe evidence of causal association between type 1 diabetes nine subgroups and PCOS using the IVW analysis, MR-Egger regression, and weighted median approaches, and all P values were > 0.05 with ORs near 1. Subsequent replicates and meta-analyses also yielded consistent results. A number of sensitivity analyses also did not reveal heterogeneity and pleiotropy, including Cochran's Q test, MR-Egger intercept test, MR-PRESSO global test, leave-one-out analysis, and funnel plot analysis.

CONCLUSION

This is the first MR study to investigate the causal relationship between type 1 diabetes and PCOS. Our findings failed to find substantial causal effect of type 1 diabetes on risk of PCOS. Further randomized controlled studies and MR studies are necessary.

Violation of the Constant Genetic Effect Assumption Can Result in Biased Estimates for Non-Linear Mendelian Randomization

INTRODUCTION

Non-linear Mendelian randomization is an extension of conventional Mendelian randomization that performs separate instrumental variable analyses in strata of the study population with different average levels of the exposure. The approach estimates a localized average causal effect function, representing the average causal effect of the exposure on the outcome at different levels of the exposure. The commonly used residual method for dividing the population into strata works under the assumption that the effect of the genetic instrument on the exposure is linear and constant in the study population. However, this assumption may not hold in practice.

METHODS

We use the recently developed doubly ranked method to re-analyse various datasets previously analysed using the residual method. In particular, we consider a genetic score for 25-hydroxyvitamin D (25[OH]D) used in a recent non-linear Mendelian randomization analysis to assess the potential effect of vitamin D supplementation on all-cause mortality.

RESULTS

The effect of the genetic score on 25(OH)D concentrations varies strongly, with a five-fold difference in the estimated genetic association with the exposure in the lowest and highest decile groups. Evidence for a protective causal effect of vitamin D supplementation on all-cause mortality in low vitamin D individuals is evident for the residual method but not for the doubly ranked method. We show that the constant genetic effect assumption is more reasonable for some exposures and less reasonable for others. If the doubly ranked method indicates that this assumption is violated, then estimates from both the residual and doubly ranked methods can be biased, although bias was smaller on average in the doubly ranked method.

CONCLUSION

Analysts wanting to perform non-linear Mendelian randomization should compare results from both the residual and doubly ranked methods, as well as consider transforming the exposure for the residual method to reduce heterogeneity in the genetic effect on the exposure.

A genome-wide gene-environment interaction study of breast cancer risk for women of European ancestry

BACKGROUND

Genome-wide studies of gene-environment interactions (G×E) may identify variants associated with disease risk in conjunction with lifestyle/environmental exposures. We conducted a genome-wide G×E analysis of ~ 7.6 million common variants and seven lifestyle/environmental risk factors for breast cancer risk overall and for estrogen receptor positive (ER +) breast cancer.

METHODS

Analyses were conducted using 72,285 breast cancer cases and 80,354 controls of European ancestry from the Breast Cancer Association Consortium. Gene-environment interactions were evaluated using standard unconditional logistic regression models and likelihood ratio tests for breast cancer risk overall and for ER + breast cancer. Bayesian False Discovery Probability was employed to assess the noteworthiness of each SNP-risk factor pairs.

RESULTS

Assuming a 1 × 10-5 prior probability of a true association for each SNP-risk factor pairs and a Bayesian False Discovery Probability < 15%, we identified two independent SNP-risk factor pairs: rs80018847(9p13)-LINGO2 and adult height in association with overall breast cancer risk (ORint = 0.94, 95% CI 0.92-0.96), and rs4770552(13q12)-SPATA13 and age at menarche for ER + breast cancer risk (ORint = 0.91, 95% CI 0.88-0.94).

CONCLUSIONS

Overall, the contribution of G×E interactions to the heritability of breast cancer is very small. At the population level, multiplicative G×E interactions do not make an important contribution to risk prediction in breast cancer.

Evaluating the distinct pleiotropic effects of omega-3 fatty acids on type 2 diabetes mellitus: a mendelian randomization study

BACKGROUND

Observational studies and conventional Mendelian randomization (MR) studies showed inconclusive evidence to support the association between omega-3 fatty acids and type 2 diabetes. We aim to evaluate the causal effect of omega-3 fatty acids on type 2 diabetes mellitus (T2DM), and the distinct intermediate phenotypes linking the two.

METHODS

Two-sample MR was performed using genetic instruments derived from a recent genome-wide association study (GWAS) of omega-3 fatty acids (N = 114,999) from UK Biobank and outcome data obtained from a large-scale T2DM GWAS (62,892 cases and 596,424 controls) in European ancestry. MR-Clust was applied to determine clustered genetic instruments of omega-3 fatty acids that influences T2DM. Two-step MR analysis was used to identify potential intermediate phenotypes (e.g. glycemic traits) that linking omega-3 fatty acids with T2DM.

RESULTS

Univariate MR showed heterogenous effect of omega-3 fatty acids on T2DM. At least two pleiotropic effects between omega-3 fatty acids and T2DM were identified using MR-Clust. For cluster 1 with seven instruments, increasing omega-3 fatty acids reduced T2DM risk (OR: 0.52, 95%CI 0.45-0.59), and decreased HOMA-IR (β = - 0.13, SE = 0.05, P = 0.02). On the contrary, MR analysis using 10 instruments in cluster 2 showed that increasing omega-3 fatty acids increased T2DM risk (OR:1.10; 95%CI 1.06-1.15), and decreased HOMA-B (β = - 0.04, SE = 0.01, P = 4.52 × 10^-5). Two-step MR indicated that increasing omega-3 fatty acid levels decreased T2DM risk via decreasing HOMA-IR in cluster 1, while increased T2DM risk via decreasing HOMA-B in cluster 2.

CONCLUSIONS

This study provides evidence to support two distinct pleiotropic effects of omega-3 fatty acids on T2DM risk influenced by different gene clusters, which could be partially explained by distinct effects of omega-3 fatty acids on insulin resistance and beta cell dysfunction. The pleiotropic feature of omega-3 fatty acids variants and its complex relationships with T2DM need to be carefully considered in future genetic and clinical studies.

The PANcreatic Disease ReseArch (PANDoRA) consortium: Ten years' experience of association studies to understand the genetic architecture of pancreatic cancer

Pancreatic cancer has an incidence that almost matches its mortality. Only a small number of risk factors and 33 susceptibility loci have been identified. so Moreover, the relative rarity of pancreatic cancer poses significant hurdles for research aimed at increasing our knowledge of the genetic mechanisms contributing to the disease. Additionally, the inability to adequately power research questions prevents small monocentric studies from being successful. Several consortia have been established to pursue a better understanding of the genetic architecture of pancreatic cancers. The Pancreatic disease research (PANDoRA) consortium is the largest in Europe. PANDoRA is spread across 12 European countries, Brazil and Japan, bringing together 29 basic and clinical research groups. In the last ten years, PANDoRA has contributed to the discovery of 25 susceptibility loci, a feat that will be instrumental in stratifying the population by risk and optimizing preventive strategies.

Genetic evidence implicating natriuretic peptide receptor-3 in cardiovascular disease risk: a Mendelian randomization study

BACKGROUND

C-type natriuretic peptide (CNP) is a known target for promoting growth and has been implicated as a therapeutic opportunity for the prevention and treatment of cardiovascular disease (CVD). This study aimed to explore the effect of CNP on CVD risk using the Mendelian randomization (MR) framework.

METHODS

Instrumental variables mimicking the effects of pharmacological intervention on CNP were identified as uncorrelated genetic variants located in the genes coding for its primary receptors, natriuretic peptide receptors-2 and 3 (NPR2 and NPR3), that associated with height. We performed MR and colocalization analyses to investigate the effects of NPR2 signalling and NPR3 function on CVD outcomes and risk factors. MR estimates were compared to those obtained when considering height variants from throughout the genome.

RESULTS

Genetically-proxied reduced NPR3 function was associated with a lower risk of CVD, with odds ratio (OR) 0.74 per standard deviation (SD) higher NPR3-predicted height, and 95% confidence interval (95% CI) 0.64-0.86. This effect was greater in magnitude than observed when considering height variants from throughout the genome. For CVD subtypes, similar MR associations for NPR3-predicted height were observed when considering the outcomes of coronary artery disease (0.75, 95% CI 0.60-0.92), stroke (0.69, 95% CI 0.50-0.95) and heart failure (0.77, 95% CI 0.58-1.02). Consideration of CVD risk factors identified systolic blood pressure (SBP) as a potential mediator of the NPR3-related CVD risk lowering. For stroke, we found that the MR estimate for NPR3 was greater in magnitude than could be explained by a genetically predicted SBP effect alone. Colocalization results largely supported the MR findings, with no evidence of results being driven by effects due to variants in linkage disequilibrium. There was no MR evidence supporting effects of NPR2 on CVD risk, although this null finding could be attributable to fewer genetic variants being identified to instrument this target.

CONCLUSIONS

This genetic analysis supports the cardioprotective effects of pharmacologically inhibiting NPR3 receptor function, which is only partly mediated by an effect on blood pressure. There was unlikely sufficient statistical power to investigate the cardioprotective effects of NPR2 signalling.

Association of exogenous factors with molecular epidemiology of Staphylococcus aureus in human oral cavity

The frequency of Staphylococcus aureus strains associated with oral cavity microbiota has prodigious consideration. Although S. aureus has been reflected as an ephemeral member of the human oral cavity microbiota, the isolation, identification, and characterization of S. aureus is important. The present study aimed to characterize S. aureus strains from the oral cavity microflora, isolation of S. aureus from the human oral cavity microbiota, and demographic information of the participants to evaluate exogenous factors associated with the presence of S. aureus and their genetic analysis linkage with different factors. The method used in this study is the isolation of oral cavity microbiomes using sheep blood agar and Mannitol salt agar. We performed antibiotic profiling with various antibiotics and genetic analysis utilizing gene-specific primers for specific genes, including nuc, mecA, pvl, agr, and coa. A significant number of S. aureus isolates were found in the oral cavity of humans 18/84 (21.42%), and all 18 strains tested positive for the confirmatory nuc gene. Antibiotic resistance-conferring gene mecA was positive in 10 (55.6%) isolates. It was found that the occurrence of pvl, agr, and coagulase (coa) genes was 9 (50%), 6 (33.33%), and 10 (55.6%), respectively. The genetic analysis reported that significant associations were present between male and mecA gene (P = 0.03) and coa (P = 0.03), smokers with the occurrence of mecA (P = 0.02), agr (P = 0.048) and coa (P = 0.02) genes. Likewise, the association of antibiotic usage was significantly found with mecA (P = 0.02), coa (P = 0.02); however, the individuals who have taken orthodontic treatment recently have a significant association with agr (P = 0.017). The use of mouth rinse was significantly associated with the prevalence of the pvl gene (P = 0.01), and tooth brushing frequency and inflammation of the buccal cavity were also statistically significant in relation to pvl gene prevalence (P = 0.02, 0.00, respectively). Moreover, calories and weight-controlled diet were significantly associated with mecA, agr, and highly significant with coa (P = 0.02, 0.048, 0.000), so all P < 0.05, and no significant association was found between the socioeconomic status of individuals with aforementioned analyzed genes.

Current ethical and social issues in epidemiology

PURPOSE

The American College of Epidemiology held its 2021 Annual Meeting virtually, September 8-10, with a conference theme of 'From Womb to Tomb: Insights from Health Emergencies'. The American College of Epidemiology Ethics Committee hosted a symposium session in recognition of the ethical and social challenges brought to light by the coronavirus disease 2019 pandemic and on the occasion of the publication of the third edition of the classic text, Ethics and Epidemiology. The American College of Epidemiology Ethics Committee invited the book editor and contributing authors to present at the symposium session titled 'Current Ethical and Social Issues in Epidemiology.' The purpose of this paper is to further highlight the ethical challenges and presentations.

METHODS

Three speakers with expertise in ethics, health law, health policy, global health, health information technology, and translational research in epidemiology and public health were selected to present on the social and ethical issues in the current landscape. Dr. S Coughlin presented on the 'Ethical and Social Issues in Epidemiology', Dr. L Beskow presented on 'Ethical Challenges in Genetic Epidemiology', and Dr. K Goodman presented on the 'Ethics of Health Informatics'.

RESULTS

New digital sources of data and technologies are driving the ethical challenges and opportunities in epidemiology and public health as it relates to the three emerging topic areas identified: (1) digital epidemiology, (2) genetic epidemiology, and (3) health informatics. New complexities such as the reliance on social media to control infectious disease outbreaks and the introduction of computing advancements are requiring re-evaluation of traditional bioethical frameworks for epidemiology research and public health practice. We identified several cross-cutting ethical and social issues related to informed consent, benefits, risks and harms, and privacy and confidentiality and summarized these alongside more nuanced ethical considerations such as algorithmic bias, group harms related to data (mis)representation, risks of misinformation, return of genomic research results, maintaining data security, and data sharing. We offered an integrated synthesis of the stages of epidemiology research planning and conduct with the ethical issues that are most relevant in these emerging topic areas.

CONCLUSIONS

New realities exist for epidemiology and public health as professional groups who are faced with addressing population health, and especially given the recent pandemic and the widespread use of digital tools and technologies. Many ethical issues can be understood in the context of existing ethical frameworks; however, they have yet to be clearly identified or connected with the new technical and methodological applications of digital tools and technologies currently in use for epidemiology research and public health practice. To address current ethical challenges, we offered a synthesis of traditional ethical principles in public health science alongside more nuanced ethical considerations for emerging technologies and aligned these with lifecycle stages of epidemiology research. By critically reflecting on the impact of new digital sources of data and technologies on epidemiology research and public health practice, specifically in the control of infectious outbreaks, we offered insights on cultivating these new areas of professional growth while striving to improve population health.

The epidemiology of Waldenström macroglobulinemia

Waldenström macroglobulinemia (WM) is a rare subtype of non-Hodgkin lymphoma characterized by the presence of lymphoplasmacytic lymphoma (LPL) in the bone marrow accompanied by a monoclonal immunoglobulin type M (IgM) in the serum. WM was first described only 80 years ago and became reportable in the US as a malignancy in 1988. Very little systematic research was conducted prior to 2000 to characterize incidence, clinical characteristics, risk factors or diagnostic and prognostic criteria, and there were essentially no WM-specific clinical interventional trials. Since the inaugural meeting of the International Workshop in Waldenström's Macroglobulinemia (IWWM) in 2000, WM has become the focus of a steadily increasing and productive body of research, engaging a growing number of investigators throughout the world. This introductory overview provides summary of the current understanding of the epidemiology of WM/LPL as a backdrop for a series of consensus panel recommendations arising from research presented at the 11th IWWM.

An integrated genome and phenome-wide association study approach to understanding Alzheimer's disease predisposition

Genome-wide association studies (GWAS) have identified common single nucleotide polymorphisms (SNPs) that increase late-onset Alzheimer's disease (LOAD) risk. To identify additional LOAD-associated variants and provide insight into underlying disease biology, we performed a phenome-wide association study on 23 known LOAD-associated SNPs and 4:1 matched control SNPs using UK Biobank data. LOAD-associated SNPs were significantly enriched for associations with 8/778 queried traits, including 3 platelet traits. The strongest enrichment was for platelet distribution width (PDW) (p = 1.2 × 10-5), but increased PDW was not associated with LOAD susceptibility in Mendelian randomization analysis. Of 384 PDW-associated SNPs identified by prior GWAS, 36 were nominally associated with LOAD risk (17,008 cases; 37,154 controls) and 5 survived false-discovery rate correction. Associations confirmed known LOAD risk loci near PICALM, CD2AP, SPI1, and NDUFAF6, and identified a novel risk locus in epidermal growth factor receptor. Integrating GWAS and phenome-wide association study data reveals substantial pleiotropy between genetic determinants of LOAD and of platelet morphology, and for the first time implicates epidermal growth factor receptor - a mediator of β-amyloid toxicity - in Alzheimer's disease susceptibility.

Lack of Familial Aggregation of the "Essential Tremor-Plus" Phenotype in Familial Essential Tremor

BACKGROUND

Essential tremor (ET) is a highly prevalent neurological disease that frequently runs in families. A recent and controversial proposal is to separate ET patients into two distinct groups - ET versus ET-plus. If this were a valid construct, one would expect in familial aggregation studies to observe that ET-plus would cluster in some families yet be absent in others, rather than being randomly distributed across families. We examined whether there is evidence of familial aggregation of ET-plus.

METHODS

Probands (n = 84 [56 ET-plus and 28 ET]) and their first- and second-degree relatives (n = 182 and 48) enrolled in a genetics study. χ2 and generalized estimating equations (GEE) tested associations between probands' ET-plus status and the ET-plus status of their relatives.

RESULTS

χ2 analyses revealed that ET-plus was no more prevalent in relatives of probands diagnosed with ET-plus than in relatives of probands diagnosed with ET, p > 0.05. Restricting relatives to first-degree relatives similarly did not detect a significant association (p = 0.88). GEE yielded similar results (respective p's = 0.39 and 0.81).

CONCLUSION

The data demonstrate that ET-plus does not seem to aggregate in families. As such, they do not lend support to the notion that ET-plus is a valid biological construct.

Hepatic decompensation is accelerated in patients with cirrhosis and alpha-1 antitrypsin Pi∗MZ genotype

Background & Aims

Alpha-1 antitrypsin deficiency is caused by mutations in SERPINA1, most commonly homozygosity for the Pi∗Z variant, and can present as liver disease. While heterozygosity for Pi∗Z (Pi∗MZ) is linked to increased risk of cirrhosis, whether the Pi∗MZ genotype is associated with an increased rate of decompensation among patients who already have compensated cirrhosis is not known.

Methods

This was a retrospective study of Michigan Genomics Initiative participants with baseline compensated cirrhosis. The primary predictors were Pi∗MZ or Pi∗MS genotype (vs. Pi∗MM). The primary outcomes were hepatic decompensation with ascites, hepatic encephalopathy, or variceal bleeding, or the combined endpoint of liver-related death or liver transplant, both modeled with Fine-Gray competing risk models.

Results

We included 576 patients with baseline compensated cirrhosis who had undergone genotyping, of whom 474 had Pi∗MM, 49 had Pi∗MZ, and 52 had Pi∗MS genotypes. Compared to Pi∗MM genotype, Pi∗MZ was associated with increased rates of hepatic decompensation (hazard ratio 1.81; 95% CI 1.22-2.69; p = 0.003) and liver transplant or liver-related death (hazard ratio 2.07; 95% CI 1.21-3.52; p = 0.078). These associations remained significant after adjustment for severity of underlying liver disease, and were robust across subgroup analyses based on etiology, sex, obesity, and diabetes status. Pi∗MS was not associated with decompensation or death/transplantation.

Conclusions

The SERPINA1 Pi∗MZ genotype is associated with an increased rate of hepatic decompensation and decreased transplant-free survival among patients with baseline compensated cirrhosis.

Lay summary

There is a mutation in the gene SERPINA1 called Pi∗MZ which increases risk of liver scarring (cirrhosis); however, it is not known what effect Pi∗MZ has if someone already has cirrhosis. In this study, we found that people who had cirrhosis and Pi∗MZ developed complications from cirrhosis faster than those who did not have the mutation.

Breast cancer risks associated with missense variants in breast cancer susceptibility genes

BACKGROUND

Protein truncating variants in ATM, BRCA1, BRCA2, CHEK2, and PALB2 are associated with increased breast cancer risk, but risks associated with missense variants in these genes are uncertain.

METHODS

We analyzed data on 59,639 breast cancer cases and 53,165 controls from studies participating in the Breast Cancer Association Consortium BRIDGES project. We sampled training (80%) and validation (20%) sets to analyze rare missense variants in ATM (1146 training variants), BRCA1 (644), BRCA2 (1425), CHEK2 (325), and PALB2 (472). We evaluated breast cancer risks according to five in silico prediction-of-deleteriousness algorithms, functional protein domain, and frequency, using logistic regression models and also mixture models in which a subset of variants was assumed to be risk-associated.

RESULTS

The most predictive in silico algorithms were Helix (BRCA1, BRCA2 and CHEK2) and CADD (ATM). Increased risks appeared restricted to functional protein domains for ATM (FAT and PIK domains) and BRCA1 (RING and BRCT domains). For ATM, BRCA1, and BRCA2, data were compatible with small subsets (approximately 7%, 2%, and 0.6%, respectively) of rare missense variants giving similar risk to those of protein truncating variants in the same gene. For CHEK2, data were more consistent with a large fraction (approximately 60%) of rare missense variants giving a lower risk (OR 1.75, 95% CI (1.47-2.08)) than CHEK2 protein truncating variants. There was little evidence for an association with risk for missense variants in PALB2. The best fitting models were well calibrated in the validation set.

CONCLUSIONS

These results will inform risk prediction models and the selection of candidate variants for functional assays and could contribute to the clinical reporting of gene panel testing for breast cancer susceptibility.

Combining evidence from Mendelian randomization and colocalization: Review and comparison of approaches

Mendelian randomization and colocalization are two statistical approaches that can be applied to summarized data from genome-wide association studies (GWASs) to understand relationships between traits and diseases. However, despite similarities in scope, they are different in their objectives, implementation, and interpretation, in part because they were developed to serve different scientific communities. Mendelian randomization assesses whether genetic predictors of an exposure are associated with the outcome and interprets an association as evidence that the exposure has a causal effect on the outcome, whereas colocalization assesses whether two traits are affected by the same or distinct causal variants. When considering genetic variants in a single genetic region, both approaches can be performed. While a positive colocalization finding typically implies a non-zero Mendelian randomization estimate, the reverse is not generally true: there are several scenarios which would lead to a non-zero Mendelian randomization estimate but lack evidence for colocalization. These include the existence of distinct but correlated causal variants for the exposure and outcome, which would violate the Mendelian randomization assumptions, and a lack of strong associations with the outcome. As colocalization was developed in the GWAS tradition, typically evidence for colocalization is concluded only when there is strong evidence for associations with both traits. In contrast, a non-zero estimate from Mendelian randomization can be obtained despite only nominally significant genetic associations with the outcome at the locus. In this review, we discuss how the two approaches can provide complementary information on potential therapeutic targets.

Community-based Investigation of the Risk Factors for Cardiovascular Diseases in Ibadan and suburbs (COMBAT-CVDs): Design and Methods

Africa is gradually becoming the epicentre for the burden of cardiovascular diseases (CVDs) worldwide, and community-based data alluding to the pattern and dynamics of escalating epidemiological thresholds of CVDs among indigenous Africans are limited. This manuscript focuses on the design and methods of Community-based Investigation of the Risk Factors for Cardiovascular Diseases in Ibadan and suburbs (COMBAT-CVDs), an ongoing community-based door-to-door study assessing the profile, burden and dynamics of CVDs risk factors among residents of Ibadan and suburbs. COMBAT-CVDs is a cohort of community-dwelling indigenous Africans, males and females, ≥18years from ten communities in Ibadan, Nigeria. The recruitment of participants for the first wave (W₀) started in 2020, covering; questionnaire administration and physical examination. The World Health Organization's STEPS Instrument for Chronic Disease Risk Factor Surveillance was used for data collection. Data were collected on sociodemographic, socioeconomic and lifestyle-related characteristics, history of CVDs, stress, depression and sleep quality. Also, anthropometric and blood pressure measures were conducted by trained personnel using standard operating procedures and instruments. Data collection for the second wave is underway, and the collection of blood and other biological samples for genetic epidemiology is planned, subject to availability of funds. For the W₀ recruitment, a total of 3638 community-dwelling adults (males - 54.6% and females - 45.4%) participated with a ≥99.7% response rate. The COMBAT-CVDs will likely provide novel data, insightful characterization of CVDs risk factors and evidence for context-specific and culturally relevant interventions for the community-based prevention and management of CVDs among Africans in this setting.

A Regional Burden of Sequence-Level Variation in the 22q11.2 Region Influences Schizophrenia Risk and Educational Attainment

BACKGROUND

Genomic loci where recurrent pathogenic copy number variants are associated with psychiatric phenotypes in the population may also be sensitive to the collective impact of multiple functional low-frequency single nucleotide variants (SNVs).

METHODS

We examined the cumulative impact of low-frequency, functional SNVs within the 22q11.2 region on schizophrenia risk in a discovery cohort and an independent replication cohort (N = 1933 and N = 11,128, respectively), as well as the impact on educational attainment (EA) in a third, independent, general population cohort (N = 2081). In the discovery and EA cohorts, SNVs were identified using genotyping arrays; in the replication cohort, whole-exome sequencing was available. For verification, we compared the regional SNV count for schizophrenia cases in the discovery cohort with a normative count distribution derived from a large population dataset (N = 26,500) using bootstrap procedures.

RESULTS

In both schizophrenia cohorts, an increased regional SNV burden (≥4 low-frequency SNVs) in the 22q11.2 region was associated with schizophrenia (discovery cohort: odds ratio = 7.48, p = .039; replication cohort: odds ratio = 1.92, p = .004). In the EA cohort, an increased regional SNV burden at 22q11.2 was associated with decreased EA (odds ratio = 4.65, p = .049). Comparing the SNV count for schizophrenia cases with a normative distribution confirmed the unique nature of the distribution for schizophrenia cases (p = .002).

CONCLUSIONS

In the general population, an increased burden of low-frequency, functional SNVs in the 22q11.2 region is associated with schizophrenia risk and a decrease in EA. These findings suggest that in addition to structural variation, a cumulative regional burden of low-frequency, functional SNVs in the 22q11.2 region can also have a relevant phenotypic impact.

Leveraging pleiotropic association using sparse group variable selection in genomics data

Background

Genome-wide association studies (GWAS) have identified genetic variants associated with multiple complex diseases. We can leverage this phenomenon, known as pleiotropy, to integrate multiple data sources in a joint analysis. Often integrating additional information such as gene pathway knowledge can improve statistical efficiency and biological interpretation. In this article, we propose statistical methods which incorporate both gene pathway and pleiotropy knowledge to increase statistical power and identify important risk variants affecting multiple traits.

Methods

We propose novel feature selection methods for the group variable selection in multi-task regression problem. We develop penalised likelihood methods exploiting different penalties to induce structured sparsity at a gene (or pathway) and SNP level across all studies. We implement an alternating direction method of multipliers (ADMM) algorithm for our penalised regression methods. The performance of our approaches are compared to a subset based meta analysis approach on simulated data sets. A bootstrap sampling strategy is provided to explore the stability of the penalised methods.

Results

Our methods are applied to identify potential pleiotropy in an application considering the joint analysis of thyroid and breast cancers. The methods were able to detect eleven potential pleiotropic SNPs and six pathways. A simulation study found that our method was able to detect more true signals than a popular competing method while retaining a similar false discovery rate.

Conclusion

We developed feature selection methods for jointly analysing multiple logistic regression tasks where prior grouping knowledge is available. Our method performed well on both simulation studies and when applied to a real data analysis of multiple cancers.

GABAA subunit single nucleotide polymorphisms show sex-specific association to alcohol consumption and mental distress in a Norwegian population-based sample

Little is known about genetic influences on the relationship between alcohol consumption and mental distress in the general population, where the majority report consumption and distress far below diagnostic thresholds. This study investigated single nucleotide polymorphisms (SNPs) from candidate gene studies on alcohol use disorder and depressive disorders, for association with alcohol consumption and with mental distress in a population-based sample from the Cohort of Norway (n = 1978, 49% women). The relationship between alcohol consumption and mental distress was further examined for genotype modification. There was a positive correlation between mental distress and alcohol consumption in men, as well as an association between SNPs and mental distress in men (GABRG1, GABRA2, DRD2, ANKK1, MTHFR) and women (CHRM2, MTHFR) and between SNPs and alcohol consumption in women (GABRA2, MTHFR). No modification by SNP genotype was found on the relationship between alcohol consumption and mental distress. The association between mental distress and GABRG1 in men remained significant after correcting for multiple comparisons. The results indicate that alcohol consumption and mental distress are associated in the general population even at levels below clinical thresholds and point to SNPs in genes related to GABAergic signalling for level of mental distress in men.

Genetic epidemiology of autoinflammatory disease variants in Indian population from 1029 whole genomes

Background

Autoinflammatory disorders are the group of inherited inflammatory disorders caused due to the genetic defect in the genes that regulates innate immune systems. These have been clinically characterized based on the duration and occurrence of unprovoked fever, skin rash, and patient’s ancestry. There are several autoinflammatory disorders that are found to be prevalent in a specific population and whose disease genetic epidemiology within the population has been well understood. However, India has a limited number of genetic studies reported for autoinflammatory disorders till date. The whole genome sequencing and analysis of 1029 Indian individuals performed under the IndiGen project persuaded us to perform the genetic epidemiology of the autoinflammatory disorders in India.

Results

We have systematically annotated the genetic variants of 56 genes implicated in autoinflammatory disorder. These genetic variants were reclassified into five categories (i.e., pathogenic, likely pathogenic, benign, likely benign, and variant of uncertain significance (VUS)) according to the American College of Medical Genetics and Association of Molecular pathology (ACMG-AMP) guidelines. Our analysis revealed 20 pathogenic and likely pathogenic variants with significant differences in the allele frequency compared with the global population. We also found six causal founder variants in the IndiGen dataset belonging to different ancestry. We have performed haplotype prediction analysis for founder mutations haplotype that reveals the admixture of the South Asian population with other populations. The cumulative carrier frequency of the autoinflammatory disorder in India was found to be 3.5% which is much higher than reported.

Conclusion

With such frequency in the Indian population, there is a great need for awareness among clinicians as well as the general public regarding the autoinflammatory disorder. To the best of our knowledge, this is the first and most comprehensive population scale genetic epidemiological study being reported from India.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-021-00268-2.

Carrier screening in the Mexican Jewish community using a pan-ethnic expanded carrier screening NGS panel

PURPOSE

The Mexican Jewish community (MJC) is a previously uncharacterized, genetically isolated group composed of Ashkenazi and Sephardi-Mizrahi Jews who migrated in the early 1900s. We aimed to determine the heterozygote frequency of disease-causing variants in 302 genes in this population.

METHODS

We conducted a cross-sectional study of the MJC involving individuals representing Ashkenazi Jews, Sephardi-Mizrahi Jews, or mixed-ancestry Jews. We offered saliva-based preconception pan-ethnic expanded carrier screening, which examined 302 genes. We analyzed heterozygote frequencies of pathogenic/likely pathogenic variants and compared them with those in the Genome Aggregation Database (gnomAD).

RESULTS

We recruited 208 participants. The carrier screening results showed that 72.1% were heterozygous for at least 1 severe disease-causing variant in 1 of the genes analyzed. The most common genes with severe disease-causing variants were CFTR (16.8% of participants), MEFV (11.5%), WNT10A (6.7%), and GBA (6.7%). The allele frequencies were compared with those in the gnomAD; 85% of variant frequencies were statistically different from those found in gnomAD (P <.05). Finally, 6% of couples were at risk of having a child with a severe disorder.

CONCLUSION

The heterozygote frequency of at least 1 severe disease-causing variant in the MJC was 72.1%. The use of carrier screening in the MJC and other understudied populations could help parents make more informed decisions.

Characterization of key amino acid substitutions and dynamics of the influenza virus H3N2 hemagglutinin

The annual epidemics of seasonal influenza is partly attributed to the continued virus evolution. It is challenging to evaluate the effect of influenza virus mutations on evading population immunity. In this study, we introduce a novel statistical and computational approach to measure the dynamic molecular determinants underlying epidemics using effective mutations (EMs), and account for the time of waning mutation advantage against herd immunity by measuring the effective mutation periods (EMPs). Extensive analysis is performed on the sequencing and epidemiology data of H3N2 epidemics in ten regions from season to season. We systematically identified 46 EMs in the hemagglutinin (HA) gene, in which the majority were antigenic sites. Eight EMs were located in immunosubdominant stalk domain, an important target for developing broadly reactive antibodies. The EMs might provide timely information on key substitutions for influenza vaccines antigen design. The EMP suggested that major genetic variants of H3N2 circulated in Southeast Asia for an average duration of 4.5 years (SD 2.4) compared to a significantly shorter 2.0 years (SD 1.0) in temperate regions. The proposed method bridges population epidemics and molecular characteristics of infectious diseases, and would find broad applications in various pathogens mutation estimations.

Genetic Overlap Profiles of Cognitive Ability in Psychotic and Affective Illnesses: A Multisite Study of Multiplex Pedigrees

BACKGROUND

Cognitive impairment is a key feature of psychiatric illness, making cognition an important tool for exploring of the genetics of illness risk. It remains unclear which measures should be prioritized in pleiotropy-guided research. Here, we generate profiles of genetic overlap between psychotic and affective disorders and cognitive measures in Caucasian and Hispanic groups.

METHODS

Data were from 4 samples of extended pedigrees (N = 3046). Coefficient of relationship analyses were used to estimate genetic overlap between illness risk and cognitive ability. Results were meta-analyzed.

RESULTS

Psychosis was characterized by cognitive impairments on all measures with a generalized profile of genetic overlap. General cognitive ability shared greatest genetic overlap with psychosis risk (average endophenotype ranking value [ERV] across samples from a random-effects meta-analysis = 0.32), followed by verbal memory (ERV = 0.24), executive function (ERV = 0.22), and working memory (ERV = 0.21). For bipolar disorder, there was genetic overlap with processing speed (ERV = 0.05) and verbal memory (ERV = 0.11), but these were confined to select samples. Major depressive disorder was characterized by enhanced working and face memory performance, as reflected in significant genetic overlap in 2 samples.

CONCLUSIONS

There is substantial genetic overlap between risk for psychosis and a range of cognitive abilities (including general intelligence). Most of these effects are largely stable across of ascertainment strategy and ethnicity. Genetic overlap between affective disorders and cognition, on the other hand, tends to be specific to ascertainment strategy, ethnicity, and cognitive test battery.

Assessment of causal effects of physical activity on neurodegenerative diseases: A Mendelian randomization study

BACKGROUND

Physical activity has been hypothesized to play a protective role in neurodegenerative diseases. However, effect estimates previously derived from observational studies were prone to confounding or reverse causation.

METHODS

We performed a two-sample Mendelian randomization (MR) analysis to explore the causal association of accelerometer-measured physical activity with 3 common neurodegenerative diseases: Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). We selected genetic instrumental variants reaching genome-wide significance (p < 5 × 10^-8) from 2 largest meta-analyses of about 91,100 UK Biobank participants. Summary statistics for AD, PD, and ALS were retrieved from the up-to-date studies in European ancestry led by the international consortia. The random-effect, inverse-variance weighted MR was employed as the primary method, while MR pleiotropy residual sum and outlier (MR-PRESSO), weighted median, and MR-Egger were implemented as sensitivity tests. All statistical analyses were performed using the R programming language (Version 3.6.1; R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

Primary MR analysis and replication analysis utilized 5 and 8 instrumental variables, which explained 0.2% and 0.4% variance in physical activity, respectively. In each set, one variant at 17q21 was significantly associated with PD, and MR sensitivity analyses indicated them it as an outlier and source of heterogeneity and pleiotropy. Primary results with the removal of outlier variants suggested odds ratios (ORs) of neurodegenerative diseases per unit increase in objectively measured physical activity were 1.52 for AD (95% confidence interval (95%CI): 0.88-2.63, p = 0.13) and 3.35 for PD (95%CI: 1.32-8.48, p = 0.01), while inconsistent results were shown in the replication set for AD (OR = 1.06, 95%CI: 1.01-1.12, p = 0.02) and PD (OR = 0.99, 95%CI: 0.88-0.12, p = 0.97). Similarly, the beneficial effect of physical activity on ALS (OR = 0.51, 95%CI: 0.29-0.91, p = 0.02) was not confirmed in the replication analysis (OR = 0.96, 95%CI: 0.91-1.02, p = 0.22).

CONCLUSION

Genetically predicted physical activity was not robustly associated with risk of neurodegenerative disorders. Triangulating evidence across other studies is necessary in order to elucidate whether enhancing physical activity is an effective approach in preventing the onset of AD, PD, or ALS.

Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study

BACKGROUND

To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups.

METHODS

Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina's Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping.

RESULTS

Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects.

CONCLUSIONS

This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.

An exploration of the genetic epidemiology of non-suicidal self-harm and suicide attempt

BACKGROUND

Empirical evidence supporting the distinction between suicide attempt (SA) and non-suicidal self-harm (NSSH) is lacking. Although NSSH is a risk factor for SA, we do not currently know whether these behaviours lie on a continuum of severity, or whether they are discrete outcomes with different aetiologies. We conducted this exploratory genetic epidemiology study to investigate this issue further.

METHODS

We explored the extent of genetic overlap between NSSH and SA in a large, richly-phenotyped cohort (the Avon Longitudinal Study of Parents and Children; N = 4959), utilising individual-level genetic and phenotypic data to conduct analyses of genome-wide complex traits and polygenic risk scores (PRS).

RESULTS

The single nucleotide polymorphism heritability of NSSH was estimated to be 13% (SE 0.07) and that of SA to be 0% (SE 0.07). Of the traits investigated, NSSH was most strongly correlated with higher IQ (rG = 0.31, SE = 0.22), there was little evidence of high genetic correlation between NSSH and SA (rG = - 0.1, SE = 0.54), likely due to the low heritability estimate for SA. The PRS for depression differentiated between those with NSSH and SA in multinomial regression. The optimal PRS prediction model for SA (Nagelkerke R2 0.022, p < 0.001) included ADHD, depression, income, anorexia and neuroticism and explained more variance than the optimal prediction model for NSSH (Nagelkerke R2 0.010, p < 0.001) which included ADHD, alcohol consumption, autism spectrum conditions, depression, IQ, neuroticism and suicide attempt.

CONCLUSIONS

Our findings suggest that SA does not have a large genetic component, and that although NSSH and SA are not discrete outcomes there appears to be little genetic overlap between the two. The relatively small sample size and resulting low heritability estimate for SA was a limitation of the study. Combined with low heritability estimates, this implies that family or population structures in SA GWASs may contribute to signals detected.

Colocalization of association signals at nicotinic acetylcholine receptor genes between schizophrenia and smoking traits

BACKGROUND

Epidemiological data suggest that smoking may be a risk factor for schizophrenia (SCZ), but more evidence is needed. Two regions coding nicotinic acetylcholine receptor (nAchR) subunits, atCHRNA2 and the CHRNA5/A3/B4 cluster, were associated with SCZ in genome-wide association studies (GWAS). Additionally, a signal at CHRNA4 is near significance. CHRNA2 was also associated with cannabis use disorder (CUD). These regions were also associated with smoking behaviors. If tobacco is a risk factor, the GWAS signals at smoking behaviors and SCZ have to be due to the same causal variants, i.e. they have to colocalize, although colocalization does not necessarily imply causality. Here, we present colocalization analysis at these loci between SCZ and smoking behaviors.

METHODS

The Bayesian approach implemented in coloc was used to check for posterior probability of colocalization versus independent signals at the three loci with some evidence of association with SCZ and smoking behaviors, using GWAS summary statistics. Colocalization was also assessed for positive control traits and CUD. Three different sensibility analyses were used to confirm the results. A visualization tool, LocusCompare, was used to facilitate interpretation of the coloc results.

RESULTS

Evidence for colocalization of GWAS signals between SCZ and smoking behaviors was found for CHRNA2. Evidence for independent causal variants was found for the other two loci. CUD GWAS signal at CHRNA2 colocalizes with SCZ and smoking behaviors.

CONCLUSIONS

Overall, the results indicate that the association between some nAchR subunit genes and SCZ cannot be solely explained by their effect on smoking behaviors.

Inference of a causal relation between low-density lipoprotein cholesterol and hypertension using mendelian randomization analysis

BACKGROUND

It is known in some studies that higher the LDL-C, the greater the risk of developing cardiovascular disease. However, studies of the causal effects between LDL-C and hypertension are limited by their observational study design, and genetic epidemiology studies of associations between LDL-C and hypertension are lacking, as are studies using data for Koreans. In this study, we confirmed the causal effect of LDL-C on hypertension using Korean chip data.

METHOD

The epidemiology and genotype data were collected from the Korean Genome and Epidemiology Study conducted by the Korea National Institute of Health and covered 20,701 subjects. Single-nucleotide polymorphisms associated with LDL-C were selected (p-value < 5 × 10^- 8) from the Global Lipids Genetics Consortium database, and Mendelian randomization analysis (MRA) was performed with counted genetic risk scores and weighted genetic risk scores (WGRSs) for 24 single-nucleotide polymorphisms.

RESULT

The assumptions for MRA were statistically confirmed, and WGRSs showed a strong association with LDL-C. Interestingly, while the relationship between LDL-C and hypertension was not statistically significant in the observational study, MRA study demonstrated that the risk of hypertension increased as LDL-C increased in both men and women.

CONCLUSIONS

The results of this study confirmed that the relationship between LDL-C and hypertension is greatly influenced by genetic information.

Penalized partial least squares for pleiotropy

BACKGROUND

The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level.

RESULTS

Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers.

CONCLUSION

The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

Clinical laboratory test-wide association scan of polygenic scores identifies biomarkers of complex disease

BACKGROUND

Clinical laboratory (lab) tests are used in clinical practice to diagnose, treat, and monitor disease conditions. Test results are stored in electronic health records (EHRs), and a growing number of EHRs are linked to patient DNA, offering unprecedented opportunities to query relationships between genetic risk for complex disease and quantitative physiological measurements collected on large populations.

METHODS

A total of 3075 quantitative lab tests were extracted from Vanderbilt University Medical Center's (VUMC) EHR system and cleaned for population-level analysis according to our QualityLab protocol. Lab values extracted from BioVU were compared with previous population studies using heritability and genetic correlation analyses. We then tested the hypothesis that polygenic risk scores for biomarkers and complex disease are associated with biomarkers of disease extracted from the EHR. In a proof of concept analyses, we focused on lipids and coronary artery disease (CAD). We cleaned lab traits extracted from the EHR performed lab-wide association scans (LabWAS) of the lipids and CAD polygenic risk scores across 315 heritable lab tests then replicated the pipeline and analyses in the Massachusetts General Brigham Biobank.

RESULTS

Heritability estimates of lipid values (after cleaning with QualityLab) were comparable to previous reports and polygenic scores for lipids were strongly associated with their referent lipid in a LabWAS. LabWAS of the polygenic score for CAD recapitulated canonical heart disease biomarker profiles including decreased HDL, increased pre-medication LDL, triglycerides, blood glucose, and glycated hemoglobin (HgbA1C) in European and African descent populations. Notably, many of these associations remained even after adjusting for the presence of cardiovascular disease and were replicated in the MGBB.

CONCLUSIONS

Polygenic risk scores can be used to identify biomarkers of complex disease in large-scale EHR-based genomic analyses, providing new avenues for discovery of novel biomarkers and deeper understanding of disease trajectories in pre-symptomatic individuals. We present two methods and associated software, QualityLab and LabWAS, to clean and analyze EHR labs at scale and perform a Lab-Wide Association Scan.

Statistical power in COVID-19 case-control host genomic study design

The identification of genetic variation that directly impacts infection susceptibility to SARS-CoV-2 and disease severity of COVID-19 is an important step towards risk stratification, personalized treatment plans, therapeutic, and vaccine development and deployment. Given the importance of study design in infectious disease genetic epidemiology, we use simulation and draw on current estimates of exposure, infectivity, and test accuracy of COVID-19 to demonstrate the feasibility of detecting host genetic factors associated with susceptibility and severity in published COVID-19 study designs. We demonstrate that limited phenotypic data and exposure/infection information in the early stages of the pandemic significantly impact the ability to detect most genetic variants with moderate effect sizes, especially when studying susceptibility to SARS-CoV-2 infection. Our insights can aid in the interpretation of genetic findings emerging in the literature and guide the design of future host genetic studies.

Gene polymorphisms in calcium-calmodulin pathway: Focus on cardiovascular disease

Cardiovascular disease is the leading cause of death in industrialized countries and affects an increasing number of people. Several risk factors play an important role in the etiology of this disease, such as an unhealthy lifestyle. It is increasingly clear that genetic factors influencing the molecular basis of excitation-contraction mechanisms in the heart could contribute to modify the individual's risk. Thanks to the progress that has been made in understanding calcium signaling in the heart, it is assumed that calmodulin can play a crucial role in the excitation-contraction coupling. In fact, calmodulin (CaM) binds calcium and consequently regulates calcium channels. Several works show how some polymorphic variants can be considered predisposing factors to complex pathologies. Therefore, we hypothesize that the identification of polymorphic variants of proteins involved in the CaM pathway could be important for understanding how genetic traits can influence predisposition to myocardial infarction. This review considers each pathway of the three different isoforms of calmodulin (CaM1; CaM2; CaM3) and focuses on some common proteins involved in the three pathways, with the aim of analyzing the polymorphisms studied in the literature and understanding if they are associated with cardiovascular disease.

Redundant meta-analyses are common in genetic epidemiology

OBJECTIVES

The massive growth in the publication of meta-analyses may cause redundancy and wasted efforts. We performed a metaepidemiologic study to evaluate the extent of potential redundancy in published meta-analyses in genetic epidemiology.

STUDY DESIGN AND SETTING

Using a sample of 38 index meta-analyses of genetic associations published in 2010, we retrieved additional meta-analyses that evaluated identical associations (same genetic variant and phenotype) using the Human Genome Epidemiology (HuGE) Navigator and PubMed databases. We analyzed the frequency of potential duplication and examined whether subsequent meta-analyses cited previous meta-analyses on the exact same association.

RESULTS

Based on 38 index meta-analyses, we retrieved a total of 99 duplicate meta-analyses. Only 12 (32%) of the index meta-analyses were unambiguously unique. We found a mean of 2.6 duplicates and a median of 2 duplicates per meta-analysis. In case studies, only 29-54% of previously published meta-analyses were cited by subsequent ones.

CONCLUSION

These results suggest that duplication is common in meta-analyses of genetic associations.

An analysis of genetically regulated gene expression across multiple tissues implicates novel gene candidates in Alzheimer's disease

Introduction

Genome-wide association studies (GWAS) have successfully identified multiple independent genetic loci that harbour variants associated with Alzheimer’s disease, but the exact causal genes and biological pathways are largely unknown.

Methods

To prioritise likely causal genes associated with Alzheimer’s disease, we used S-PrediXcan to integrate expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression (GTEx) study and CommonMind Consortium (CMC) with Alzheimer’s disease GWAS summary statistics. We meta-analysed the GTEx results using S-MultiXcan, prioritised disease-implicated loci using a computational fine-mapping approach, and performed a biological pathway analysis on the gene-based results.

Results

We identified 126 tissue-specific gene-based associations across 48 GTEx tissues, targeting 50 unique genes. Meta-analysis of the tissue-specific associations identified 73 genes whose expression was associated with Alzheimer’s disease. Additional analyses in the dorsolateral prefrontal cortex from the CMC identified 12 significant associations, 8 of which also had a significant association in GTEx tissues. Fine-mapping of causal gene sets prioritised gene candidates in 10 Alzheimer’s disease loci with strong evidence for causality. Biological pathway analyses of the meta-analysed GTEx data and CMC data identified a significant enrichment of Alzheimer’s disease association signals in plasma lipoprotein clearance, in addition to multiple immune-related pathways.

Conclusions

Gene expression data from brain and peripheral tissues can improve power to detect regulatory variation underlying Alzheimer’s disease. However, the associations in peripheral tissues may reflect tissue-shared regulatory variation for a gene. Therefore, future functional studies should be performed to validate the biological meaning of these associations and whether they represent new pathogenic tissues.

The Association of Aquaporin-1 Gene with Marathon Running Performance Level: a Confirmatory Study Conducted in Male Hispanic Marathon Runners

Background

Replication studies are essential for identifying credible associations between alleles and phenotypes. Validation of genotype-phenotype associations in the sports and exercise field is rare. An initial genetic association study suggested that rs1049305 (C > G) in the 3′ untranslated region (3′UTR) of the aquaporin-1 (AQP1) gene was associated with marathon running (MR) performance level in Hispanic males. To validate this finding, we conducted a replication analysis in an independent case-control sample of Hispanic male marathon runners (n = 1430; cases n = 713 and controls n = 717). A meta-analysis was utilized to test the extent of the association between the initial results and the present report. It also provided to test the heterogeneity (variation) between the two studies.

Results

The replication study showed a statistically significant (p ≤ 0.05) association between rs1049305 (C > G) of the AQP1 gene and MR performance level. Association test results using a fixed effect model for the combined, original study and the present report, yielded an odds ratio = 1.28, 95% confidence interval = 1.13–1.45, p = 0.0001. The extent of the measures of heterogeneity was Tau-squared = 0, H statistic = 1, I² statistic = 0, and Cochran’s Q test (Q = 0.29; p value 0.59), indicated the variation between studies were due to chance and not to differences in heterogeneity between the two studies. Within the limitations of the present replication, contrast of two studies and its effects on meta-analysis, the findings were robust.

Conclusion

This study successfully replicated the results of Martínez et al. (Med Sportiva 13:251-5, 2009). The meta-analysis provided further epidemiological credibility for the hypothesis of association between the DNA rs1049305 (C > G) variation in the 3′UTR of the AQP1 gene and MR running performance level in Hispanics male marathon runners. It is not precluded that a linked DNA structure in the surrounding molecular neighborhood could be of influence by been part of the overly complex phenotype of MR performance level.

Genome-wide meta-analysis identified novel variant associated with hallux valgus in Caucasians

BACKGROUND

Hallux valgus, one of the most common structural foot deformities, is highly heritable. However, previous efforts to elucidate the genetic underpinnings of hallux valgus through a genome-wide association study (GWAS) conducted in 4409 Caucasians did not identify genome-wide significant associations with hallux valgus in both gender-specific and sex-combined GWAS meta-analyses. In this analysis, we add newly available data and more densely imputed genotypes to identify novel genetic variants associated with hallux valgus.

METHODS

A total of 5925 individuals of European Ancestry were categorized into two groups: 'hallux valgus present' (n = 2314) or 'no deformity' (n = 3611) as determined by trained examiners or using the Manchester grading scale. Genotyping was performed using commercially available arrays followed by imputation to the Haplotype Reference Consortium (HRC) reference panel version 1.1. We conducted both sex-specific and sex-combined association analyses using logistic regression and generalized estimating equations as appropriate in each cohort. Results were then combined in a fixed-effects inverse-variance meta-analyses. Functional Mapping and Annotation web-based platform (FUMA) was used for positional mapping, gene and gene-set analyses.

RESULTS

We identified a novel locus in the intronic region of CLCA2 on chromosome 1, rs55807512 (OR = 0.48, p = 2.96E-09), an expression quantitative trait locus for COL24A1, a member of the collagen gene family.

CONCLUSION

In this report of the largest GWAS of hallux valgus to date, we identified a novel genome-wide significant locus for hallux valgus. Additional replication and functional follow-up will be needed to determine the functional role of this locus in hallux valgus biology.

Mendel's laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues

We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel's laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR's substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that "the hard problem of conducting high-quality, reproducible epidemiology" should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.

Elevated plasma YKL-40 and risk of infectious disease: a prospective study of 94665 individuals from the general population

OBJECTIVES

YKL-40 is an acute phase protein elevated in patients with infectious and inflammatory diseases. We tested the hypothesis that baseline elevated YKL-40 is associated with increased risk of future infectious disease in healthy individuals in the general population.

METHODS

We prospectively followed 94 665 individuals from the Danish general population for up to 23 years and analysed for plasma YKL-40 levels (n = 21 584) and CHI3L1 rs4950928 genotype (n = 94 184). Endpoints were any infection, bacterial pneumonia, urinary tract infection, skin infection, sepsis, diarrhoeal disease, and other infections.

RESULTS

For YKL-40 percentile category 91-100% versus 0-33%, the multifactorially and C-reactive protein (CRP) adjusted hazard ratios were 1.71 (95% confidence interval 1.50-1.96; p 4 × 10^-14) for any infection, 1.97 (1.64-2.37; p 4 × 10^-13) for bacterial pneumonia, 1.62 (1.24-2.11; p 0.002) for urinary tract infection, 1.74 (1.31-2.32; p 2 × 10^-4) for skin infection, 1.76 (1.25-2.46; p 0.004) for sepsis, 1.90 (1.29-2.78; p 0.002) for diarrhoeal disease and 2.71 (1.38-5.35; p 0.01) for other infections. In multifactorially and CRP-adjusted models, a twofold increase in YKL-40 was associated with increased risk of all infectious disease endpoints. Mendelian randomization did not support causality, as CHI3L1 rs4950928 was associated with 94% and 190% higher YKL-40 levels (for CG and CC versus GG genotype), but not with increased risk of any infectious disease endpoint.

DISCUSSION

Baseline elevated plasma YKL-40 was not a cause but a strong marker of increased risk of future infectious diseases in individuals in the general population.

Common polymorphic inversions at 17q21.31 and 8p23.1 associate with cancer prognosis

BACKGROUND

Chromosomal inversions are structural genetic variants where a chromosome segment changes its orientation. While sporadic de novo inversions are known genetic risk factors for cancer susceptibility, it is unknown if common polymorphic inversions are also associated with the prognosis of common tumors, as they have been linked to other complex diseases. We studied the association of two well-characterized human inversions at 17q21.31 and 8p23.1 with the prognosis of lung, liver, breast, colorectal, and stomach cancers.

RESULTS

Using data from The Cancer Genome Atlas (TCGA), we observed that inv8p23.1 was associated with overall survival in breast cancer and that inv17q21.31 was associated with overall survival in stomach cancer. In the meta-analysis of two independent studies, inv17q21.31 heterozygosity was significantly associated with colorectal disease-free survival. We found that the association was mediated by the de-methylation of cg08283464 and cg03999934, also linked to lower disease-free survival.

CONCLUSIONS

Our results suggest that chromosomal inversions are important genetic factors of tumor prognosis, likely affecting changes in methylation patterns.

Associations Between Attention-Deficit/Hyperactivity Disorder and Various Eating Disorders: A Swedish Nationwide Population Study Using Multiple Genetically Informative Approaches

BACKGROUND

Although attention-deficit/hyperactivity disorder (ADHD) and eating disorders (EDs) frequently co-occur, little is known about the shared etiology. In this study, we comprehensively investigated the genetic association between ADHD and various EDs, including anorexia nervosa (AN) and other EDs such as bulimia nervosa.

METHODS

We applied different genetically informative designs to register-based information of a Swedish nationwide population (N = 3,550,118). We first examined the familial coaggregation of clinically diagnosed ADHD and EDs across multiple types of relatives. We then applied quantitative genetic modeling in full-sisters and maternal half-sisters to estimate the genetic correlations between ADHD and EDs. We further tested the associations between ADHD polygenic risk scores and ED symptoms, and between AN polygenic risk scores and ADHD symptoms, in a genotyped population-based sample (N = 13,472).

RESULTS

Increased risk of all types of EDs was found in individuals with ADHD (any ED: odds ratio [OR] = 3.97, 95% confidence interval [CI] = 3.81, 4.14; AN: OR = 2.68, 95% CI = 2.15, 2.86; other EDs: OR = 4.66, 95% CI = 4.47, 4.87; bulimia nervosa: OR = 5.01, 95% CI = 4.63, 5.41) and their relatives compared with individuals without ADHD and their relatives. The magnitude of the associations decreased as the degree of relatedness decreased, suggesting shared familial liability between ADHD and EDs. Quantitative genetic models revealed stronger genetic correlation of ADHD with other EDs (.37, 95% CI = .31, .42) than with AN (.14, 95% CI = .05, .22). ADHD polygenic risk scores correlated positively with ED symptom measures overall and with the subscales Drive for Thinness and Body Dissatisfaction despite small effect sizes.

CONCLUSIONS

We observed stronger genetic association with ADHD for non-AN EDs than for AN, highlighting specific genetic correlation beyond a general genetic factor across psychiatric disorders.

Mendelian Randomization Analysis in Observational Epidemiology

Mendelian randomization (MR) in epidemiology is the use of genetic variants as instrumental variables (IVs) in non-experimental design to make causality of a modifiable exposure on an outcome or disease. It assesses the causal effect between risk factor and a clinical outcome. The main reason to approach MR is to avoid the problem of residual confounding. There is no association between the genotype of early pregnancy and the disease, and the genotype of an individual cannot be changed. For this reason, it results with randomly assigned case-control studies can be set by regressing the measurements. IVs in MR are used genetic variants for estimating the causality. Usually an outcome is a disease and an exposure is risk factor, intermediate phenotype which may be a biomarker. The choice of the genetic variable as IV (Z) is essential to a successful in MR analysis. MR is named 'Mendelian deconfounding' as it gives to estimate of the causality free from biases due to confounding (C). To estimate unbiased estimation of the causality of the exposure (X) on the clinically relevant outcome (Y), Z has the 3 core assumptions (A1-A3). A1) Z is independent of C; A2) Z is associated with X; and A3) Z is independent of Y given X and C; The purpose of this review provides an overview of the MR analysis and is to explain that using an IV is proposed as an alternative statistical method to estimate causal effect of exposure and outcome under controlling for a confounder.

Association of sickle cell trait with measures of cognitive function and dementia in African Americans

OBJECTIVE

The incidence and prevalence of cognitive decline and dementia are significantly higher among African Americans compared with non-Hispanic Whites. The aim of this study was to determine whether inheritance of the sickle cell trait (SCT) i.e. heterozygosity for the sickle cell mutation increases the risk of cognitive decline or dementia Among African Americans.

METHODS

We studied African American participants enrolled in the Atherosclerosis Risk in Communities study. SCT genotype at baseline and outcome data from cognitive assessments at visits 2, 4 and 5, and an MRI performed at visit 5 were analyzed for the association between SCT and risk of cognitive impairment and/or dementia.

RESULTS

There was no significant difference in risk factors profile between participants with SCT (N = 176) and those without SCT (N = 2532). SCT was not independently associated with a higher prevalence of global or domain-specific cognitive impairment at baseline or with more rapid cognitive decline. Participants with SCT had slightly lower incidence of dementia (HR = 0.63 [0.38, 1.05]). On the other hand, SCT seems to interact with the apolipoprotein E ε4 risk allele resulting in poor performance on digit symbol substitution test at baseline (z-score = -0.08, Pinteraction = 0.05) and over time (z-score = -0.12, Pinteraction = 0.04); and with diabetes mellitus leading to a moderately increased risk of dementia (HR = 2.06 [0.89, 4.78], Pinteraction = 0.01).

CONCLUSIONS

SCT was not an independent risk factor for prevalence or incidence of cognitive decline or dementia, although it may interact with and modify other putative risk factors for cognitive decline and dementia.

Methodological challenges in European ethics approvals for a genetic epidemiology study in critically ill patients: the GenOSept experience

BACKGROUND

During the set-up phase of an international study of genetic influences on outcomes from sepsis, we aimed to characterise potential differences in ethics approval processes and outcomes in participating European countries.

METHODS

Between 2005 and 2007 of the FP6-funded international Genetics Of Sepsis and Septic Shock (GenOSept) project, we asked national coordinators to complete a structured survey of research ethic committee (REC) approval structures and processes in their countries, and linked these data to outcomes. Survey findings were reconfirmed or modified in 2017.

RESULTS

Eighteen countries participated in the study, recruiting 2257 patients from 160 ICUs. National practices differed widely in terms of composition of RECs, procedures and duration of the ethics approval process. Eight (44.4%) countries used a single centralised process for approval, seven (38.9%) required approval by an ethics committee in each participating hospital, and three (16.7%) required both. Outcomes of the application process differed widely between countries because of differences in national legislation, and differed within countries because of interpretation of the ethics of conducting research in patients lacking capacity. The RECs in four countries had no lay representation. The median time from submission to final decision was 1.5 (interquartile range 1-7) months; in nine (50%) approval was received within 1 month; six took over 6 months, and in one 24 months; had all countries been able to match the most efficient approvals processes, an additional 74 months of country or institution-level recruitment would have been available. In three countries, rejection of the application by some local RECs resulted in loss of centres; and one country rejected the application outright.

CONCLUSIONS

The potential benefits of the single application portal offered by the European Clinical Trials Regulation will not be realised without harmonisation of research ethics committee practices as well as national legislation.