A polygenic risk score for alcohol-associated cirrhosis among heavy drinkers with European ancestry.

BACKGROUND: Polygenic Risk Scores (PRS) based on results from genome-wide association studies offer the prospect of risk stratification for many common and complex diseases. We developed a PRS for alcohol-associated cirrhosis by comparing single-nucleotide polymorphisms among patients with alcohol-associated cirrhosis (ALC) versus drinkers who did not have evidence of liver fibrosis/cirrhosis. METHODS: Using a data-driven approach, a PRS for ALC was generated using a meta-genome-wide association study of ALC (N=4305) and an independent cohort of heavy drinkers with ALC and without significant liver disease (N=3037). It was validated in 2 additional independent cohorts from the UK Biobank with diagnosed ALC (N=467) and high-risk drinking controls (N=8981) and participants in the Indiana Biobank Liver cohort with alcohol-associated liver disease (N=121) and controls without liver disease (N=3239). RESULTS: A 20-single-nucleotide polymorphisms PRS for ALC (PRSALC) was generated that stratified risk for ALC comparing the top and bottom deciles of PRS in the 2 validation cohorts (ORs: 2.83 [95% CI: 1.82 -4.39] in UK Biobank; 4.40 [1.56 -12.44] in Indiana Biobank Liver cohort). Furthermore, PRSALC improved the prediction of ALC risk when added to the models of clinically known predictors of ALC risk. It also stratified the risk for metabolic dysfunction -associated steatotic liver disease -cirrhosis (3.94 [2.23 -6.95]) in the Indiana Biobank Liver cohort -based exploratory analysis. CONCLUSIONS: PRSALC incorporates 20 single-nucleotide polymorphisms, predicts increased risk for ALC, and improves risk stratification for ALC compared with the models that only include clinical risk factors. This new score has the potential for early detection of heavy drinking patients who are at high risk for ALC.

Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals.

Problematic alcohol use (PAU), a trait that combines alcohol use disorder and alcohol-related problems assessed with a questionnaire, is a leading cause of death and morbidity worldwide. Here we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals (European, N = 903,147; African, N = 122,571; Latin American, N = 38,962; East Asian, N = 13,551; and South Asian, N = 1,716 ancestries). We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by a computational drug repurposing analysis. Cross-ancestry polygenic risk scores showed better performance of association in independent samples than single-ancestry polygenic risk scores. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. This study advances our knowledge of the genetic etiology of PAU, and these findings may bring possible clinical applicability of genetics insights-together with neuroscience, biology and data science-closer.

Multi-ancestry study of the genetics of problematic alcohol use in >1 million individuals.

Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. To improve our understanding of the genetics of PAU, we conducted a large cross-ancestry meta-analysis of PAU in 1,079,947 individuals. We observed a high degree of cross-ancestral similarity in the genetic architecture of PAU and identified 110 independent risk variants in within- and cross-ancestry analyses. Cross-ancestry fine-mapping improved the identification of likely causal variants. Prioritizing genes through gene expression and/or chromatin interaction in brain tissues identified multiple genes associated with PAU. We identified existing medications for potential pharmacological studies by drug repurposing analysis. Cross-ancestry polygenic risk scores (PRS) showed better performance in independent sample than single-ancestry PRS. Genetic correlations between PAU and other traits were observed in multiple ancestries, with other substance use traits having the highest correlations. The analysis of diverse ancestries contributed significantly to the findings, and fills an important gap in the literature.

All-cause and liver-related mortality risk factors in excessive drinkers: Analysis of data from the UK biobank.

BACKGROUND: High alcohol intake is associated with increased mortality. We aimed to identify factors affecting mortality in people drinking extreme amounts of alcohol. METHODS: We obtained information from the UK Biobank on approximately 500,000 participants aged 40-70 years at baseline assessment in 2006-2010. Habitual alcohol intake, lifestyle and physiological data, laboratory test results, and hospital diagnoses and death certificate data (to June 2020) for 5136 men (2.20% of male participants) and 1504 women (0.60%) who reported consuming ≥80 or ≥50 g/day, respectively, were used in survival analysis. RESULTS: Mortality hazard ratios for these excessive drinkers, compared to all other participants, were 2.02 (95% CI 1.89-2.17) for all causes, 1.89 (1.69-2.12) for any cancer, 1.87 (1.61-2.17) for any circulatory disease, and 9.40 (7.00-12.64) for any liver disease. Liver disease diagnosis or abnormal liver function tests predicted not only deaths attributed to liver disease but also those from cancers or circulatory diseases. Mortality among excessive drinkers was also associated with quantitative alcohol intake; diagnosed alcohol dependence, harmful use, or withdrawal syndrome; and current smoking at assessment. CONCLUSIONS: People with chronic excessive alcohol intake experience decreased average survival, but there is substantial variation in their mortality, with liver abnormality and alcohol dependence or other alcohol use disorders associated with a worse prognosis. Clinically, patients with these risk factors and high alcohol intake should be considered for early or intensive management. Research can usefully focus on the factors predisposing to dependence or liver abnormality.

Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors.

Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.

A genetic risk score and diabetes predict development of alcohol-related cirrhosis in drinkers.

BACKGROUND & AIMS: Only a minority of excess alcohol drinkers develop cirrhosis. We developed and evaluated risk stratification scores to identify those at highest risk. METHODS: Three cohorts (GenomALC-1: n = 1,690, GenomALC-2: n = 3,037, UK Biobank: relevant n = 6,898) with a history of heavy alcohol consumption (≥80 g/day (men), ≥50 g/day (women), for ≥10 years) were included. Cases were participants with alcohol-related cirrhosis. Controls had a history of similar alcohol consumption but no evidence of liver disease. Risk scores were computed from up to 8 genetic loci identified previously as associated with alcohol-related cirrhosis and 3 clinical risk factors. Score performance for the stratification of alcohol-related cirrhosis risk was assessed and compared across the alcohol-related liver disease spectrum, including hepatocellular carcinoma (HCC). RESULTS: A combination of 3 single nucleotide polymorphisms (SNPs) (PNPLA3:rs738409, SUGP1-TM6SF2:rs10401969, HSD17B13:rs6834314) and diabetes status best discriminated cirrhosis risk. The odds ratios (ORs) and (95% CIs) between the lowest (Q1) and highest (Q5) score quintiles of the 3-SNP score, based on independent allelic effect size estimates, were 5.99 (4.18-8.60) (GenomALC-1), 2.81 (2.03-3.89) (GenomALC-2), and 3.10 (2.32-4.14) (UK Biobank). Patients with diabetes and high risk scores had ORs of 14.7 (7.69-28.1) (GenomALC-1) and 17.1 (11.3-25.7) (UK Biobank) compared to those without diabetes and with low risk scores. Patients with cirrhosis and HCC had significantly higher mean risk scores than patients with cirrhosis alone (0.76 ± 0.06 vs. 0.61 ± 0.02, p = 0.007). Score performance was not significantly enhanced by information on additional genetic risk variants, body mass index or coffee consumption. CONCLUSIONS: A risk score based on 3 genetic risk variants and diabetes status enables the stratification of heavy drinkers based on their risk of cirrhosis, allowing for the provision of earlier preventative interventions. LAY SUMMARY: Excessive chronic drinking leads to cirrhosis in some people, but so far there is no way to identify those at high risk of developing this debilitating disease. We developed a genetic risk score that can identify patients at high risk. The risk of cirrhosis is increased >10-fold with just two risk factors - diabetes and a high genetic risk score. Risk assessment using this test could enable the early and personalised management of this disease in high-risk patients.

Blood copper and risk of cardiometabolic diseases: a Mendelian randomization study.

Observational evidence links higher blood levels of copper with higher risk of cardiovascular diseases. However, whether those associations reflect causal links or can be attributed to confounding is still not fully clear. We investigated causal effects of copper on the risk of cardiometabolic endpoints (stroke, coronary artery disease [CAD] and type 2 diabetes) and cardiometabolic risk factors in two-sample Mendelian randomization (MR) studies. The selection of genetic instruments for blood copper levels relied on meta-analysis of genome-wide association studies in three independent studies (European Prospective Investigation into Cancer and Nutrition-Potsdam study, Prospective investigation of the Vasculature in Uppsala Seniors study, Queensland Institute of Medical Research studies). For the selected instruments, outcome associations were drawn from large public genetic consortia on the respective disease endpoints (MEGASTROKE, Cardiogram, DIAGRAM) and cardiometabolic risk factors. MR results indicate an inverse association for genetically higher copper levels with risk of CAD (odds ratio [95% confidence interval] = 0.92 [0.86-0.99], P = 0.022) and systolic blood pressure (beta [standard error (SE)] = -0.238 [0.121]; P = 0.049). Multivariable MR incorporating copper and systolic blood pressure into one model suggested systolic blood pressure as mediating factor between copper and CAD risk. In contrast to previous observational evidence establishing higher blood copper levels as risk-increasing factor for cardiometabolic diseases, this study suggests that higher levels of genetically predicted copper might play a protective role for the development of CAD and systolic blood pressure.

Association and genetic overlap between clinical chemistry tests and migraine.

INTRODUCTION: In this paper, we studied several serum clinical chemistry tests of cardiovascular disease (CVD), iron deficiency anemia, liver and kidney disorders in migraine. METHODS: We first explored the association of 22 clinical chemistry tests with migraine risk in 697 migraine patients and 2722 controls. To validate and interpret association findings, cross-trait genetic analyses were conducted utilising genome-wide association study (GWAS) data comprising 23,986 to 452,264 individuals. RESULTS: Significant associations with migraine risk were identified for biomarkers of CVD risk, iron deficiency and liver dysfunction (odds ratios = 0.86-1.21; 1 × 10-4 < p < 3 × 10-2). Results from cross-trait genetic analyses corroborate the significant biomarker associations and indicate their relationship with migraine is more consistent with biological pleiotropy than causality. For example, association and genetic overlap between a lower level of HDL-C and increased migraine risk are due to shared biology rather than a causal relationship. Furthermore, additional genetic analyses revealed shared genetics among migraine, the clinical chemistry tests, and heart problems and iron deficiency anemia, but not liver disease. CONCLUSIONS: These findings highlight common biological mechanisms underlying migraine, heart problems and iron deficiency anemia and provide support for their investigation in the development of novel therapeutic and dietary interventions.

Obesity, Diabetes, Coffee, Tea, and Cannabis Use Alter Risk for Alcohol-Related Cirrhosis in 2 Large Cohorts of High-Risk Drinkers.

INTRODUCTION: Sustained high alcohol intake is necessary but not sufficient to produce alcohol-related cirrhosis. Identification of risk factors, apart from lifetime alcohol exposure, would assist in discovery of mechanisms and prediction of risk. METHODS: We conducted a multicenter case-control study (GenomALC) comparing 1,293 cases (with alcohol-related cirrhosis, 75.6% male) and 754 controls (with equivalent alcohol exposure but no evidence of liver disease, 73.6% male). Information confirming or excluding cirrhosis, and on alcohol intake and other potential risk factors, was obtained from clinical records and by interview. Case-control differences in risk factors discovered in the GenomALC participants were validated using similar data from 407 cases and 6,573 controls from UK Biobank. RESULTS: The GenomALC case and control groups reported similar lifetime alcohol intake (1,374 vs 1,412 kg). Cases had a higher prevalence of diabetes (20.5% (262/1,288) vs 6.5% (48/734), P = 2.27 × 10-18) and higher premorbid body mass index (26.37 ± 0.16 kg/m2) than controls (24.44 ± 0.18 kg/m2, P = 5.77 × 10-15). Controls were significantly more likely to have been wine drinkers, coffee drinkers, smokers, and cannabis users than cases. Cases reported a higher proportion of parents who died of liver disease than controls (odds ratio 2.25 95% confidence interval 1.55-3.26). Data from UK Biobank confirmed these findings for diabetes, body mass index, proportion of alcohol as wine, and coffee consumption. DISCUSSION: If these relationships are causal, measures such as weight loss, intensive treatment of diabetes or prediabetic states, and coffee consumption should reduce the risk of alcohol-related cirrhosis.

Genome-wide Association Study and Meta-analysis on Alcohol-Associated Liver Cirrhosis Identifies Genetic Risk Factors.

BACKGROUND AND AIMS: Only a minority of heavy drinkers progress to alcohol-associated cirrhosis (ALC). The aim of this study was to identify common genetic variants that underlie risk for ALC. APPROACH AND RESULTS: We analyzed data from 1,128 subjects of European ancestry with ALC and 614 heavy-drinking subjects without known liver disease from Australia, the United States, the United Kingdom, and three countries in Europe. A genome-wide association study (GWAS) was performed, adjusting for principal components and clinical covariates (alcohol use, age, sex, body mass index, and diabetes). We validated our GWAS findings using UK Biobank. We then performed a meta-analysis combining data from our study, the UK Biobank, and a previously published GWAS. Our GWAS found genome-wide significant risk association of rs738409 in patatin-like phospholipase domain containing 3 (PNPLA3) (odds ratio [OR] = 2.19 [G allele], P = 4.93 × 10-17 ) and rs4607179 near HSD17B13 (OR = 0.57 [C allele], P = 1.09 × 10-10 ) with ALC. Conditional analysis accounting for the PNPLA3 and HSD17B13 loci identified a protective association at rs374702773 in Fas-associated factor family member 2 (FAF2) (OR = 0.61 [del(T) allele], P = 2.56 × 10-8 ) for ALC. This association was replicated in the UK Biobank using conditional analysis (OR = 0.79, P = 0.001). Meta-analysis (without conditioning) confirmed genome-wide significance for the identified FAF2 locus as well as PNPLA3 and HSD17B13. Two other previously known loci (SERPINA1 and SUGP1/TM6SF2) were also genome-wide significant in the meta-analysis. GeneOntology pathway analysis identified lipid droplets as the target for several identified genes. In conclusion, our GWAS identified a locus at FAF2 associated with reduced risk of ALC among heavy drinkers. Like the PNPLA3 and HSD17B13 gene products, the FAF2 product has been localized to fat droplets in hepatocytes. CONCLUSIONS: Our genetic findings implicate lipid droplets in the biological pathway(s) underlying ALC.

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression.

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

Pessimism is associated with greater all-cause and cardiovascular mortality, but optimism is not protective.

Scores on an optimistic-pessimistic personality scale have been associated with mortality, but optimism and pessimism scores are separable traits and it is unclear which has effects on health or longevity. The Life Orientation Test (LOT), containing items for optimism and pessimism, was included in a twin study on health of Australians aged over 50 in 1993-1995. After a mean of 20 years, participants were matched against death information from the Australian National Death Index. 1,068 out of 2,978 participants with useable LOT scores had died. Survival analysis tested for associations between separate optimism and pessimism scores and mortality from any cause, and from cancers, cardiovascular diseases or other known causes. Age-adjusted scores on the pessimism scale were associated with all-cause and cardiovascular mortality (Hazard Ratios per 1 standard deviation unit, 95% confidence intervals and p-values 1.134, 1.065-1.207, 8.85 × 10-5 and 1.196, 1.045-1.368, 0.0093, respectively) but not with cancer deaths. Optimism scores, which were only weakly correlated with pessimism scores (age-adjusted rank correlation = - 0.176), did not show significant associations with overall or cause-specific mortality. Reverse causation (disease causing pessimism) is unlikely because in that case both cardiovascular diseases and cancers would be expected to lead to pessimism.

Genetics of Biochemical Phenotypes.

Biomarkers diagnose, predict or assess the risk of disease, and studies of the effects of genetic variation on biomarker phenotypes in the general population complement studies on patients diagnosed with disease. This paper traces the evolution of studies on biomarker genetics over the past 40 years through examples drawn from the work of Professor Martin and his colleagues.

Comparison of Familial, Polygenic and Biochemical Predictors of Mortality.

Mortality risk is known to be associated with many physiological or biochemical risk factors, and polygenic risk scores (PRSs) may offer an additional or alternative approach to risk stratification. We have compared the predictive value of common biochemical tests, PRSs and information on parental survival in a cohort of twins and their families. Common biochemical test results were available for up to 13,365 apparently healthy men and women, aged 17-93 years (mean 49.0, standard deviation [SD] 13.7) at blood collection. PRSs for longevity were available for 14,169 study participants and reported parental survival for 25,784 participants. A search for information on date and cause of death was conducted through the Australian National Death Index, with median follow-up of 11.3 years. Cox regression was used to evaluate associations with mortality from all causes, cancers, cardiovascular diseases and other causes. Linear relationships with all-cause mortality were strongest for C-reactive protein, gamma-glutamyl transferase, glucose and alkaline phosphatase, with hazard ratios (HRs) of 1.16 (95% CI [1.07, 1.24]), 1.15 (95% CI 1.04-1.21), 1.13 (95% CI [1.08, 1.19]) and 1.11 (95% CI [1.05, 1.88]) per SD difference, respectively. Significant nonlinear effects were found for urea, uric acid and butyrylcholinesterase. Lipid risk factors were not statistically significant for mortality in our cohort. Family history and PRS showed weaker but significant associations with survival, with HR in the range 1.05 to 1.09 per SD difference. In conclusion, biochemical tests currently predict long-term mortality more strongly than genetic scores based on genotyping or on reported parental survival.

Associations between polygenic risk for tobacco and alcohol use and liability to tobacco and alcohol use, and psychiatric disorders in an independent sample of 13,999 Australian adults.

BACKGROUND: Substance use, substance use disorders (SUDs), and psychiatric disorders commonly co-occur. Genetic risk common to these complex traits is an important explanation; however, little is known about how polygenic risk for tobacco or alcohol use overlaps the genetic risk for the comorbid SUDs and psychiatric disorders. METHODS: We constructed polygenic risk scores (PRSs) using GWAS meta-analysis summary statistics from a large discovery sample, GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN), for smoking initiation (SI; N = 631,564), age of initiating regular smoking (AI; N = 258,251), cigarettes per day (CPD; N = 258,999), smoking cessation (SC; N = 312,273), and drinks per week (DPW; N = 527,402). We then estimated the fixed effect of these PRSs on the liability to 15 phenotypes related to tobacco and alcohol use, substance use disorders, and psychiatric disorders in an independent target sample of Australian adults. RESULTS: After adjusting for multiple testing, 10 of 75 combinations of discovery and target phenotypes remained significant. PRS-SI (R2 range: 1.98%-5.09 %) was positively associated with SI, DPW, and with DSM-IV and FTND nicotine dependence, and conduct disorder. PRS-AI (R2: 3.91 %) negatively associated with DPW. PRS-CPD (R2: 1.56 %-1.77 %) positively associated with DSM-IV nicotine dependence and conduct disorder. PRS-DPW (R2: 3.39 %-6.26 %) positively associated with only DPW. The variation of DPW was significantly influenced by sex*PRS-SI, sex*PRS-AI and sex*PRS-DPW. Such interaction effect was not detected in the other 14 phenotypes. CONCLUSIONS: Polygenic risks associated with tobacco use are also associated with liability to alcohol consumption, nicotine dependence, and conduct disorder.

Metabolomics reveals a link between homocysteine and lipid metabolism and leukocyte telomere length: the ENGAGE consortium.

Telomere shortening has been associated with multiple age-related diseases such as cardiovascular disease, diabetes, and dementia. However, the biological mechanisms responsible for these associations remain largely unknown. In order to gain insight into the metabolic processes driving the association of leukocyte telomere length (LTL) with age-related diseases, we investigated the association between LTL and serum metabolite levels in 7,853 individuals from seven independent cohorts. LTL was determined by quantitative polymerase chain reaction and the levels of 131 serum metabolites were measured with mass spectrometry in biological samples from the same blood draw. With partial correlation analysis, we identified six metabolites that were significantly associated with LTL after adjustment for multiple testing: lysophosphatidylcholine acyl C17:0 (lysoPC a C17:0, p-value = 7.1 × 10-6), methionine (p-value = 9.2 × 10-5), tyrosine (p-value = 2.1 × 10-4), phosphatidylcholine diacyl C32:1 (PC aa C32:1, p-value = 2.4 × 10-4), hydroxypropionylcarnitine (C3-OH, p-value = 2.6 × 10-4), and phosphatidylcholine acyl-alkyl C38:4 (PC ae C38:4, p-value = 9.0 × 10-4). Pathway analysis showed that the three phosphatidylcholines and methionine are involved in homocysteine metabolism and we found supporting evidence for an association of lipid metabolism with LTL. In conclusion, we found longer LTL associated with higher levels of lysoPC a C17:0 and PC ae C38:4, and with lower levels of methionine, tyrosine, PC aa C32:1, and C3-OH. These metabolites have been implicated in inflammation, oxidative stress, homocysteine metabolism, and in cardiovascular disease and diabetes, two major drivers of morbidity and mortality.

New alcohol-related genes suggest shared genetic mechanisms with neuropsychiatric disorders.

Excessive alcohol consumption is one of the main causes of death and disability worldwide. Alcohol consumption is a heritable complex trait. Here we conducted a meta-analysis of genome-wide association studies of alcohol consumption (g d-1) from the UK Biobank, the Alcohol Genome-Wide Consortium and the Cohorts for Heart and Aging Research in Genomic Epidemiology Plus consortia, collecting data from 480,842 people of European descent to decipher the genetic architecture of alcohol intake. We identified 46 new common loci and investigated their potential functional importance using magnetic resonance imaging data and gene expression studies. We identify genetic pathways associated with alcohol consumption and suggest genetic mechanisms that are shared with neuropsychiatric disorders such as schizophrenia.